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Lecture 07 - Executive Information Systems and the Data Warehouse

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Building the Data WareHouse

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Lecture 07 - Executive Information Systems and the Data Warehouse

  1. 1. Chapter 7: Executive Information Systems and the Data Warehouse http://it-slideshares.blogspot.com/
  2. 2. Agenda1. Introduction2. EIS – The Promise3. A Simple Example4. Drill-Down Analysis5. Supporting the Drill-Down Process6. The Data Warehouse as a Basic for EIS7. Where to Turn8. Event Mapping9. Detailed Data and EIS10. Keeping Only Summary Data in the EIS11. Summary http://it-slideshares.blogspot.com/
  3. 3. 7.1 Introduction Prior to data warehousing, there were Executive Information Systems (EIS). EIS was a notion that computation should be available to everyone in the corporation, not just the clerical community doing day-to-day transactions. EIS presented the executive with a set of appealing screens. The entire idea behind EIS was presentation of information with no real understanding of the infrastructure needed to create that information in the first place. EIS has reappeared in many forms today—such as OLAP processing and DSS applications like customer relationship management (CRM).
  4. 4. 7.2 EIS — The Promise EIS is one of the most potent forms of computing. EIS processing is designed to help the executive make decisions.  EIS becomes the executive’s window into the corporation. Some of the typical uses of EIS are these :  Trend analysis and detection  Key ratio indicator measurement and tracking  Drill-down analysis  Problem monitoring  Competitive analysis  Key performance indicator monitoring http://it-slideshares.blogspot.com/
  5. 5. 7.3 A Simple Example
  6. 6. 7.3 A Simple Example (Con’t)
  7. 7. 7.3 A Simple Example (Con’t)The few approachs thatthe manager can use EISeffectively :  Trend analysis and comparison  To do slicing and dicing Figure 7-3 shows a comparison that might be found in an EIS analysis.
  8. 8. 7.4 Drill-Down Analysis Drilling down refers to the ability to start at a summary number and to break that summary into a successively finer set of summarizations.
  9. 9. 7.4 Drill-Down Analysis (Con’t) Another important aspect of EIS is the ability to track key performance indicators. Although each corporation has its own set, typical key performance indicators might be the following:  Cash on hand  Customer pipeline  Length of sales cycle  Collection time  New product channel  Competitive products
  10. 10. 7.4 Drill-Down Analysis (Con’t) The difficult part of EIS is not in the graphical presentation, but in discovering and preparing the numbers – accurately, completely, and integrated— that go into the graphics, as shown in Figure 7-5.
  11. 11. 7.5 Supporting the Drill-Down Process Creatingthe basis of data on which to perform drill- down analysis, then, is the major obstacle to successfully implementing the drill-down process, as shown in Figure 7-6.
  12. 12. 7.5 Supporting the Drill-DownProcess (Con’t)
  13. 13. 7.6 The Data WareHouse as a Basic for EIS It is in the EIS environment that the data warehouse operates in its most effective state. With a data warehouse, the EIS analyst does not have to worry about the following:  Searching for the definitive source of data  Creating special extract programs from existing systems  Dealing with unintegrated data  Compiling and linking detailed and summary data and the linkage between the two  Finding an appropriate time basis of data (finding historical data)  Management constantly changing its mind about what needs to be looked at next
  14. 14. 7.6 The Data WareHouse as a Basic for EIS (con’t)
  15. 15. 7.7 Where to Turn TheEIS analyst can turn to various places in the architecture to get data.
  16. 16. 7.7 Where to Turn (Con’t) There is a very good reason for the order shown, as indicated in Figure 7-10.
  17. 17. 7.7 Where to Turn (Con’t) Theways that EIS is supported by the data warehouse are illustrated in Figure 7-11.
  18. 18. 7.7 Where to Turn (Con’t)The EIS function uses the following :  The data warehouse for a readily available supply of summary data.  The structure of the data warehouse to support the drill- down process.  Data warehouse metadata for the DSS analyst to plan how the EIS system is built.  The historical content of the data warehouse to support the trend analysis that management wishes to see.  The integrated data found throughout the data warehouse to look at data across the corporation
  19. 19. 7.8 Event Mapping A useful technique in using the data warehouse for EIS processing is event mapping. The simplest way to depict event mapping is to start with a simple trend line.
  20. 20. 7.8 Event Mapping (con’t)Figure 7-12 shows that corporate revenues have varied by month, as expected.
  21. 21. 7.8 Event Mapping (con’t)
  22. 22. 7.8 Event Mapping (con’t) Misleading conclusions can be drawn, though, by looking at correlative information. It often helps to look at more than one set of trends that relate to the events at hand.
  23. 23. 7.9 Detailed Data and EIS The following question must be answer :  How much detailed data do you need to run your EIS/DSS environment?  What, then, is so wrong with keeping all the detail in the world around when you are building an EIS/DSS environment? Summary data is an integral part of the EIS/DDS environment.
  24. 24. 7.10 Keeping Only Summary Data in the EIS Some very real problems become evident with keeping just summary data.  First, summary data implies a process  It may or may not be at the appropriate level of granularity for the analytical purpose at hand.
  25. 25. 7.11 Summary There is a very strong affinity between the needs of the EIS analyst and the data warehouse. The data warehouse explicitly supports all of the EIS analyst’s needs. With a data warehouse in place, the EIS analyst can be in a proactive rather than a reactive position. The data warehouse enables the EIS analyst to deal with the following management needs:  Accessing information quickly  Changing their minds (that is, flexibility)  Looking at integrated data  Analyzing data over a spectrum of time  Drilling down The data warehouse provides an infrastructure on which the EIS analyst can build. http://it-slideshares.blogspot.com/

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