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McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved Chapter 8 Chapter 8 Accessing Accessing Organizational Organizational Information – Data Information – Data Warehouse Warehouse

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  • 1. Chapter 8Accessing Organizational Information Data WarehouseMcGraw-Hill/Irwin 2008 The McGraw-Hill Companies, All Rights Reserved

2. Learning Outcomes8.1 Describe the roles and purposes of datawarehouses and data marts in anorganization8.2 Compare the multidimensional nature ofdata warehouses (and data marts) withthe two-dimensional nature of databases8-2 3. Learning Outcomes8.3 Identify the importance of ensuring thecleanliness of information throughout anorganization8.4 Explain the relationship betweenbusiness intelligence and a datawarehouse 8-3 4. History of Data Warehousing Data warehouses extend the transformation ofdata into information In the 1990s executives became lessconcerned with the day-to-day businessoperations and more concerned with overallbusiness functions The data warehouse provided the ability tosupport decision making without disrupting theday-to-day operations 8-4 5. Data Warehouse Fundamentals Data warehouse a logical collection of information gathered from many different operational databases that supports business analysis activities and decision-making tasks The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes 8-5 6. Data Warehouse Fundamentals Extraction, transformation, and loading (ETL) a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse Data mart contains a subset of data warehouse information8-6 7. Data Warehouse Fundamentals8-7 8. Multidimensional Analysis and Data Mining Databases contain information in a seriesof two-dimensional tables In a data warehouse and data mart,information is multidimensional, itcontains layers of columns and rows Dimension a particular attribute ofinformation8-8 9. Multidimensional Analysis and Data Mining Cube common term for therepresentation of multidimensionalinformation 8-9 10. Multidimensional Analysis and Data Mining Data mining the process of analyzing data toextract information not offered by the raw dataalone To perform data mining users need data-miningtools Data-mining tool uses a variety of techniques tofind patterns and relationships in large volumes ofinformation and infers rules that predict futurebehavior and guide decision making8-10 11. Information Cleansing or Scrubbing An organization must maintain high-quality data in the data warehouse Information cleansing or scrubbing aprocess that weeds out and fixes ordiscards inconsistent, incorrect, orincomplete information8-11 12. Information Cleansing or Scrubbing Contact information in an operational system 8-12 13. Information Cleansing or Scrubbing Standardizing Customer name from Operational Systems 8-13 14. Information Cleansing or Scrubbing Information cleansing activities 8-14 15. Information Cleansing or Scrubbing Accurate and complete information8-15 16. Business Intelligence Business intelligence information thatpeople use to support their decision-making efforts Principle BI enablers include: Technology People Culture 8-16 17. OPENING CASE STUDY QUESTIONSIt Takes A Village to Write an Encyclopedia1. Determine how Wikipedia could use a data warehouse to improve its business operations2. Explain why Wikipedia must cleanse or scrub the information in its data warehouse3. Explain how a company could use information from Wikipedia to gain business intelligence8-17 18. CHAPTER EIGHT CASE Mining the Data Warehouse According to a Merrill Lynch survey in2006, business intelligence software anddata-mining tools were at the top of thetechnology spending list of CIOs Ben & Jerrys, California Pizza Kitchen,and Noodles & Company are usingbusiness intelligence and data mining innew and exciting ways 8-18 19. Chapter Eight Case Questions 1. Explain how Ben & Jerrys is usingbusiness intelligence tools to remainsuccessful and competitive in asaturated market 2. Identify why information cleansing andscrubbing is critical to California PizzaKitchens business intelligence toolssuccess8-19 20. Chapter Eight Case Questions 3. Illustrate why 100 percent accurate andcomplete information is impossible forNoodles & Company to obtain 4. Describe how each of the companies above isusing BI from their data warehouse to gain acompetitive advantage8-20 21. BUSINESS DRIVEN TECHNOLOGYUNIT TWO CLOSINGMcGraw-Hill/Irwin 2008 The McGraw-Hill Companies, All Rights Reserved 22. UNIT CLOSING CASE ONEHarrahs Gambling Big on Technology1. Identify the effects poor information might have on Harrahs service-oriented business strategy2. Summarize how Harrahs uses database technologies to implement its service-oriented strategy3. Harrahs was one of the first casino companies to find value in offering rewards to customers who visit multiple Harrahs locations. Describe the effects on the company if it did not build any integrations among the databases located at each of its casinos 8-22 23. UNIT CLOSING CASE ONEHarrahs Gambling Big on Technology 4. Estimate the potential impact to Harrahsbusiness if there is a security breach in itscustomer information 5. Explain the business effects if Harrahs fails touse data-mining tools to gather businessintelligence 6. Identify three different types of data martsHarrahs might want to build to help it analyzeits operational performance 8-23 24. UNIT CLOSING CASE ONEHarrahs Gambling Big on Technology 7. Predict what might occur if Harrahs fails to clean orscrub its information before loading it into its datawarehouse 8. How could Harrahs use data mining to increaserevenue? 8-24 25. UNIT CLOSING CASE TWOSearching for Revenue - Google1. Determine if Googles search results are examples of transactional information or analytical information2. Describe the ramifications on Googles business if the search information it presented to its customers was of low quality3. Explain how the Web site solved its problem of poor information8-25 26. UNIT CLOSING CASE TWO Searching for Revenue - Google4. Identify the different types of entity classes that might be stored in Googles indexing database5. Identify how Google could use a data warehouse to improve its business6. Explain why Google would need to scrub and cleanse the information in its data warehouse7. Identify a data mart that Googles marketing and sales department might use to track and analyze its AdWords revenue8-26