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3.17: End of Chapter Resources

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    End Of Chapter Summary

    • Distinguishing data, information, and knowledge within computer information systems.
    • Highlights the significance of database technology in efficient data resource management.
    • Discusses the process of creating databases and the role of Database Management Systems (DBMS).
    • Addresses challenges such as redundancy and integrity violations, emphasizing the role of database technology in resolving these issues.
    • Explores complexities associated with big data and ongoing efforts to manage and analyze massive datasets.
    • Covers topics such as data types, DBMS, and Structured Query Language (SQL) in the context of database management.
    • Examines various database models and addresses challenges in large-scale distributed systems.
    • Explores applications in business intelligence, data visualization, and data warehouses.
    • Equipes readers with a holistic understanding of fundamental concepts, practical applications, and emerging trends in data and database management within information systems.

    Key Terms

    Big data: extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

    Competitive advantage: a condition or circumstance that puts a company in a favorable or superior business position.

    Data integrity: the accuracy, completeness, and quality of data as it’s maintained over time and across formats.

    Data mining: the practice of analyzing large databases to generate new information.

    Data redundancy: when multiple copies of the same information are stored in more than one place at a time.

    Data resource management: known as data administration, deals with computer science and information systems.

    Data visualization: is the graphical representation of information and data.

    Data warehouses: a large store of data accumulated from a wide range of sources within a company and used to guide in management decisions.

    Data: the raw facts and devoid of context or intent data can be quantitative or qualitative.

    Database Management System (DBMS): Stores and retrieves the data that an application creates and uses. Although the DBMS is itself considered an application, it’s often useful to think of a firm’s database systems as sitting above the operating system, but under the enterprise applications.

    Database technology: takes information and store, organize, and process it in a way that enables users to go back easily and intuitively and find details they are searching for.

    Database: a structured set of data held in a computer, especially one that is accessible in various ways.

    Enterprise database: must be able to keep track of all operations on the database that are applied by a certain user during each log-in session.

    Information: is processed data that possess context, relevance, and purpose.

    Knowledge management: efficient handling of information and resources within a commercial organization.

    Knowledge: is human beliefs or perceptions about relationships among facts or concepts relevant to that area.

    Meta base: an open-source tool that allows for powerful data instrumentation, visualization, and querying.

    Normalization: is the process of organizing data in a database.

    Open Source: Software that can be freely used, changed, and shared (in modified or unmodified form) by anyone.

    Qualitative data: is descriptive.

    Quantitative data: is a numeric, the result of a measurement, count, or other mathematical calculation.

    Query-by-example (QBE): a database query language for relationship databases.

    Relational data model: the logical data structures – the data tables, views, and indexes – are separate from the physical storage structures.

    Structured query language: a programming language for storing and processing information in a relational database.

    End Of Chapter Discussions

    1. Distinguish between data, information, and knowledge.
    2. Clarify how the data component is interconnected with the hardware and software components in information systems.
    3. Differentiate between a spreadsheet and a database by identifying three key distinctions.
    4. Enumerate three advantages of utilizing a data warehouse.

    3.17: End of Chapter Resources is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

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