02010_ch13

02010_ch13 - Database Systems: Design, Implementation, and...

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Database Systems: Design, Implementation, and Management Eighth Edition Chapter 13 Business Intelligence and Data Warehouses
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th 2 Objectives In this chapter, you will learn: How business intelligence is a comprehensive framework to support business decision making How operational data and decision support data differ What a data warehouse is, how to prepare data for one, and how to implement one What star schemas are and how they are constructed
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th 3 Objectives (continued): In this chapter, you will learn: (continued) What data mining is and what role it plays in decision support About online analytical processing (OLAP) How SQL extensions are used to support OLAP- type data manipulations
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th 4 The Need for Data Analysis Managers track daily transactions to evaluate how the business is performing Strategies should be developed to meet organizational goals using operational databases Data analysis provides information about short- term tactical evaluations and strategies
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th 5 Business Intelligence Comprehensive, cohesive, integrated tools and processes Capture, collect, integrate, store, and analyze data Generate information to support business decision making Framework that allows a business to transform: Data into information Information into knowledge Knowledge into wisdom
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th 6 Business Intelligence Architecture Composed of data, people, processes, technology, and management of components Focuses on strategic and tactical use of information Key performance indicators ( KPI ) Measurements that assess company’s effectiveness or success in reaching goals Multiple tools from different vendors can be integrated into a single BI framework
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th 7
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th 8 Decision Support Data Operational data Mostly stored in relational database Optimized to support transactions representing daily operations Decision support data differs from operational data in three main areas: Time span Granularity Dimensionality
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th 9
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th 10 Decision Support Database Requirements Specialized DBMS tailored to provide fast answers to complex queries Four main requirements: Database schema Data extraction and loading End-user analytical interface Database size
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th 11 Decision Support Database Requirements (continued) Database schema Complex data representations Aggregated and summarized data Queries extract multidimensional time slices Data extraction and filtering Supports different data sources Flat files Hierarchical, network, and relational databases Multiple vendors Checking for inconsistent data
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th 12 Decision Support Database Requirements (continued) End-user analytical interface One of most critical DSS DBMS components Permits user to navigate through data to simplify and accelerate decision-making process Database size In 2005, Wal-Mart had 260 terabytes of data in its data warehouses DBMS must support very large databases ( VLDBs )
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02010_ch13 - Database Systems: Design, Implementation, and...

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