3.17: End of Chapter Resources
- Page ID
- 38238
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- 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
- Distinguish between data, information, and knowledge.
- Clarify how the data component is interconnected with the hardware and software components in information systems.
- Differentiate between a spreadsheet and a database by identifying three key distinctions.
- Enumerate three advantages of utilizing a data warehouse.