The Data Warehouse
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Understanding Data Warehouses & Decision Support Systems: Concepts, Components, & Implemen, Slides of Introduction to Database Management Systems
An in-depth exploration of data warehouses and decision support systems (dss). Learn about the differences between operational and dss data, the concept and construction of star schemas, and the implementation steps of a data warehouse. Discover the role of data mining in decision support and how it adds value to organizations. Understand the main components of a dss and how they transform operational data into decision support data.
Typology: Slides
2012/2013
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The Data Warehouse
In this chapter, you will learn:
- How operational data and decision support
data differ
- What a data warehouse is and how data for it
are prepared
- What star schemas are and how they are
constructed
- What steps are required to successfully
implement a data warehouse
- What data mining is and what role it plays in
decision support
Solving Business Problems and Adding
Value with Data Warehouse-Based
Solutions
Solving Business Problems and Adding
Value with Data Warehouse-Based
Solutions (continued)
Decision Support Systems
(continued)
- Composed of four main components:
- Data store component
- Basically a DSS database
- Data extraction and filtering component
- Used to extract and validate data taken from operational database and external data sources
- End-user query tool
- Used to create queries that access database
- End-user presentation tool
- Used to organize and present data
- Data store component
Main Components of a
Decision Support System
(DSS)
Contrasting Operational and
DSS Data Characteristics
Ten-Year Sales History for
a Single Department, in
Millions of Dollars
The Data Warehouse
- Integrated, subject-oriented, time-variant,
nonvolatile database that provides support for
decision making
A Comparison of Data Warehouse
and Operational Database
Characteristics
DSS Architectural Styles
Online Analytical Processing
- Advanced data analysis environment that
supports decision making, business
modeling, and operations research
- OLAP systems share four main
characteristics:
- Use multidimensional data analysis techniques
- Provide advanced database support
- Provide easy-to-use end-user interfaces
- Support client/server architecture