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Acct 6910 Building Business Intelligence Systems An Introduction to Data Warehouse.

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Presentation on theme: "Acct 6910 Building Business Intelligence Systems An Introduction to Data Warehouse."— Presentation transcript:

1 Acct 6910 Building Business Intelligence Systems An Introduction to Data Warehouse

2 2 Agenda Why Data Warehouse What is Data Warehouse Current practice of data warehouse

3 3 Why Data Warehouse Why Database??

4 4 Why Data Warehouse Problems with current database practices: Problem 1: Isolated databases distributed in an enterprise SalesCRM Inventory Sub-problems: Data Inconsistency No comprehensive view of enterprise’s data sources – information island

5 5 Why Data Warehouse Problem 1: Isolated databases distributed in an enterprise SalesCRM Inventory Sub-problems: Data Inconsistency Performance

6 6 Why Data Warehouse Problem 2: Historical data is archived in offline storage systems Sales Sub-problems: Historical data is always needed to support business decisions Archive Historical Sales Data

7 7 Why Data Warehouse

8 8 A marketing manager wants to know sales amount distribution by product category and customer state in July? Query???

9 9 Why Data Warehouse Problem 3: Database is designed to process transactions but not to answer decision support queries Complex queries Bad query performance

10 10 What is Data Warehouse Data Warehouse is designed to solve problems associated with current database practices: Problem 1: Isolated databases distributed in an enterprise SalesCRM Inventory Extract, Integrate and Replicate Data Warehouse

11 11 Why Data Warehouse Problem 2: Historical data is archived in offline storage systems Sales Archive Historical Sales Data Data Warehouse Integrate Historical Data with Current Data

12 12 What is Data Warehouse Problem 3: Database is designed to process transactions but not to answer decision support queries Solution: In data warehouse, organize data in subject –oriented way rather than process-oriented way – dimensional modeling.

13 13 What is Data Warehouse ER Modeling Dimensional Modeling

14 14 What is Data Warehouse Data Warehouse is a subject-oriented, integrated, time-variant, non-volatile collection of data in support of management’s decision making process. 1. Subject-oriented means the data warehouse focuses on the high- level entities of business such as sales, products, and customers. This is in contrast to database systems, which deals with processes such as placing an order.

15 15 What is Data Warehouse  2. Integrated means the data is integrated from distributed data sources and historical data sources and stored in a consistent format. 3. Time-variant means the data associates with a point in time (i.e., semester, fiscal year and pay period) 4. Non-volatile means the data doesn’t change once it gets into the warehouse.

16 16 What is Data Warehouse

17 17 Current Practice of DW * Expected DW market value is 2002 will grow to $113.5 billion. Average DW development cost is $1.5 million and average maintenance cost is $0.5 million. * Source: H.J. Watson, “ Current Practicing in Data Warehousing”, I.S. Management, 2001

18 18 Current Practice of DW * Sponsorship for the DW project SponsorPercentage VP of a business unit39.8 CIO26.9 Business unit manager16.7 CEO11.1 Other25.0 * Source: H.J. Watson, “ Current Practicing in Data Warehousing”, I.S. Management, 2001

19 19 Current Practice of DW * DW Benefits Less effort to produce better information Better decisions Improvement of business processes Supporting for accomplishments of strategic business objectives * Source: H.J. Watson, “ Current Practicing in Data Warehousing”, I.S. Management, 2001

20 20 Reading: “ The Data Warehouse Toolkit” – Chapter 1


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