CHAPTER 2: DATA WAREHOUSING Objectives: After completing this chapter, you should be able to: 1. Understand the basic deﬁnitions and concepts of data warehouses 2. Understand data warehousing architectures 3. Describe the processes used in developing and managing data warehouses 4. Explain data warehousing operations 5. Explain the role of data warehouses in decision support 6. Explain data integration and the extraction, transformation, and load (ETL) processes 7. Describe real-time (active) data warehousing 8. Understand data warehouse administration and security issues CHAPTER OVERVIEW Data warehousing is at the foundation of most BI. This is the data warehousing chapter of the book. Later chapters will use it as they discuss DW applications such as business analytics and data mining. I. OPENING VIGNETTE: DIRECTV THRIVES WITH ACTIVE DATA WAREHOUSING, PAGE 30
Problem? The company’s IT system could not handle the high data volume from customer calls along with the rapidly changing market conditions. Solution? Developed a real-time, integrated active DW solution from Teradata and GoldenGate. Results? Huge business beneﬁts such as reduced churn rate and better managed call centers with real-time data for decision making.
What can we learn from this vignette? 1. It illustrates the strategic value of implementing an active DW, along with its supporting BI methods. 2. The key lesson here is that a real-time, enterprise-level active DW combined with a strategy for its use in decision support can result in signiﬁcant beneﬁts (ﬁnancial and otherwise) for an organization. Answer Questions for the Opening Vignette 1-5 on page 31. 1. 2. 3. Why is it important for DirecTV to have an active data warehouse? What were the challenges DirecTV faced on its way to having an integrated active data warehouse? Identify the major differences between a traditional data warehouse and an active data warehouse, such as the one implemented at DirecTV. What strategic advantage can DirecTV derive from the real-time system as opposed to a traditional information system? Why do you think large organizations like DirecTV cannot afford not to have a capable data warehouse? E. Other Case Studies to watch: Premier Bank Card & Enterprise Rental 1. Premier Bank Card (3:46)
Business Intelligence Customer Case Study: Premier Bank Card, http://www.youtube.com/watch?v=ritRCFcyaLw
Watch this customer case study to learn how Premier Bank Card uses Microsoft Business Intelligence. BI is critical to this company to manage and analyze massive amounts of data. Premier Bankcard is a credit card company and helps people rehabilitate their credit. Today PREMIER Bankcard is the 9th largest issuer of VISA® and MasterCard® credit cards in the country serving millions of customers nationwide. http:// www.ﬁrstpremier.com/about/premier-bankcard/ Problem: The old system: 1. Did not keep up with the user demand. 2. Consisted of Access and Excel 3. Manual process of analyses and trending 4. Time was long 5. Error rate was high 6. Low accuracy Solution: Microsoft Business Intelligence – an end-to-end solution. 1. BI is critical to this company because they are focused on data and analysis of data. 2. The users now have instant response and they can pull data down out of the cubes and data warehouse. 3. Everybody in the company was accustomed to Excel and this is a common user interface.
4. The BI solution gives them one version of the truth, delivering the right information to the right people. Microsoft Business Intelligence Products picture "Hamburger Slide"
The Microsoft BI stack consists of: 1. Microsoft SQL Server 2005 where all the data resides. 2. Microsoft Analysis Services and Reporting Services From SQL Server, they push out the data to Microsoft Analysis Services and Reporting Services. 3. Data warehouse - has 12 terabytes of information. Every day the BI system organizes and imports about 20-30 gigabytes of data. 4. SharePoint, Performance...
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