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Chapter
5
Business Intelligence: Data Warehousing, Data Acquisition,
Data Mining, Business Analytics, and Visualization
L EARNING O BJECTIVES
❖ Describe issues in data collection, problems, and quality.
❖ Describe the characteristics anization of database management systems.
❖ Explain the importance and use of a data warehouse and data mart.
❖ Describe business intelligence/business analytics and their importance anizations.
❖ Describe how online analytical processing (OLAP), data mining, data visualization, multidi-
mensionality, and real-time analytics can improve decision-making.
❖ Explain how the Web impacts database technologies and methods, and vice versa.
❖ Describe how database technologies and methods as part of business intelligence/business
analytics improve decision-making.
❖ Describe Web intelligence/Web analytics and their importance anizations.
anizations have amassed vast amounts of data that employees use to unlock
valuable secrets to enable pete essfully. anizations
do this extremely well, but others are quite use analytic tools to improve
organizational decision-making, a foundational data architecture and enterprise archi-
tecture must be in place to facilitate effective decision analysis. Enabling decision
analysis through access to all relevant information is known as business intelligence.
Business intelligence includes data warehousing, online analytical processing, data
mining, and visualization and multidimensionality. The outline of this chapter is as
follows:
Opening te: Information Sharing a ponent of the
National Strategy for Homeland Security,
The Nature and Sources of Data
Data Collection, Problems, and Quality
The Web/ mercial Database Services
Database Management Systems in Decision-Support Systems/Business
Intelligence
anization and Structures
Data Warehousing
Data Marts
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