Category: Information Systems

Information systems (IS) refer to the combination of hardware, software, data, people, and processes that work together to collect, process, store, and disseminate information within an organization. These systems stand designed to support the management, operations, and decision-making processes of a business or other entities.

Key components and characteristics of information systems include:

  1. Hardware: This includes computers, servers, networking devices, storage devices, and other physical equipment necessary for data processing and communication.
  2. Software: IS relies on software applications and programs that facilitate data manipulation, analysis, and reporting. Examples include enterprise resource planning (ERP) systems, customer relationship management (CRM) software, and business intelligence tools.
  3. Data: IS collects and stores data from various sources, such as customers, transactions, inventory, and financial records. Data serves as the foundation for generating information and insights.
  4. People: IS require skilled professionals to design, implement, manage, and use them effectively. This includes IT professionals, database administrators, system analysts, and end-users who interact with the systems.
  5. Processes: IS stand guided by defined processes and workflows that govern how data collects, processed, and transforms into meaningful information. Business processes and data flows stand often mapped within the system.
  6. Integration: IS often integrates with other systems and applications, facilitating seamless data exchange and enhancing business efficiency.
  7. Security: IS incorporates security measures to protect data and prevent unauthorized access. This includes user authentication, encryption, and data backup.
  8. Decision Support: Many information systems provide decision support capabilities, offering relevant information and insights to support managerial decision-making.
  9. Reporting and Analytics: IS enables the generation of various reports and analytics to track performance, monitor trends, and support strategic planning.

Information systems play a crucial role in modern organizations, supporting daily operations, improving productivity, and aiding strategic decision-making. They stand utilized in various industries, including healthcare, finance, manufacturing, education, and government. Organizations invest in information systems to gain a competitive advantage, enhance customer experiences, and adapt to the fast-paced digital landscape. Effective implementation and management of information systems contribute to increased efficiency, improved data accuracy, and enhanced organizational performance.

  • Best HRIS Systems for Midsize Companies

    Best HRIS Systems for Midsize Companies

    Discover the best HRIS systems for midsize companies in our comprehensive guide. Learn why investing in an HRIS is essential for growth, key features to consider, and how to compare top systems to streamline your HR processes and enhance employee experience.

    Streamline and Grow: Finding the Best HRIS Systems for Your Midsize Companies

    Growing your midsize company is exciting! You’re past the initial startup hustle and building momentum. But with growth comes complexity, especially when managing your valuable employees. Juggling spreadsheets, manual processes, and siloed data can quickly become overwhelming, hindering your ability to scale efficiently and focus on what truly matters: your people and your business goals.

    That’s where a Human Resources Information System (HRIS) comes in. It’s not just about digitizing paperwork; it’s about empowering your HR team, improving employee experience, and driving strategic decision-making. Finding the best hris systems for midsize companies can feel like navigating a crowded marketplace, but with the right guidance, you can find the perfect fit.

    This article is your friendly guide to navigating the world of HRIS and finding the solution that will help your midsize company thrive. We’ll explore why an HRIS is crucial for your stage of growth, highlight key features to look for, and introduce some of the leading contenders in the market. Let’s dive in!

    Why Now is the Time for an HRIS

    Midsize companies often reach a point where their HR needs outgrow their existing manual or basic systems. Here’s why investing in an HRIS is a smart move:

    • Increased Efficiency: Automate time-consuming tasks like payroll processing, benefits enrollment, and leave management, freeing up your HR team to focus on more strategic initiatives.
    • Improved Data Accuracy: Eliminate the risk of manual errors and ensure consistent, reliable data across your organization.
    • Enhanced Compliance: Stay up-to-date with labor laws and regulations, minimizing the risk of costly penalties.
    • Better Employee Experience: Provide employees with self-service access to their information, making it easier for them to manage their benefits, request time off, and access company resources.
    • Strategic Insights: Gain valuable data analytics on your workforce, allowing you to make informed decisions about talent management, compensation, and training.
    • Scalability: Choose a system that can grow with your company, adapting to your evolving needs as your workforce expands.

    Key Features to Look for in Your Midsize Company HRIS

    Not all HRIS systems are created equal. As a midsize company, you need a solution that balances robust functionality with affordability and ease of use. Here are some crucial features to consider:

    • Core HR: This is the foundation, including employee data management, organizational charts, and reporting functionalities.
    • Payroll Processing: Automated payroll calculations, tax deductions, and direct deposit. Integration with accounting software is a big plus.
    • Benefits Administration: Streamline open enrollment, manage employee benefits plans, and track eligibility.
    • Time and Attendance: Automated time tracking, absence management, and integration with payroll.
    • Talent Management: Features for recruitment, onboarding, performance management, and learning & development can be invaluable for growing teams.
    • Reporting and Analytics: Robust reporting capabilities to track key HR metrics and gain insights into your workforce.
    • Employee Self-Service (ESS): Empower employees to manage their personal information, access pay stubs, and request time off.
    • Mobile Accessibility: Allow employees and managers to access the system from anywhere, at any time.
    • Integration Capabilities: Seamless integration with other business systems like accounting software, applicant tracking systems (ATS), and project management tools.

    Top HRIS Systems for Midsize Companies: A Closer Look

    Choosing the right HRIS is a significant decision. To help you narrow down your options, here’s a table highlighting some of the best hris systems for midsize companies, along with their key features and considerations:

    HRIS SystemKey FeaturesStrengthsConsiderationsIdeal For
    BambooHRCore HR, Benefits Admin, Payroll (add-on), Time Tracking, Performance Management, ReportingUser-friendly interface, strong focus on employee experience, excellent customer support.Payroll is an additional cost, some advanced features may require higher-tier plans.Growing companies need a comprehensive solution that integrates HR and IT functions.
    RipplingUnified platform for HR, IT, and Finance, Core HR, Payroll, Benefits Admin, Time & Attendance, App ManagementCan be more complex to set up initially, and pricing can be higher depending on the modules chosen.Highly versatile platform, with excellent automation capabilities, strong for tech-savvy organizations.Can be less intuitive than some other systems, and pricing can be less transparent.
    PaylocityCore HR, Payroll, Benefits Admin, Time & Attendance, Talent Management, Learning Management, Applicant TrackingStrong payroll processing capabilities, comprehensive suite of HR tools, good for compliance.Simple and intuitive interface, good for companies with limited HR staff, and integrated compliance features.Companies with complex payroll needs and a desire for an all-in-one HR platform.
    Zenefits (Now Zenefits People Operations)Core HR, Benefits Admin, Payroll, Time & Attendance, HR Advisory Services (add-on)Can be a more significant investment, but implementation can be complex and time-consuming.Some users report limitations in advanced reporting and customization options.Smaller midsize companies looking for a straightforward and affordable HR solution.
    Workday HCMCore HR, Payroll, Benefits Admin, Talent Management, Learning, Compensation, Workforce Planning, AnalyticsEnterprise-grade capabilities, highly customizable, robust analytics and reporting.An established player in the HR industry, a wide range of features and services, and strong compliance expertise.Larger midsize companies with complex HR needs and a focus on data-driven decision-making.
    ADP Workforce NowCore HR, Payroll, Benefits Admin, Time & Attendance, Talent Management, Compliance SupportCan feel less modern than some newer platforms, and customer service can be inconsistent.An established player in the HR industry, with a wide range of features and services, and strong compliance expertise.Companies seeking a well-established and reliable platform with a wide breadth of features.

    Beyond the Feature Set: Choosing the Right Fit

    While features are crucial, selecting the best hris systems for midsize companies involves considering other important factors:

    • Budget: HRIS solutions vary in price, often based on the number of employees and the features you need. Factor in implementation costs, ongoing support fees, and potential add-on costs.
    • Ease of Use: A user-friendly interface will ensure higher adoption rates and reduce training time for both HR administrators and employees.
    • Implementation Process: Understand the vendor’s implementation process, including data migration, training, and ongoing support.
    • Customer Support: Reliable and responsive customer support is essential, especially during implementation and when you encounter issues.
    • Scalability: Ensure the system can grow with your company and adapt to future needs.
    • Security: Data security is paramount. Inquire about the vendor’s security measures and compliance certifications.

    Making the Right Choice for Your Company

    Choosing the best hris systems for midsize companies is a unique process for each organization. Here are some final tips to guide your decision:

    • Define Your Needs: Clearly outline your current HR challenges and future goals. What processes do you need to streamline? What data do you need to track?
    • Involve Your Team: Gather input from your HR team and other stakeholders who will be using the system.
    • Request Demos: Schedule demos with several vendors to see the systems in action and ask specific questions.
    • Check References: Speak to other companies of a similar size and industry who are using the systems you are considering.
    • Start Small, Scale Up: Consider starting with core HR functionalities and adding modules as your needs evolve.

    Conclusion: Empowering Your Growth with the Right HRIS

    Investing in the right HRIS is a strategic move that can significantly impact the efficiency, productivity, and overall success of your midsize company. By understanding your needs, evaluating key features, and carefully considering your options, you can find the best hris systems for midsize companies that will empower your HR team, enhance the employee experience, and ultimately help your business reach its full potential. Take the time to explore your options, ask the right questions, and choose a partner that will support your growth journey every step of the way.

  • Definition Examples Advantages and Disadvantages of Python

    Definition Examples Advantages and Disadvantages of Python

    A comprehensive guide to understanding Python, including its definition, advantages, disadvantages, features, and examples. It is a versatile and high-level programming language that was created by Guido van Rossum and first released in 1991. It knows for its simplicity, readability, and ease of use, making it an excellent choice for beginners as well as experienced developers.

    Python: A Guide to Its Examples with Advantages and Disadvantages

    Python is an interpreted language, which means it does not need to compile before running. This makes it highly productive and allows for quick iteration during the development process. It also has a vast and active community. Which has contributed to the creation of a large number of libraries and frameworks that extend its functionality.

    Some key features of Python include:

    • Easy to learn: Python uses a clean and straightforward syntax that emphasizes readability, making it an ideal language for beginners.
    • Extensive standard library: Python comes with a comprehensive standard library that provides ready-to-use modules and functions for a wide range of tasks, such as working with files, networking, and handling data structures.
    • Cross-platform: Python is available on multiple platforms, including Windows, macOS, and Linux, allowing developers to write code that can run on different operating systems.
    • Large ecosystem: Python has a vibrant ecosystem with a vast collection of third-party packages and frameworks. These libraries allow developers to build various applications. Such as web development with Django, scientific computing with NumPy and Pandas, machine learning with TensorFlow and PyTorch, and much more.

    Python stands widely used in various domains, such as web development, data analysis, scientific computing, artificial intelligence, and automation. Its versatility and ease of use have made it one of the most popular programming languages in the world.

    Meaning of Python

    Python is a programming language renowned for its simplicity and readability. It was created by Guido van Rossum and first released in 1991. Python is an interpreted language, which means the code executes line by line without the need for a compilation step. It prioritizes developer productivity and code readability, making it an excellent choice for beginners and experienced programmers alike.

    Python has a vast ecosystem and a vibrant community, offering a wide range of libraries and frameworks for various purposes, from web development to data analysis and machine learning. Its versatility, combined with its clean syntax, has contributed to its popularity among developers worldwide.

    Definition of Python

    Python is a widely-used, high-level programming language known for its simplicity and readability. It was developed by Guido van Rossum and first released in 1991. Python focuses on providing clear and concise syntax, making it easy to read and write code.

    One of Python’s key features is its versatility, as it can use for a wide range of applications, including web development, data analysis, scientific computing, artificial intelligence, automation, and more. It offers a vast standard library and a thriving ecosystem of third-party packages, allowing developers to leverage existing code and tools to streamline their projects.

    Python is an interpreted language, meaning that it does not need to compile before running. This dynamic nature allows for a quicker development cycle and easier debugging. It also supports multiple programming paradigms, including procedural, object-oriented, and functional programming styles.

    The popularity of Python is driven by its simplicity, scalability, and community support. It has a large and active community of developers who contribute to its continuous growth and improvement. Python has gained a reputation for being beginner-friendly, offering an accessible entry point for those new to programming while remaining powerful enough to meet the needs of experienced developers. How to Identify the Advantages and Disadvantages of Python.

    Definition Examples Advantages and Disadvantages of Python Image
    Photo by Pixabay

    The Advantages of Python: A Comprehensive Guide

    Python offers several advantages that make it a popular choice among developers:

    Simplicity and Readability:

    Python uses a clean and straightforward syntax that emphasizes readability. Its code is easy to understand and write, making it an ideal language for beginners as well as experienced developers. This simplicity also contributes to faster development and easier maintenance of code.

    Versatility:

    Python is a versatile programming language that can use for a wide range of applications. Whether it’s web development, data analysis, scientific computing, artificial intelligence, automation, or even game development, Python has frameworks and libraries that make it suitable for various domains.

    Large Standard Library:

    Python comes with a comprehensive standard library. It provides a rich set of modules and functions for tasks such as file handling, networking, working with data structures, and more. This extensive library eliminates the need to write code from scratch and allows developers to save time and effort.

    Third-Party Packages and Frameworks:

    Python has a vibrant ecosystem with an extensive collection of third-party packages and frameworks. This ecosystem includes popular libraries such as Django for web development, NumPy and Pandas for data analysis, TensorFlow and PyTorch for machine learning, and many more. These packages significantly extend Python’s functionality and enable developers to build complex applications quickly.

    Cross-Platform Compatibility:

    Python is available on multiple platforms, including Windows, macOS, and Linux. This cross-platform compatibility allows developers to write code that can run seamlessly on different operating systems, making Python a flexible choice for application development.

    Great Community Support:

    Python has a large and active community of developers worldwide. This community actively contributes to the language’s growth and provides support through online forums, user groups, and extensive documentation. The strong community ensures that developers can find help, resources, and guidance whenever needed.

    Integration Capabilities:

    Python can easily integrate with other languages such as C, C++, and Java. This feature allows developers to leverage existing code from other languages and incorporate it into their Python projects. It also makes Python a suitable choice for integrating different systems and technologies.

    Overall, Python’s simplicity, versatility, extensive library support, and thriving community make it an excellent language for developers of all levels. Its advantages enable faster development, code reusability, and a wide range of applications, making Python one of the most popular programming languages in the world. Continue, Exploring the Advantages and Disadvantages of Python.

    The Disadvantages of Python: A Comprehensive Guide

    While Python is a powerful and popular programming language, it does have a few disadvantages that developers should consider:

    Speed:

    Python is an interpreted language, which means it is generally slower compared to languages like C or C++. This can be a disadvantage when developing applications that require high-speed processing or real-time execution. However, it’s important to note that Python offers options for optimizing performance, such as using libraries written in faster languages or optimizing critical sections of code.

    Limited Mobile Development:

    Python is not as widely used in mobile app development as languages like Java or Swift. While there are frameworks like Kivy and BeeWare that facilitate Python app development, they may not have the same level of support or functionality as native frameworks specific to mobile platforms.

    Global Interpreter Lock (GIL):

    Python has a Global Interpreter Lock, which is a mechanism that ensures thread safety by allowing only one thread to execute Python bytecode at a time. This can limit the performance of multi-threaded applications in certain scenarios where parallelism require. As only one thread can effectively utilize multiple cores. However, it’s important to note that the GIL primarily affects CPU-bound tasks and does not significantly impact I/O-bound tasks or applications that heavily utilize external libraries written in other languages.

    Mobile Computing:

    While Python has frameworks like Kivy and BeeWare for mobile app development, it may not be the most efficient choice for resource-intensive mobile applications that require optimal performance in terms of memory usage and battery life. Native frameworks specific to mobile platforms may offer better performance optimizations in these scenarios.

    Less Suitable for Low-Level System Programming:

    Python is a high-level language, which means it is less suited for low-level system programming compared to languages like C or C++. While Python can interface with low-level languages through modules or libraries, it may not be the best choice for tasks that require low-level hardware access or fine-grained control over system resources.

    Packaging and Distribution:

    Packaging and distributing Python applications can sometimes be challenging, especially when dependencies and specific versions need to manage. Although tools like pip and virtual environments help streamline this process, it can still be a concern for complex projects with numerous dependencies.

    Compatibility:

    In certain cases, Python updates and changes to the language may introduce incompatibilities with older versions. This can make it necessary to update and modify existing code to ensure compatibility. However, the Python community and ecosystem typically provide migration guides and tools to ease the transition between major versions.

    Despite these disadvantages, Python’s ease of use, versatility, and large ecosystem of libraries and frameworks continue to make it a popular choice among developers for a wide range of applications. Ultimately, the suitability of Python depends on the specific requirements of the project at hand. Above, You may know to understand the Top 7 Advantages and Disadvantages of Python.

    Examples of Python

    Python can use for a wide range of applications. Here are a few examples of what you can do with Python:

    1. Web Development: Python has frameworks like Django and Flask that make web development quick and efficient. You can build dynamic websites, web applications, and even APIs using Python.
    2. Data Analysis: Python is widely used in data analysis and scientific computing. Libraries like NumPy and Pandas provide powerful tools for data manipulation, analysis, and visualization.
    3. Machine Learning: Python has gained popularity in the field of machine learning. Libraries like TensorFlow, Keras, and PyTorch make it easier to build and train machine-learning models.
    4. Automation: Python is great for automating repetitive tasks. Whether it’s file manipulation, web scraping, or interacting with APIs, Python can help you automate these tasks and save time.
    5. Scripting: Python is often used as a scripting language due to its simplicity and ease of use. You can write scripts to perform specific tasks or automate workflows.
    6. Game Development: Python has libraries like Pygame that allow you to create games. While it may not be the best choice for high-performance games, it’s a great option for 2D games and prototyping.
    7. Internet of Things (IoT): Python can use to program and control IoT devices. Its simplicity and versatility make it a good choice for developing IoT applications.
    8. Natural Language Processing (NLP): Python has libraries like NLTK and SpaCy that enable you to work with text data for tasks like sentiment analysis, language translation, and text classification.

    These are just a few examples of what you can do with Python. The language’s versatility and extensive library support make it suitable for a wide range of applications.

    Bottom line

    Python is a versatile and high-level programming language known for its simplicity and readability. It was created by Guido van Rossum and first released in 1991. Python is an interpreted language, which means it does not require compilation before running. This allows for quick iteration during development. It has a large and active community that has contributed to a vast collection of libraries and frameworks.

    Some key qualities of Python include easy learning, extensive standard library, cross-platform compatibility, and a large ecosystem of third-party packages and frameworks. Python stands widely used in web development, data analysis, scientific computing, artificial intelligence, and automation. What are the Advantages and Disadvantages of Python?

    Python has advantages such as simplicity, versatility, a large standard library, third-party packages, cross-platform compatibility, great community support, and integration capabilities. However, it also has disadvantages like slower speed compared to compiled languages, limited mobile development, global interpreter lock, less suitability for low-level system programming, packaging and distribution challenges, and potential compatibility issues with older versions.

    Some examples of what can be done with Python include web development, data analysis, machine learning, automation, scripting, game development, IoT programming, and natural language processing. Overall, Python’s simplicity, versatility, extensive library support, and large community make it a popular choice among developers for a wide range of applications.

  • Definition Advantages Disadvantages Examples of CSS framework

    Definition Advantages Disadvantages Examples of CSS framework

    A comprehensive guide to understanding the CSS framework, including its definition, advantages, disadvantages, features, and examples. A CSS framework is a pre-prepared library of CSS styles and rules that provide a foundation for building websites or web applications. It consists of a collection of ready-made CSS classes and components that can easily apply to HTML elements to style and structure the content.

    A Comprehensive Guide to CSS Framework, its Definition, Advantages, Disadvantages, and Examples

    A CSS framework is a pre-prepared library of CSS styles and rules that provide a foundation for building websites or web applications. It consists of a collection of ready-made CSS classes and components. That can be easily applied to HTML elements to style and structure the content. CSS frameworks aim to streamline the web development process by providing a set of standardized styles, responsive layouts, and reusable UI components, allowing developers to quickly create visually appealing and consistent designs without starting from scratch.

    A Comprehensive Guide to CSS Framework Definition Advantages Disadvantages and Examples Image
    Photo by Christina Morillo

    Meaning of CSS framework

    A CSS framework is a collection of pre-written CSS styles and rules that provide a set of guidelines and tools for designing and managing the presentation of a website or web application. It offers a structured approach to web development by providing a standardized framework that helps streamline the design process and ensures consistency across different web pages. CSS frameworks typically include ready-made classes and components that can be easily applied to HTML elements, allowing developers to style their websites faster and with less code.

    These frameworks often include features like responsive layouts, grid systems, typography styles, button styles, and other UI components. Making it easier for developers to create visually appealing and functional designs. Using a CSS framework can save development time, improve code organization, and facilitate the creation of responsive and consistent user interfaces.

    Definition of CSS framework

    A CSS framework is a pre-developed toolkit or library that provides a set of standardized CSS styles and components to facilitate the process of web development. It offers a collection of reusable CSS classes, rules, and utilities that can easily apply HTML elements to style and structure web pages.

    CSS frameworks aim to simplify and streamline the design and layout process by providing a solid foundation and consistent styling guidelines. They typically include predefined styles for common elements such as typography, buttons, forms, grids, navigation menus, and more, allowing developers to quickly build and style web pages without having to start from scratch.

    In addition to ready-made styles, CSS frameworks often focus on responsive design, offering responsive grids and other responsive components that automatically adapt to different screen sizes and devices. This helps developers create websites that optimize for various devices and screen resolutions.

    By utilizing a CSS framework, developers can save time, maintain code consistency, and achieve a visually appealing and professional-looking design for their websites. How to Identify the advantages and disadvantages of the CSS framework? Below are:

    How to Recognize the Advantages of CSS Framework

    CSS frameworks offer several advantages that can greatly benefit web developers. Here are some of the main advantages of using a CSS framework:

    Rapid development:

    CSS frameworks provide a set of ready-made styles and components that can easily apply to web pages. This allows developers to quickly build and style websites without having to write CSS code from scratch. It saves time and effort, especially when working on projects with tight deadlines.

    Consistency:

    CSS frameworks enforce consistent styling guidelines across different web pages and projects. They establish a unified design language and ensure that all elements follow the same visual principles. This consistency improves user experience and helps maintain a professional and polished look throughout the website.

    Responsive design:

    Many CSS frameworks come with built-in responsive grids and components. This makes it easier for developers to create websites that adapt seamlessly to different screen sizes and devices. With responsive design features readily available, developers can build mobile-friendly websites without the need for extensive manual coding or third-party libraries.

    Cross-browser compatibility:

    CSS frameworks design to work well across various web browsers. They handle any differences in rendering and ensure a consistent experience for users, regardless of the browser they are using. This saves developers from spending extra time troubleshooting and fixing browser-specific CSS bugs.

    Code organization and scalability:

    CSS frameworks provide a structured approach to web development. They often come with a modular architecture that encourages the separation of concerns and allows for easy maintenance and scalability. With the help of CSS frameworks, developers can keep their codebase organized, reusable, and easily maintainable as their projects grow.

    How to Recognize the Disadvantages of CSS Framework

    While CSS frameworks offer many advantages, there are also some potential disadvantages that developers should consider:

    Learning curve:

    CSS frameworks often come with their own set of conventions, classes, and syntax. This means that developers need to invest time in learning how to effectively use the framework and understand its architecture. This initial learning curve can slow down the development process, especially for those who are unfamiliar with the specific framework.

    Limited flexibility:

    CSS frameworks design to provide a consistent and predefined set of styles and components. While this can be advantageous for maintaining a consistent design language. It can limit the flexibility and creativity of developers who want to create unique and unconventional designs. Developers may find themselves constrained by the framework’s predefined styles, which can require additional effort to customize or override.

    File size and performance:

    CSS frameworks often come with a significant file size due to the inclusion of various styles, components, and utilities. This can increase the overall page load time, especially on networks with slower internet speeds or on mobile devices. Additionally, using a large CSS framework may result in unnecessary styling being loaded for elements. That is not utilized on the website, potentially impacting performance.

    Unused styles and bloated code:

    Since CSS frameworks provide a wide range of predefined styles and components, developers may end up including styles that are not necessary for their specific project. Also, This can result in bloated and unnecessary code, which impacts the efficiency and maintainability of the project. Additionally, overriding or modifying the default styles can lead to more complex and hard-to-maintain code.

    Dependency on the framework:

    When using a CSS framework, developers become dependent on its ongoing development and support. If a framework becomes outdated, lacks updates, or its community support declines, developers may face challenges in maintaining and updating their projects. This can result in the need to migrate to a different framework or invest additional time and also effort in maintaining the existing codebase.

    Features of CSS framework

    CSS frameworks typically offer a range of features that can greatly benefit web developers. Here are some commonly found features of CSS frameworks:

    • Grid systems: CSS frameworks often include responsive grid systems that provide a structured layout for web pages. These grids help developers create responsive designs that automatically adapt to different screen sizes, making it easier to build consistent and visually appealing layouts.
    • Typography styles: CSS frameworks offer a variety of pre-defined typography styles, such as headings, paragraphs, lists, and more. These typographic styles ensure consistency in font sizes, line heights, and margins, simplifying the process of styling text across a website.
    • Buttons and form styles: CSS frameworks provide ready-made styles for buttons and form elements, allowing developers to quickly create visually appealing and consistent user interfaces. Also, This includes button sizes, colors, hover effects, and form input styles.
    • Responsive utilities: Many CSS frameworks include responsive utility classes that make it easier to build responsive designs. These utilities enable developers to hide or show elements based on the screen size, apply different styles for different devices, and also handle responsive layouts more efficiently.
    • Component libraries: CSS frameworks often come with a set of reusable UI components. Such as navigation menus, cards, modals, sliders, and more. These pre-built components can be easily customized and integrated into web pages, saving developers time and effort in designing and coding these elements from scratch.

    Examples of CSS framework

    Here are some popular examples of CSS frameworks:

    • Bootstrap: Bootstrap is one of the most well-known and widely used CSS frameworks. It provides a comprehensive collection of CSS styles, components, and JavaScript plugins. Also, Bootstrap offers a responsive grid system, typography styles, forms, buttons, navigation bars, and much more. It is known for its ease of use and extensive documentation.
    • Foundation: Foundation is another popular CSS framework that focuses on responsive design and building mobile-first websites. Also, It offers a flexible grid system, customizable UI components, and a range of utility classes. Foundation provides a clean and modular approach to web development and has robust community support.
    • Bulma: Bulma is a lightweight and modern CSS framework that emphasizes simplicity and flexibility. It provides a responsive grid, typography styles, form elements, and a variety of UI components. Bulma is class-based, making it easy to use and customize. Also, It doesn’t rely on JavaScript, making it a good choice for performance-conscious developers.
    • Tailwind CSS: Tailwind CSS is a highly customizable CSS framework that takes a utility-first approach. It provides a large set of utility classes that can be combined to create complex and unique designs. Tailwind CSS offers a responsive grid system, typography styles, form styles, and more. Also, It allows developers to build websites with a lot of flexibility and control over the design.
    • Materialize CSS: Materialize CSS is a framework based on Google’s Material Design principles. It offers a wide range of UI components, including cards, buttons, forms, and navigation bars. Materialize CSS provides a responsive grid system and a set of predefined color palettes. Also, It is popular among developers who want to create visually appealing and modern-looking websites.

    Bottom line

    A CSS framework is a pre-prepared library of CSS styles and rules that provide a foundation for building websites or web applications. It consists of a collection of ready-made CSS classes and components. That can be easily applied to HTML elements to style and also structure the content. CSS frameworks aim to streamline the web development process by providing a set of standardized styles, responsive layouts, and reusable UI components. What are the Advantages and Disadvantages of the CSS Framework? They offer several advantages, including rapid development, consistency, responsive design, cross-browser compatibility, code organization, and community support.

    However, there are also potential disadvantages to consider, such as a learning curve, limited flexibility, file size and performance concerns, unused styles and bloated code, dependency on the framework, increased specificity and conflicts, and lack of customization options. CSS frameworks commonly include features like grid systems, typography styles, buttons and form styles, responsive utilities, component libraries, cross-browser compatibility, customization options, documentation, and community support.

  • Enterprise Wide System Computing Background Significances

    Enterprise Wide System Computing Background Significances

    Background and Significances of Enterprise Wide System Computing; Current breakthroughs in information technology have enabled the worldwide usage of distributed computing systems, leading to decentralize management of information. This has been supported by and has become inflamed great competition in business through faster and more precise data storage and retrieval and information processing. Several organizations have accomplished high efficiency, comprising ease of use and lesser costs in operations by adopting a client/server computing structure.

    Here is the article to explain, How to define Enterprise Wide System Computing with Background and Significances!

    Furthermore, system integration and interoperability issues are being intensified as institutions and organizations are moving from mainframe-based processes toward an open, distributed computing environment, and this situation is pressing corporations into an accelerated construction of extensive distributed systems for operational use. Technological transformations are at this point are happening and accelerating very fast that it may increase the computational power just same as the creation of desktop and personal computers did. Soon a lot of demanding computer applications will no longer be executed mainly on supercomputers and singular workstations relying on local data sources.

    Alternatively enterprise-wide systems, and eventually nationwide systems will be used that include workstations, vector supercomputers, and parallel supercomputers linked by a local and wide-area network. With this technology, users will be displayed with the illusion of a singular and highly powerful computer, rather than a collection of moderate machines. The system will program the application components on processors, administer data transfer, and it provides communication and synchronization to dramatically enhance application performance.

    Barriers;

    Furthermore, barriers between computers will exist concealed; similarly accompanied by the location of data as well as the drawback of processors. To demonstrate the theory of an enterprise-wide system, first think about the workstation or personal computer on a table. It can run the applications by a ratio that is generally a function of its expense; manipulate local data kept on a local disk, and perform printouts on local printers. Sharing of resources among other users is minimal and also hard. If the workstation stands joined to a local area network, not only the resources of the workstation are available; but so with the network file and printer stands made available to users and shared. This enables expensive equipment such as hard disks and printers to share and permits data to share between users on the Local area network.

    With these types of system structures, processing resources can divide and share in a method by remote login to another machine. To understand an enterprise-wide system, a lot of systems under a bigger organization; such as a company, or academic institution connected; so they will become additionally powerful resources such as parallel machines and vector supercomputers. Still, connection solely does not construct an enterprise-wide system. To transform a collection of devices with machines into an enterprise-wide system requires software that can perform sharing resources; such as processor cycles and databases similarly as easy as sharing files and printers on a Local area network.

    Background Of Enterprise Wide system Computing;

    The enterprise-wide computing environment is distinct from conventional host-centric information technology environments that support traditional types of information systems. In a host-centric computer surrounding and environment; for example, a mainframe, each information system, and the application deal with its corresponding technical responsibilities independent of the other groups. The group’s productions stand worked together. However, there is an intense level of independence as well as separation among the groups. In the host-centric environment, the operating system along with application software work by processing system resource applications between the software layers in a hierarchical method.

    This allows the application’s group to construct programs and transport the source program to the production environment for collection; while not corrupting different application software products. In the situation of an interruption, the program stands backed out of the production surroundings; and the clients carry on their regular roles using an earlier version of the program. Application computer programmers exist in a somewhat isolated world and system management is not an interest. This is a usual support approach for an organization that used this traditional system and software approach. Host-centric computing environments developed for the time when hierarchical organizations were the pattern. As an outcome, the information technology fields of this period existed hierarchically structured.

    Backgrounds 01;

    Furthermore, at that time information technology existed designed, and deployed to support hierarchical organizational structures. Meanwhile, in the enterprise-wide computing environment, enterprise-wide client/server information systems existed developed to fit different organizational structures; for example, flat and matrix, which differs from the traditional where it only fixed with the hierarchical organization structure. Client/server application provides the versatility and diversity required to support these various organizational structures. Client/server technologies allow software systems to converse with each other through a network.

    The systems connect clients and servers through a network that supports distributed computing, diagnosis, and presentation, given a common approach for distributing computer authorization within organizations. A client is a program that attaches to a system to request resources, and a server is a program that runs on a device listening on a designated part of the network wait for different programs to connect to it. Client/server information systems can operate separately in standalone networks or moreover, regularly as a portion of an enterprise-wide network.

    Backgrounds 02;

    In this scenario, a client/server computing structure provides for the network connection of any computer or server to any other computer; allowing desktops to connect to a network and access various servers or other system resources easily. In comparison, host-centric traditional information systems run in a standalone environment. Client/server technology divided the information system into three layers. The first layer, the presentation layer, is the portion of the information systems that the customer views.

    For example, a website downloaded from www.dell.com presents text, pictures, video, etc. By this level, the customer inserts buying information into the dell server. The second layer is the operation layer where the algorithms execute and also the general data manipulation takes place. At the dell server, the customer’s data exists processed. For example, credit card confirmation and a total exist decided derived from the number of items bought. In the third layer, the data layer, information exists kept and fetched from the dell databases. The three layers exist in host-centric traditional information, however, execute on a particular computer.

    The Significances Of Enterprise Wide system Computing;

    The arrangement of business strategies for an organization’s information technology is a repetitive subject in an information system scope and has appeared obviously in the latest surveys of critical concerns for information system management. Present-day corporate downsizing patterns have had the effect of flattening organization structures. Conversion of information systems has gone along with this organizational flattening.

    Various architectures have advanced during the transition from the monolithic centralized systems of the previous to the decentralized, distributed, client/server, and network-based computing architectures of the present day. Despite their diversities, many of these architectures share an important attribute allocation of processing jobs or data through various computing platforms. On simple occasions, this might require saving data or applications on a local area network server and retrieving it using a personal computer.

    Further complicated situations, is when encountering partitioning of databases and application programs, data migration, multiphase database updates, and many more. The common thread in these scenarios is the use of enterprise-wide computing to accomplish a single task. The speedy enterprise-wide computing growth during the 1990s has transformed the information system roles; and its management in many institutions as well as organizations.

    Significances 01;

    The attributes of this transformation frequently comprise a downsizing of systems apart from mainframe environments to smaller platforms, paired with network-based access to information management. In different situations, it has been an increase in the dimension and sophistication of end-user-developed systems; or the upscaling of departmental or local area network-based computing, alongside local area networks; that have become the repositories for mission-critical corporate information.

    Computing difficulties that once stood allocated to mainframe computers exist now regularly allocated to desktop computing platforms. Cost performance ratios keep on improving dramatically over reasonably short periods. The arrival of the Internet and the Web offer exceptional chances as well as demanding management problems. In the middle of an expanding set of technology alternatives, information system managers must; however, encounter basic inquiries about the character of underlying technology infrastructures; and the application of rapidly changing technologies to business decision making.

    The term “enterprise-wide computing architecture” stands being used to define the set of computing platforms in addition to the data networking facilities to support an organization’s information needs. Once upon a time fairly well-balanced in nature, architectures are at this point subject to frequent alteration as organizations attempt to achieve the best fit technology to their organizations. Given the expanding set of technological alternatives; this has got turn out to be no longer an easy task to achieve. It has become an important concern for information system managers since dependence on information technology increased.

    Significances 02;

    Regardless of this issue, efficient strategies for specifying an enterprise-wide computing architecture are however lacking. Architectures are the appearance of an organization’s overall information system approach. Technological integration is growing viewed as a way to support the overall strategic goals of a business. Appropriate architectures of enterprise-wide computing enable organizations to meet current information needs; and, to successfully adopt brand new information processing paradigms in a cost-effective method.

    The advantages of coordinated architectures comprise minimization of unacceptable redundancy of system components, appropriate measurement of information processing roles to platforms, significant allocation of computing resources to organization locations; as well as the capability to share information resources among organizational bodies at a manageable expense. The idea behind enterprise-wide computing includes the capability to centrally control; and, manage numerous software distributions across a huge number of clients’ workstations.

    Administering over one hundred applications across more than one thousand desktops in the enterprise-wide environment can turn out to be an ominous assignment and a nightmare. But, finding and making use of the proper tools for this task can be the single most important goal to obtain. While IT organizations resume growing, so does the need for simplified management tools that can contribute to greater functionality. When the total of workstations and software applications exist taken care of in the desktop environments and carry on to grow from day to day; the organization must sequentially analyze the tools with which these environments administer.

    Enterprise Wide System Computing Background Significances Image
    Enterprise Wide System Computing Background Significances; Image by Goumbik from Pixabay.
  • Database Management System (DBMS) History

    Database Management System (DBMS) History

    What is the History of Database Management System (DBMS)? It is a computer software program that stands designed as the means of managing all databases that exist currently installed on a system hard drive or network. Different types of database management systems exist, with some of them designed for the oversight and proper control of databases that exist configured for specific purposes. Here are some examples of the various incarnations of DBMS technology that are currently in use, and some of the basic elements that are part of DBMS software applications. Data is a collection of facts and figures. The data collection was increasing day today and also they needed to store it in a device or software which is safer.

    Here is the article to explain, Database Management System (DBMS) Introduction and their History!

    What is DBMS? Database Management System (DBMS) is software for storing and retrieving users’ data while considering appropriate security measures. It consists of a group of programs that manipulate the database. The DBMS accepts the request for data from an application and instructs the operating system to provide the specific data. In large systems, a DBMS helps users and other third-party software to store and retrieve data. Also, DBMS allows users to create their databases as per their requirements. The term “DBMS” includes the use of the database and other application programs. It provides an interface between the data and the software application.

    Introduction to Database Management System (DBMS);

    A Database Management System (DBMS) is a set of computer programs that controls the creation, maintenance, and use of a database. It allows organizations to place control of database development in the hands of database administrators (DBAs) and other specialists. Also, DBMS is a system software package that helps the use of the integrated collection of data records and files known as databases. It allows different user application programs to easily access the same database. DBMSs may use any of a variety of database models, such as the network model or relational model. In large systems, a DBMS allows users and other software to store and retrieve data in a structured way.

    Instead of having to write computer programs to extract information, users can ask simple questions in a query language. Thus, many DBMS packages provide Fourth-generation programming language (4GLs) and other application development features. It helps to specify the logical organization for a database and access and use the information within a database. It provides facilities for controlling data access, enforcing data integrity, managing concurrency, and restoring the database from backups. A DBMS also provides the ability to logically present database information to users.

    History of Database Management System (DBMS);

    Here, are the important landmarks from history:

    • 1960 – Charles Bachman designed the first DBMS system
    • 1970 – Codd introduced IBM’S Information Management System (IMS)
    • 1976 – Peter Chen coined and defined the Entity-relationship model also known as the ER model
    • 1980 – Relational Model becomes a widely accepted database component
    • 1985 – Object-oriented DBMS develops.
    • 1990 – Incorporation of object-orientation in relational DBMS.
    • 1991 – Microsoft ships MS access, a personal DBMS and that displaces all other personal DBMS products.
    • 1995 – First Internet database applications
    • 1997 – XML applied to database processing. Many vendors begin to integrate XML into DBMS products.
    Charles Bachman;

    Charles Bachman was the first person to develop the Integrated Data Store (IDS); which existed based on a network data model for which he existed inaugurated with the Turing Award (The most prestigious award; which is equivalent to the Nobel prize in the field of Computer Science.). It existed developed in the early 1960s. In the late 1960s, IBM (International Business Machines Corporation) developed the Integrated Management Systems; which is the standard database system used to date in many places. Also, It stood developed based on the hierarchical database model.

    It was during the year 1970 that the relational database model existed developed by Edgar Codd. Also, Many of the database models we use today are relationally based. It stood considered the standardized database model from then. The relational model was still in use by many people in the market. Later during the same decade (1980’s), IBM developed the Structured Query Language (SQL) as a part of the R project. It stood declared as a standard language for the queries by ISO and ANSI.

    The Transaction Management Systems for processing transactions stood also developed by James Gray for which he has felicitated the Turing Award. Further, there were many other models with rich features like complex queries, datatypes to insert images, and many others. The Internet Age has perhaps influenced the data models much more. Data models stood developed using object-oriented programming features, embedding with scripting languages like HyperText Markup Language (HTML) for queries. With humongous data being available online, DBMS is gaining more significance day by day.

    More History of DBMS;

    Databases have been in use since the earliest days of electronic computing. Unlike modern systems which can be applied to widely different databases and needs, the vast majority of older systems were tightly linked to the custom; databases to gain speed at the expense of flexibility. Originally DBMSs were found only in large organizations with the computer hardware needed to support large data sets. Some types of DBMS are:

    1960s Navigational DBMS;

    As computers grew in speed and capability, several general-purpose database systems emerged; by the mid-1960s there were several such systems in commercial use. Interest in a standard began to grow, and Charles Bachman, the author of one such product, Integrated Data Store (IDS), founded the “Database Task Group” within CODASYL, the group responsible for the creation and standardization of COBOL. In 1971 they delivered their standard, which generally became known as the “Codasyl approach”, and soon there were several commercial products based on it available.

    1970s Relational DBMS;

    Edgar Codd worked at IBM in San Jose, California, in one of their offshoot offices that were primarily involved in the development of hard disk systems. He was unhappy with the navigational model of the Codasyl approach, notably the lack of a “search” facility. In 1970, he wrote several papers that outlined a new approach to database construction that eventually culminated in the groundbreaking A Relational Model of Data for Large Shared Data Banks.

    In this paper, he described a new system for storing and also working with large databases. Instead of records being stored in some sort of linked list of free-form records as in Codasyl, Codd’s idea was to use a “table” of fixed-length records. A linked-list system would be very inefficient when storing “sparse” databases where some of the data for anyone’s record could be left empty. The relational model solved this by splitting the data into a series of normalized tables, with optional elements being moved out of the main table to where they would take up room only if needed.

    Some differences between DBMSs;

    SQL (Structured query language) is a database computer language designed for managing data in relational database management systems (RDBMS) and originally based upon relational algebra. Its scope includes data insert, query, update and delete, schema creation and modification, and data access control. SQL was one of the first languages for Edgar F. Codd’s relational model in his influential 1970 paper, “A Relational Model of Data for Large Shared Data Banks” and became the most widely used language for relational databases.

    PHP (hypertext Preprocessor) provides a range of facilities to allow web database developers to retrieve data from a database and merge this dynamic content with static content on a web page. It includes the actual database(where the data are stored)and the DBMS, which manages all the access to the database, the application server manages communication with the database server with the DBMS API.

    Oracle DBMS;

    Oracle DBMS Oracle database system†”identified by an alphanumeric system identifier or SID †”comprises at least one instance of the application, along with data storage. An instance†”identified persistently by an instantiation number comprises a set of operating-system processes and memory structures that interact with the storage. In addition to storage, the database consists of online redo logs (or logs), which hold transactional history. Processes can in turn archive the online redo logs into archive logs (offline redo logs), which provide the basis (if necessary) for data recovery and some forms of data replication.

    The Oracle DBMS can store and execute stored procedures and functions within itself. PL/SQL (Oracle Corporation’s proprietary procedural extension to SQL), or the object-oriented language Java can invoke such code objects and/or provide the programming structures for writing them. Also, DBMS stands for Database Management System which is a general term for a set of software dedicated to controlling the storage of data.

    RDMBS stands for Relational Database Management System. This is the most common form of DBMS. Invented by E.F. Codd, the only way to view the data is as a set of tables. Because there can be relationships between the tables, people often assume that is what the word “relational” means. Not so. Codd was a mathematician and the word “relational” is a mathematical term from the science of set theory. It means, roughly, “based on tables.

    Database Management System (DBMS) History Image
    Database Management System (DBMS) History
  • Global Digital Divide Examples Essay

    Global Digital Divide Examples Essay

    The phrase global digital divide has become a global phenomenon and has taken the world by storm, with It an Essay and Examples. What exactly does this term mean and what does it entail? This phenomenon became current during the mid-1990s and define as the segregation between those; who have access to advanced forms of technology and those who do not have access to advanced forms of technology specifically between the developing and non-developing world.

    Here is the article to explain, The definition of Global Digital Divide with an Essay and Examples!

    The global digital divide is an ongoing debate that includes a variety of contributing factors that will discuss in this paper such as cultural, political, and economic issues specifically within the context of how two African nations South Africa and Mauritius are combating the global digital divide.

    Moreover, this paper will utilize the success story of Mauritius as a comparison of how once government institutions; and powers are actively involved within communities by providing subsidized internet access; the division caused by the global digital divide examples minimizes.

    Furthermore, this specific case study of Mauritius provides hope and ambition to other African states specifically in the context of South Africa; that if a community-supported with powerful institutions and federal resources combating the global digital divide examples is possible. Likewise, this paper will focus on both the quantitative and primarily the qualitative research measures that differ between how Mauritius successfully combated the global digital divide along with the obstacles; which hindered South Africa’s potential success of combating the digital divide; the challenges which prevented the success of South Africa.

    Essay Part 01;

    Additionally, Mauritius is a small island nation within the Sub-Saharan region of Africa. Mauritius has a population of about 1.2 million and an estimated 70% of the nation’s population aged between 15-64; as well as an estimated 88% are literate. Despite English being the official language; it spoke by less than 1% of the population, while the majority (80%) speak Creole.

    Interestingly enough, Mauritius existed previously colonized by both the Dutch and French; although either french or dutch are prominent languages in Mauritius. Mauritius adopted towards establishing an English-speaking nation after the colonial period; which has significantly helped them in the world trading market and ultimately increased the nation’s literacy rate to 88%. As well as “These efforts have​ been acknowledged in the e-government readiness ranking by United Nations”​.

    Furthermore, the government of Mauritius proposed a five-year National ICT Strategic Plan in 2007. This plan aspires to convert Mauritius into a favored hot spot for ICT skills, expertise, and employment in the region. Additionally, once Mauritius converts into an ICT hub; this will allow Mauritius to have the necessary skills they need to access the Internet without any challenges.

    Essay Part 02;

    Therefore, once this establishes the strategic plan also aims to target social indicators by the year 2011; which includes increasing personal ownership by at least 12,000 in primary schools, 20,000 in households; increasing broadband internet penetration by at least 250,000, and establishing 150 public internet kiosks across the island.

    Furthermore, the targeted installment of kiosks throughout Mauritius primarily in geographically located areas; such as rural neighborhoods has been positively linked with ICT use. Findings include that perceived usefulness and subjective norm are both factors that lead to the positive use of ICT.

    Perceived usefulness can define as “a degree to which an​ individual believes that using a particular technology would enhance performance”.

    To guarantee the relevance of internet kiosks, a diverse range of sources; such as internet browsing, word processing, health care, and e-mail is more efficient compared to third-party sources; which typically come at a cost. Thus, these advances are more likely to encourage the use of publicly subsidized Kiso’s.

    Essay Part 03;

    Additionally, the subjective norm positively links to ICT use. Subjective norm can define as “an individual’s perception of the extent to​ which important social referents would desire the performance of a behavior”, this factor is relevant in Mauritius. For example, if a relative or friend suggest the use of public internet kiosks is helpful and encourages one to make use of it; the individual is more likely to believe his or her friend or relative and in return has the motivation and intention to use the public internet kiosk.

    Moreover, this essay will focus on a case study of South Africa; and the challenges that this nation faces with combating the global digital divide. In the article Addressing the digital divide. Online information review (2001).​

    Cullen highlights that a major issue is the lack of physical access to ICT’s. The constraint with physical access to ICT use in South Africa is that the majority of ICT centers; and hubs are located in major cities as opposed to geographically isolated areas such as rural neighborhoods. Similarly, constantly commuting to these locations is not feasible along with another obstacle; which is the challenges that disabled people encounter.

    Essay Part 04;

    Therefore, not only are an absence of ICT use in rural areas but the commute cost is to the ICT centers is not feasible along with the significant challenges that these commutes can be for disabled people. Also, according to statistics on world connectivity; findings show that during the year 2000 South Africa’s number was 440,000 compared to Mauritius’s number of 1.8 million.

    Likewise, in the article Reevaluating the global digital divide: Socio-demographic and conflict barriers to the internet revolution. Sociological Inquiry (2010).​

    Robinson and Crenshaw, highlight a vital constraint towards Internet connectivity which is oftentimes dismissed. This constraint is the impact and influence that political leaders have on the nation. Nations which have liberal and democratic leaders are more likely to have citizens that are proactive and engaging in internet activity. Similarly, these leaders are also more likely to incorporate activities and programs; which motivate ICT use similarly to Mauritius Strategic Plan. Moreover, the turmoil of the post-apartheid conflict in South Africa is still significantly relevant in today’s society.

    Although this conflict occurred over 20 years ago, South Africa’s trajectory was stagnant for a few years; and it hasn’t been until recent presidential figures that democratic values became acceptable. Thus, this greatly impacts political institutions to confidently and successfully incorporate and introduce ICT; use simply because South Africa’s primary concern was moving past an apartheid government; basic values such as marrying someone of the opposite race; and freedom of speech were primary concerns rather than Internet connectivity.

    Essay Part 05;

    Additionally, in the article Information access for development: A case study at a rural community center in South Africa (2006).

    Jacobs and Hersleman argue the barriers which restrict ICT use in South Africa. These barriers include, “lack of awareness of the benefits of ICTs” ​ ​and”lack of ICT skills and​ support”. As mentioned above, South Africa is progressing rather slowly post-apartheid. This plays a significant role in the barriers of ICT use because; although they may have established ICT hubs in populated cities Capetown, Durban, and Soweto; there is one problem that contributes to both the lack of awareness of benefits and lack of ICT skills and support.

    This constraint is that “Facilities like community centers can assist by​ increasing user’s familiarity with technology in non-threatening, social settings”. Therefore, utilizing the staff and volunteers at community centers is imperative in increasing the motivation and engagement of ICT use; especially because incorporating ICT use at facilities such as community centers do not provide much use; if the community is unaware that these resources are available to them and how exactly they can access these resources.

    Essay Part 06;

    Furthermore, in the article Time machines and virtual portals: The spatialities of the digital divide. Progress in development studies ​ ​(2011).

    Graham highlights that cultural barriers play a significant role in contributing to the lack of Internet connectivity, information, and access. English is commonly spoken throughout South Africa; however, it does not speak outside of main cities such as Capetown and Durban.

    Also, not only is English not commonly spoken outside of these main cities, the degree of English use on computers or Kiosks and other forms of ICT are not at a beginner level.

    Ultimately, this creates a significant barrier to access to the Internet. Another challenge in South Africa is that has 10 main languages spoken throughout the country excluding English.

    The languages spoken depend on which region or part of South Africa an individual is in. Unlike Mauritius, English is not the most common and main language spoken in South Africa; therefore an alternative can be to provide translators at community centers or providing installing alternative language options on computer or kiosk settings.

    Essay Part 07;

    Moreover, in the article The impact of connectivity in Africa: Grand Visions and the mirage of inclusive digital development. The Electronic Journal of Information Systems in Developing​ Countries ​(2017).

    Friederici, Ojanperä, and Graham highlight that “telecommunication services have been​ found to lessen the financial vulnerability and susceptibility to shocks of poor households in South Africa”. Although, the poorest households may not necessarily benefit simply because they do not have access to telecommunication services.

    These constraints could be because poor households reside in rural areas; which do not have telecommunication services nearby and the commute cost is out of their means as well as the comprehension of English is poor. Unlike the Mauritius case study, the government and other institutions placed publicly subsidized kiosks in both rural and urban areas to mitigate the lack of mobility and accessibility as a constraint.

    Essay Part 08;

    Overall, the highlighted challenge that South Africa faces to combat or mitigate the global digital divide is the lack of physical access; ICT’s do not place in geographically isolated areas such as rural neighborhoods; thus making the commute costly and challenging for those with disabilities.

    Another challenge that South Africa faces is that there is a significant lack of awareness of present or available ICT’s and how exactly one can navigate ICT’s; community members do not encompass sufficient skills to navigate ICT’s. Furthermore, a final constraint that South Africa faces is a lack of English literacy.

    English spoke throughout South Africa, however, it is not the dominant language, and providing ICT’s with intricate levels of English is a barrier that prevents successful ICT use. Comparingly, Mauritius was successful in mitigating the global digital divide examples because English is their main language and they placed publicly subsidized kiosks in rural areas as well as provided the necessary skills needed to navigate kiosks.

    Essay Part 09;

    Moreover, as mentioned above there is a variety of contributing factors that have been constraints in South Africa’s success in combating the global digital divide. The supporting articles of the challenges that South Africa faces in this essay provide significant support for both quantitative and primarily quantitative research.

    Throughout, the articles surrounding South Africa, there has not been a great deal of statistical data as opposed to Mauritius. Additionally, South Africa’s recent history with geopolitical affairs and conflict plays a significant role in their trajectory towards combating the global digital divide.

    Mauritius had both fewer geopolitical and post-colonization obstacles compared to South Africa. As well, suggestions for South Africa are to place ICT’s in geographically isolated regions with different language options as well as advertising where ICTs can find along with having staff or volunteers at the ICT locations that are knowledgeable on how to successfully navigate ICT’s trajectory towards combating the global digital divide.

    It is clear that Mauritius had both fewer geopolitical and post-colonization obstacles compared to South Africa which allowed them to be successful in combating the global digital divide, further research needs to determine the current status of South Africa’s trajectory with the global digital divide. In conjunction, this paper demonstrates that if the government understands the need and importance of combating the global digital divide by incorporating publicly subsidized kiosks and other forms of ICT’s, it is possible to strengthen internet connectivity.

    The definition of Global Digital Divide with an Essay and Examples Image
    The definition of Global Digital Divide with an Essay and Examples! Image by StockSnap from Pixabay.
  • Big Data Visualization Techniques and Challenges

    Big Data Visualization Techniques and Challenges

    What are the Techniques and Challenges of Big Data Visualization in Information Systems Essay? This study examined what big data means with its importance of it and its usage in each industry along with visual analytics to drive success in their organization. Various types of big data analytics tools such as Tableau, PowerBI, SAS, etc. along with the comparison of the tools to discover the best fit based on a profile of a company and its goals also cover. We tried to examine how data visualization tools helped big technological giants to achieve competitive advantage taking care of the challenges that big data brings into visualization.

    Here is the article to explain, Techniques and Challenges of Big Data Visualization in Information Systems Essay!

    By 2025, it predicts that the value of data will increase by 10-fold. Virtually, every branch of industry or business will generate a vast amount of data. Thus, the world will experience aggressive growth and data could be a missed opportunity when not being utilized. And to make matter worse, the rate of collecting and storing data is faster than the ability to use them as tangible decision-making. With the help of ever-growing technology, visionaries are creating visualization methods to help turn raw data with no value into informative data.

    Big data has served a purpose for organizations to optimize their businesses. With an abundant amount of data that organizations generate every day, the ability to turn the data into a decision effectively and efficiently is crucial. Thus, the knowledge of analytics and visualization would come hand-in-hand to tackle the problem in big data. Hence, a new interdisciplinary research field of “Visual Analytics” is being established, in which its aims to make the best possible use of the information by combining intelligent data analysis with visual perception. The visual analytics knowledge has been quite useful to the two most common streams of the profession in the Big Data world, Data Scientists and Business Analytics.

    Business Analytics;

    Business Analytics (BA) define as a data-centric approach that relies heavily on the collection, extraction, and analysis tools to enable data to use as an insight as well as decision-maker; which in most disciplines, is being used by top-management people. Previously, BA existed used to report what has happened in the past, although nowadays, with the massive volume of data that can generate; BA can exploit them to predict the future and also make breakthroughs.

    Data Science;

    Through Big Data, the need to create a reliable source of information and a business support system has invented a new and widespread business application of Data Science. However, the art of data science is multifaceted, it combined the skills of computer science, advanced analytical and statistical skills, and knowledge of methods of visualizing data. Although there has been no universally accepted definition of Data Science; it defines as a set of fundamental principles that support and guide the principled extraction of information and knowledge of data.

    One of the main thing that visualization can help is projecting a model that data scientist has built to the reader. They usually play with data that has hundreds of dimensions that do not have the usual mapping point thus standard visualization such as bar chart, will not work. Therefore, novel visualization employing Parallel Coordinates and others techniques, usually used in this type of data. Secondly, visualization can help the process of Data Mining, which is the process that scientists aim to automatically extract valuable information from raw data through an automatic analysis algorithm. Visualization has been found to give benefit for the process; and would help the analysis to arrive at the optimal point as it helps to appropriately communicate; the results of the automatic analysis which often hand in the abstract demonstration.

    Big Data Visualization Essay;

    In the Visual Analytics Process above, the data that has been collected is being transformed according to the streams. For the Business Analytics (BA), the transformed data is mapping into a visualization for a user to process into knowledge, usually in a form of decisions; then the knowledge is feedbacking into the data for continuous improvement and to enable analysts to a better conclusion in the future.

    For the Data Science (DS) stream, the transformed data is mining to build a model; that would help certain objectives, the overall approach of the data is problem-agnostic. When certain models have been built; they would need to visualize as well, or vice versa. There is a feedback loop in between models and visualization to get the right outcome for the objectives. Furthermore, the knowledge comes from either visualization or models themselves.

    In general, visualization works as a better and faster way to identify patterns or trends; and any correlation that would otherwise remain undetected with a text or numbers figure. And visualization also helps to approach the problem in a new and creative way; that would tap into the human’s cognitive brain to understand the information hiding behind a huge number of data. The human can also interact with the visualization; which can utilize to find more insights or to find the right questions.

    Techniques in Big Data Visualization;

    According to user requirements, the visualization techniques decide. Conventional visualization makes use of tables, Venn diagrams, entity-relationship diagrams, bar charts, pie charts for data visualization. Below is the list of visualization techniques for visualizing large amounts of data and getting insight into it are:

    • One-dimensional; It consists of one value per data item or variable. The histogram is the perfect example of it.
    • Two-dimensional; As the name suggests, it has two variables. Bar charts, pie charts, scatter plots, maps are the type of 2D visualization.
    • Three Dimensional; This visualization will give more information to the user in the form of slicing techniques, Iso-surface, 3D bar charts, etc.
    • Multi-Dimensional; It will give a clearer picture of the visualization by analyzing the variables from a different perspective. Parallel coordinates, Auto graphics, etc. are the type of such visualization.
    • TreeMap; Here the data neste in form of the rectangle which represents each branch of the tree.
    • Temporal Technique; It has the scalability of displaying the data in a timeline, time series, and scatter plot.
    • Network technique; It use when you want to present data collected from social media in the form of a network.

    Challenges for Big Data Visualization or Visual Analytics;

    The main challenge with visual analytics is to apply visual analytics to big data problems. Generally, technological challenges such as computation, algorithm, database, and storage, rendering along with human perception; such as visual representation, data summarization, and abstraction are some of the common challenges. “The top 5 challenges in extreme-scale visual analytics” as addressed in the publication by SAS analytics are as follows:

    • Speed requirement; In-memory analysis and expanding memory should utilize to address this challenge.
    • Data understanding; There must be proper tools and professionals; who are proficient in understanding the data underneath the sea to make proper insight.
    • Information quality; One of the biggest challenges is managing large amounts of data and maintaining the quality of such data. The data needs to understand and presented in the proper format that increases its overall quality of it.
    • Meaningful output; Using the proper visualization technique according to the data presented is necessary to bring meaningful output to the data.
    • Managing outliers; While you cluster the data for favorable outcomes; it is obvious that an outlier will exist. Outliers cannot neglecte because they might reveal some valuable information and must treate separately in separate charts.
    What are the Techniques and Challenges of Big Data Visualization in Information Systems Essay Image
    What are the Techniques and Challenges of Big Data Visualization in Information Systems Essay? Image by StockSnap from Pixabay.
  • Best Cloud ERP System Solutions Essay for Small Business

    Best Cloud ERP System Solutions Essay for Small Business

    Best Cloud ERP System Solutions Essay, Definitions, Benefits, and Impact for Small Business; Enterprise Resource Planning (ERP) is a structure that use to manage and deliver solutions for the company. Enterprise Resource Planning (ERP) helps in the integration, implementation, management, planning, purchasing, marketing, sales, and inventory of an Information system. The data of the ERP management software is stored in the database using a database management system. The stored data should distribute among the departments of the company as a part of the process. It facilitates the information transfer among the departments which includes a lot of manual work as the data should manage and update manually.

    Here is the article to explain, Best Cloud ERP System Solutions Essay for Small Business!

    Cloud computing is a model for on-demand network access to a shared pool of resources like network, server, applications, and storage which has a minimal management effort or a service provider. On using cloud computing the users can share or view the shared data without any external resources. This achieves using the Software as a Service (SaaS) which provides the user to access the information given by the provider.

    SaaS (Software as a Service);

    The applications can be accessible by the users on personal systems in their small network. Also, The cloud helps the user to access their system within their comfort zone and which acts as the Software as a Service (SaaS).

    PaaS (Platform as a Service);

    The user can work on any platform or application using programming languages and different infrastructure; this is possible with the cloud and is known as Platform as a Service (PaaS).

    IaaS (Infrastructure as a Service);

    The cloud provides the user to store the data, work on the applications as well as manage the system with no installation of prior or excess software. Also, This calls Infrastructure as a Service (IaaS).

    Cloud computing plays a major role to reduce manual work in sharing the data. ERP which includes cloud is been introduced to overcome the problem. The data is shared among the departments of the company using Cloud (Internet) technology. The data of ERP is stored on the cloud which can share and accessed by the members of the company who have access to the system. Further, the cloud-based ERP definitions, Information System based definitions, key benefits of cloud ERP and taxonomies discuss.

    Definition of Cloud ERP or Cloud-Based ERP;

    They define as the on-premises or the hosted ERP on cloud computing technology. It is mostly required or useful for small and also medium enterprises (SMEs) for the improvement of the business.

    According to (Shivam, C., Ned, & David, 2018), Cloud ERP helps SMEs to benefit from the privileges of the ERP packages without installing IT (Information Technology) software/hardware. Moreover, it has less maintenance and removes the IT workforce. Based on the SME’s requirements the cloud service provider render. The cloud servicer provides a standard cloud ERP module on which a company can rely.

    There are vast benefits of the system which include cost minimalization in the infrastructure of the company, the operating cost as the cloud service providers manage the operations of cloud and services, scalability, improved accessibility, mobility, and usability. It also includes system availability and disaster recovery, security, integration, sales atomization, cost transparency, and free trials. Few other advantages of cloud ERP are enhancement of system speed and performance and an effective system upgrade.

    But, the views on cost minimalization of operating cost differs. Few authors specified that the Minimalization of operating cost is an advantage, whereas, the others argued that the cloud can use initially but as the organization is developing and the data is increasing the cost by small and medium enterprises is not affordable. Whereas, security plays a crucial in the cloud ERP. The main risk of the systems is the security of the database or the leakage of information.

    Other definitions;

    All the definitions stated above are similar in the case of cloud ERP systems including the risk of the database. The cloud ERP system is cloud-based rather than server infrastructure; which is used to help the companies to share the data or the information across the departments of the company. It integrates a few key functions financial management, inventory management, customer relationship management (CRM), human resource (HR) management to run a business.

    Definition of Cloud ERP – IS (Information Systems);

    Business Information System (BIS) is the system that contains the information of various sectors of the company like customer relationship management (CRM), Enterprise Resource Planning (ERP), Human Resource Management (HRM), Financial Management, integration, implementation, purchasing, marketing, sales, and inventory.

    Enterprise Resource Planning (ERP) is a module that helps in managing and giving solutions to run the company with different aspects like managing, planning, modifying, integrating, implementing, and marketing. The cloud-based ERP is nothing but the ability of the service providers and the end-users like Information Technology/Information Systems and clients to share the data among their business or the company.

    When the process of sharing and managing the information is successful the decision made to run a process will be accurate resulting in the profits of the company. While using the cloud-based ERP, the time taken for the upgrade of the system enhance and works effectively. The process speeds up when the company has an accurate and effective cloud ERP system which is an added advantage.

    Other Information;

    Meanwhile, when the decisions are made accurately within the time limit the productivity of the organization is enhanced and it leads to the growth of the company. The company gains profits as it has an effective system. Accordingly, as there is a growth in the business it leads to a competitive edge, which leads to competition with other companies.

    The organization’s productivity and competitiveness increase including the increase of knowledge on the new technologies and software with minimal human work. On the other hand, if the company has a bad system the time taken to upgrade the system is more and leads to an ineffective result. The ineffective result again leads to an inappropriate decision which drops the company’s productivity. As the productivity of the company is let down the company has no competitors and results in a loss. When poor integration occurs, it results in unsatisfactory results. As there is a loss in the company it impacts the Business Information System (BIS).

    A good Business Information System aims to integrate successful end-users like IT, People, and business which helps in making an accurate decision on time. The accurate and effective decision leads to good productivity of the organization. The organization benefits from the reduction of cost, profit maximization, and good decision support. The competitors of the against the organization increases which helps in enhancing knowledge on all the new technologies and software.

    Benefits of Cloud ERP system;

    Cloud ERP system has many benefits which include;

    • Cost Minimization
    • Scalability
    • Mobility
    • Usability
    • Efficiency
    • Cost Transparency
    • Accessibility
    • Disaster Recovery
    • Speed Enhancement of the system

    The predominant benefits of the cloud ERP systems are;

    • Scalability
    • Accessibility and Usability
    • Mobility
    • Security
    Scalability;

    The ability of the computing process in resource pooling and rapid resource elasticity of the cloud-based ERP system leads to a high elastic infrastructure capacity. The high-level strategic flexibility and enhanced competitiveness in the SME’s result in scalability. The enterprises can adjust according to the requirements, they can move their scale up or down flexibly.

    Accessibility and Usability;

    As the cloud ERP is on-demand and it works using the internet it has several options to access. Also, The applications over the cloud are in an open environment which leads to easy access. An increase in accessibility steps forward on an increase in usability which includes the usability of cloud ERP inside and outside of the enterprise.

    Mobility;

    According to (Peng & Gala, 2014), the enhanced ERP mobility took over the existing or the old system of working at the office. When the cloud came into place, the data or the whole information of the system is stored on the cloud and can view or access from any place through web browsers. For example, the manager used to work on the project in the office as there is no cloud ERP available. Later, when the cloud-based ERP discover and implement, the manager can work from anywhere just by using a secure web browser. This helped the end-users to enhance their knowledge by saving time.

    Security;

    The ERP consists of data of the system or the business, connecting the data to the cloud draws the main attention of security. The cloud ERP which holds the information of the complete system should be secure enough to rely upon. Since the data controller is by a third party (Cloud Service Provider), it is not to be relied on. Whereas, when there is an effective and enhanced system there is no problem with the security of the system as it is safe. But, if the system is ineffective then there is a loss of data or leakage of data.

    If the system has the disaster recovery option then it is easy for the data to obtain when lost. Security plays a major role in the Cloud ERP system. Data Privacy and Data Security seem to be similar but indeed they are different from each other. Data Privacy refers to the privacy of the company or the manager and the workers to access data. Whereas, data security relates to the protection of the data to avoid data loss or data leakage. More often, data leaks by humans, rather than technology defects.

    Cost Minimalization;

    A system always needed a high maintenance and implementation cost, especially in on-premises ERP systems. Generally, an on-premises ERP system requires investments in the user; as well as the client system as they should install the software and hardware for running the system. This leads to management, maintenance, implementation, and investments. Cloud ERP system has overcome all these problems as there is the requirement of installing the systems on user PC’s and the data can view, access, and stored on the cloud. This reduced the investments, maintenance which leads to cost minimalization or in short cost reduction. It also maximized the profits of the company with low maintenance and low cost.

    Similarly, the other benefits of cloud ERP are equally important for the development of the system. Cost transparency and enhancement of speed while upgrading the system leads to the enhancement of the perfection of the system. The system cannot run slow while upgrading as it leads to time loss; so, the system should upgrade fast enough to avoid any time gap. When the system upgrades the performance level increases as the system is more effective.

    Taxonomies Benefits of Cloud ERP system;

    The key benefits of cloud ERP systems in terms of ERP benefits Taxonomies according to Shang and Seddon are;

    • Operational
    • Managerial
    • Strategic
    • IT Infrastructural and
    • Organizational
    Operational;

    The predominant operational benefit is cost reduction or cost minimalization. Rather than traditional ERP, Cloud ERP has the subscription method of payments; which not only includes software cost but also the management and support cost. This is the key benefit of the Cloud ERP as the cost reduction; it also includes less workforce and helps to travel less. As the Cloud Service Provider (CSP) takes over the management of the system there is a drastic improvement in the profit maximization and functioning of the system.

    Managerial;

    Cloud ERP system helps in making an accurate decision that effectively works on the system. This leads to easy access to the system as the third party (Cloud Service Provider) provides a good ERP system. The managerial benefit of cloud ERP system gives a fast and accurate output which is time-saving with low cost. When the datastore is on a cloud every person inside the system can easily access and also can modify the data if they have access to the system.

    Strategic;

    The rapid development of the system is possible as the system is more effective and accurate; it allows the users to have a fast and reliable result which leads to the growth of the company. Using Cloud ERP system, the users can enhance their knowledge towards software and the structure; which drives through innovations and creativity. The competitive edge of the company increases and there will be the maximization of profits.

    IT Infrastructural;

    As mentioned above, a cloud ERP system helps to enhance knowledge on software as well as the modules of the system. The IT knowledge helps the end-user to develop the business with great IT infrastructure which will be easy to operate by the end-users.

    Organizational;

    The cloud ERP system helps to support the organization and with the changes in an organization because of its flexibility and scalability. Now a day, technology is enhancing and also new technologies are coming into the system, cloud ERP is flexible to adapt to the new technology. The end users can learn the strategies of business easily as the cloud ERP helps to share the information with no installing of software onto the end user’s system.

    These five taxonomies are in the perspective of a stakeholder and also senior manager which helps in the development of the company; which includes the enhancement of users’ knowledge towards software systems and the business strategies or the business rules. The end-users will have easy access to the system as the information is stored on the cloud with no prior installment of software.

    Best Cloud ERP System Solutions Essay for Small Business Image
    Best Cloud ERP System Solutions Essay for Small Business; Image by Mohamed Hassan from Pixabay.

    References; Cloud ERP Systems – Definitions and Impact. Retrieved from https://ukdiss.com/examples/cloud-erp-systems.php?vref=1

  • What does Artificial Intelligence (AI) mean? PPT with Components of Robot

    What does Artificial Intelligence (AI) mean? PPT with Components of Robot

    How does artificial intelligence work? Artificial intelligence is a branch of computer science that aims to create intelligent machines. What does AI or Artificial Intelligence mean? PPT with Components of Robot; It has become an essential part of the technology industry. Article of Artificial intelligence (AI) is the ability of a computer program or a machine to think and learn. The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

    Artificial Intelligence: Meaning, Definition, Components with PPT Example.

    AI or artificial intelligence a modern approach; As well as, refers to software technologies that make a robot or computer act and think like a human. Some software engineers say that it is only artificial intelligence if it performs as well or better than a human. In this context, when we talk about performance, we mean human computational accuracy, speed, and capacity.

    What is Artificial intelligence? It is a theory and development of computer systems that can perform tasks that normally require human intelligence. As well as, Speech recognition, decision-making, visual perception; for example, are features of human intelligence that AI may possess. Translation between languages is another feature.

    Meaning and Definition of Artificial Intelligence:

    An ideal (perfect) intelligent machine is a flexible agent that perceives its environment and takes actions to maximize its chance of success at some goal or objective. As machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition.

    For example, optical character recognition is no longer perceived as an exemplar of “artificial intelligence”: it is just a routine technology. At present we use the term AI for successfully understanding human speech, competing at a high level in strategic game systems, self-driving cars, and interpreting complex data. Some people also consider AI a danger to humanity if it continues to progress at its current pace.

    The following definition of AI:

    First, definition;

    “Artificial Intelligence, or AI, is the ability of a computer to act like a human being. It has several applications, including software simulations and robotics.”

    Second, definition;

    “However, artificial intelligence is most commonly used in video games, where the computer is made to act as another player.”

    AI, the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Also, the term frequently applies to the project of developing systems endowed with the intellectual processes characteristic of humans; such as the ability to reason, discover meaning, generalize, or learn from experience.

    One thing we know, John McCarthy came up with the name “Artificial Intelligence” in 1955. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can program to carry out very complex tasks; for example, discovering proofs for mathematical theorems or playing chess—with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity; there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge.

    On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks; so that AI in this limited sense finds in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.

    Here is the PPT slide explain What is Artificial Intelligence?

    What are the Components of the Robot?

    Robot: A machine resembling a human being and able to replicate certain human movements and functions automatically. Also, a robot is a machine designed to execute one or more tasks automatically with speed and precision.

    Some of the important components of Robot are as follows:

    • Manipulator.
    • Controller.
    • Sensors.
    • End-effector, and.
    • Locomotion Device.

    Now, explain;

    1] Manipulator:

    Just like the human arm, the robot consists of what call a manipulator having several joints and links.

    2] Controller:

    The digital computer (both the hardware and the software) acts as a controller to the robot. Also, the controller functions in a manner analogous to the human brain. With the help of this controller, the robot can carry out the assigned tasks. As well as, the controller directs and controls the movement of the Manipulator and the end-effector. In other words, the controller controls the robot.

    3] Sensors:

    Without the data supplied by the sense organs, the brain would be incapable of intelligence. In other words, the controller (the computer) of the robot cannot do any meaningful task, if the robot is not with a component analogous to the sense organs of the human body.

    Thus, the fifth and most important component of the robot is the set of sensors. Sensors are nothing but measuring instruments that measure quantities such as position, velocity, force, torque, proximity, temperature, etc.

    4] End-effector:

    The base of the manipulator is fixed to the base support and at its other free end, the End-effector attaches. As well as, the end-effector expects to perform tasks normally performed by the palm and finger arrangements of the human arm.

    5] Locomotion Device:

    In the case of Human Beings, the power for the movement of the arm, the palm, and fingers provide by muscles. For the robot, the power for the movement (locomotion) is provided by the motors. Also, the motors used for providing locomotion in robots are of three types depending on the source of energy: Electric, Hydraulic, or Pneumatic.

    What does Artificial Intelligence (AI) mean PPT with Components of Robot
    What does Artificial Intelligence (AI) mean? PPT with Components of Robot, #Pixabay.

    What is Knowledge? without knowledge, Artificial Intelligence maybe calls Zero.

    By Peter Drucker, The truly revolutionary impact of the Information Revolution is not artificial intelligence, information, or the effect of computers and data processing on decision-making, policymaking, or strategy. Also, the key to continued growth and leadership in the New Economy is not the electronics of computers but the cognitive skills of the “knowledge workers”.

    Knowledge may record in the individual brain or stored in the organizational process, products, facilities, systems, and documents. Knowledge is the capacity to act. It is the product of learning, related to human activity, and is more than just a piece of information.

    Knowledge assets are the knowledge regarding markets, products, technologies, and organizations, that a business owns or needs to own and which enable its business process to generate profits. What does Employees Stock Option mean? with Motivating Employees.

    Reference:
    1. britannica.com/technology/artificial-intelligence
    2. wikipedia.org/wiki/Artificial_intelligence
    3. marketbusinessnews.com/financial-glossary/artificial-intelligence/
    4. yourarticlelibrary.com/robots/robots-5-important-components-of-robots/5692
    5. slideshare.net/EdurekaIN/what-is-artificial-intelligence-artificial-intelligence-tutorial-for-beginners-edureka/13-Copyright_2017_edureka_andor_its
  • What do you think of Data Warehousing?

    What do you think of Data Warehousing?

    Companies using data warehousing and its effects, How many Types of Data Warehousing? What are the benefits of using data warehousing? The term data warehouse or data warehousing was first coined by Bill Inmon in the year 1990 which was defined as a “warehouse which is subject-oriented, integrated, time variant and non-volatile collection of data in support of management’s decision-making process”. When referring to data warehousing as subject-oriented, it simply means that the process is giving information about a particular subject rather than the details regarding the on-going operations of the company. It is a blend of technologies and components which allows the strategic use of data. You are read and studying to learn, What do you think of Data Warehousing? Download PDF.

    A data warehousing is a technique for collecting and managing data from varied sources to provide meaningful business insights. What do you think of Data Warehousing? Download PDF.

    It is electronic storage of a large amount of information by a business which is designed for query and analysis instead of transaction processing. It is a process of transforming data into information and making it available to users in a timely manner to make a difference. Moreover, when data warehousing was referred to as integrated it means that the data or information which are gathered from a number of sources are then all gathered to synthesize a coherent whole.

    On the other hand, data warehousing being time variant simply means that the data available were identified during a particular period. Lastly, data warehousing as being non-volatile means that the data is stable and when a new data is added to the system, the old data are never removed, instead they just remain there and this enables the organization to be able to give the management consistency in their business. In the existence of modern times with the advent of technological advancements inevitably affecting the businesses in major ways, there has also been a development and emergence of new measures, practices, and techniques which used technology to be able to provide an unwavering solution to the problems in the organization with regards to the level and kind of information that the organization needs to be able to survive and prosper amidst the increasing competition in the market.

    Undeniably, one of this techniques and practices refers to the emergence of data warehousing as a tool for helping today’s businesses to be able to manage competition and the turbulent economic condition. The birth f the concept of data warehousing can be contributed to various researches and studies which were conducted in the past to provide various organizations with the means of getting information in a manner which is efficient, effective, and flexible. The data warehousing which is known today among the corporate practice is not what it was when it started almost two decades ago. The practice of data warehousing nowadays is a result of the experiences and technologies in the last twenty years. Bill Inmon and Ralph Kimball are two of the heavyweights when it comes to data warehousing.

    However, although their names are known in this field, these two scholars have two varying views with regards to data warehousing. The paradigm which was illustrated by Inmon holds that the data warehouse forms only a part of the general business intelligence system. On the other hand, the paradigm of Kimball assumes that the data warehouse is a conglomerate of all the data in the organization.

    Other researchers assume that there is no right or wrong theories among the two assumptions from the two heavy weighs in data warehousing. However, most of them support the notion of Kimball’s paradigm. They believe that most data warehouses started only as efforts from various departments starting with what they call as data marts until they develop and evolve to become a data warehouse. Furthermore, data warehousing has been heralded as one of the sustainable solutions to management information and dilemma and such also provide the organization and environment which entails various benefits if they are practiced in the right way and if the perspectives are directed towards the right goal.

    The process of data warehousing is said to have the intention of providing an architectural model which can best provide an illustration of the flow data from the systems regarding the operation of the decision support environments. However, according to the same author, one problem stems down from the data warehousing technique – that is such a system is said to be too expensive to be affordable for some organizations or businesses.

    It is undeniable that data warehousing continues to attract interest, it is also undeniable that many projects are failing to deliver the expectations from what they are supposed to deliver and they still prove to be too high of accost to be handled by some businesses. However, to be able to justify this relatively high cost, it has been said that organizations should look at the long-term benefit of the warehouse rather than simply looking at the short-term benefits that such an offer. Moreover, data warehousing is also said to be designed to be able to support ad-hoc data analysis, inquiry and reporting by end-users, without programmers, interactively and online.

    There are some key factors which can make the data warehousing practice a success among different organizations. One of the key ingredients to the success of the practice is to make the management, especially the higher management, aware and conscious of all the benefits which this tool entails and what can data warehousing do to improve the performance of the business.

    Another key to the success of data warehousing is choosing the right people to make it happen. By choosing the right people, the contribution of individual minds should be recognized to form a synthesis and a greater whole. Training strategy, the right structure or architecture, a sustainable mission statement, showing early benefits, ensuring scalability, understanding how important is the quality of data and using only proven and effective methodology are some of the other key ingredients to make data warehousing a successful practice, Data Warehousing file Download in PDF.

    Why needs Data warehousing?

    The data warehousing is needed for all types of these users like:

    • If the user wants fast performance on a huge amount of data which is a necessity for reports, grids or charts, then Data warehouse proves useful.
    • Decision makers who rely on the mass amount of data.
    • It is also used by the people who want simple technology to access the data.
    • It also essential for those people who want a systematic approach to making decisions.
    • The data warehouse is a first step If you want to discover ‘hidden patterns’ of data-flows and groupings.
    • Users who use customized, complex processes to obtain information from multiple data sources.

    The Companies using data warehousing and its effects.

    An example of a known company which uses data warehousing is WalMart. Being the world’s largest retailer, many say that the company should be also the organization with the largest data warehouse which is going to serve as the database of its inventory and all transactions related to their business performance. The data warehousing also has a big implication on the business of WalMart.

    According to the management of the world’s largest retailer, more than any other purpose, their data warehouse is helping them to be able to make decision support systems between the company and its various suppliers. Aside from that, another implication of data warehousing on WalMart is that it enables the suppliers to be able to access a large amount of online information and data which will be helpful with their suppliers in terms of improving their operations.

    One example of companies using and reaping the benefits of adapt warehousing will be various pharmaceutical companies, or on a larger scale, the general healthcare industry. For most of the pharmaceutical businesses which are under operation, they were able to acknowledge the fact that they lack a sustainable focus on their promotional practices, resulting in diffused sales efforts. With that, they regard that data warehousing technique has a big implication in their business because they regard such as the best medicine and remedy for the aforementioned problem.

    They are even using data warehousing to be able to attain a sustainable competitive edge against other businesses in the industry. In the case of pharmaceutical companies, it has an implication also in the marketing department. Data warehousing helps the marketing department, through various information contained, to come up with promotional and marketing activities which can yield the maximum results. Moreover, data warehousing also has an implication on the human resources department of the organizations because they can also help in the effective allocation of people and resources.

    How many Types of Data Warehousing?

    There are three main types of Data Warehousing are:

    • Enterprise Data Warehousing: Enterprise Data Warehouse is a centralized warehouse. It provides decision support service across the enterprise. It offers a unified approach to organizing and representing data. It also provides the ability to classify data according to the subject and give access according to those divisions.
    • Operational Data Store: Operational Data Store, which is also called ODS, are nothing but data store required when neither Data warehouse nor OLTP systems support organizations reporting needs. In ODS, Data warehouse is refreshed in real time. Hence, it is widely preferred for routine activities like storing records of the Employees.
    • Data Mart: A data mart is a subset of the data warehouse. It specially designed for a particular line of business, such as sales, finance, sales or finance. In an independent data mart, data can collect directly from sources.

    What are the benefits of using data warehousing?

    Some of the benefits of data warehousing that it offers include the fact that it has a relative orientation on the subject area, it has the ability to provide an integration of data which were retrieved from diverse and multiple sources, it allows data analysis from time to time, it adds ad hoc inquiry and reporting, it provides decision makers with the capabilities to analyze, it relieves the IT from information development.

    It has the ability to provide better performance for complex analytical queries, it relieves the burden of processing databases which are based on transactions, it allows a planning process that is perpetual and continuous, and lastly, it converts corporate data to make them strategic information which can help them in planning for a better performance of the organization.

    Another benefit of data warehousing is that it enables and it helps different organizations in the strategic decision making resulting into the formulation of strategic decisions which are geared towards enabling a better business performance and yielding better results.

    It can be assumed that most data warehousing practices are not intended for strategic decision making because they are normally used for post-monitoring of decisions regarding how effective they are. Nonetheless, it should not be also disregarded that data warehousing, can also be sued for strategic decision making and can be used profitably.

    Another benefit of data warehousing is that it enables the user to have unlimited access to a relatively very large amount of enterprise information which can be used to potentially solve a large number of enterprise problems which can even be used to increase the profitability of the company. A very well-designed data warehouse can yield a greater return-on-investment with unlimited benefits had the ability to better assess the risks associated with the organization. Fully read on PDF file and download.

    What do you think of Data Warehousing - ilearnlot
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