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Decision Support And Business Intelligence Systems 9th Edition Dursun Delen Efraim Turban, Ramesh Sharda - Solutions
3. Contact some data warehouse vendors and obtain information about their products. Give special attention to vendors that provide tools for multiple purposes, such as Cognos, Software A&G, SAS Institute, and Oracle. Free online demos are available from some of these vendors.Download a demo or two
2. Survey some ETL tools and vendors. Start with fairisaac.com and egain.com. Also with dmreview.com.
1. Search the Internet to find information about data warehousing.Identify some newsgroups that have an interest in this concept. Explore ABI/INFORM in your library, e-library, and Google for recent articles on the topic.Begin with tdwi.com, technologyevaluation.com, and the major vendors:
6. Read the article K. Liddell Avery and Hugh J. Watson,“Training Data Warehouse End-users,” Business Intelligence Journal, Vol. 9, No. 4, Fall 2004, pp. 40–51 (which is available at teradatastudentnetwork.com). Consider the different classes of end users, describe their difficulties, and
5. Access teradata.com and read the white papers“Measuring Data Warehouse ROI” and “Realizing ROI:Projecting and Harvesting the Business Value of an Enterprise Data Warehouse.” Also, watch the Web-based course “The ROI Factor: How Leading Practitioners Deal with the Tough Issue of
4. Go through the list of data warehousing risks described in this chapter and find two examples of each in practice.
3. Interview administrators in your college or executives in your organization to determine how data warehousing could assist them in their work. Write up a proposal describing your findings. Include cost estimates and benefits in your report.
2. Jeet Kumar is the administrator of data warehousing at a big regional bank. He was appointed 5 years ago to implement a data warehouse to support the bank’s CRM business strategy. Using the data warehouse, the bank has been successful in integrating customer information, understanding customer
1. Kathryn Avery has been a DBA with a nationwide retail chain (Big Chain) for the past 6 years. She has recently been asked to lead the development of Big Chain’s first data warehouse. The project has the sponsorship of senior management and the CIO. The rationale for developing the data
11. Access teradatastudentnetwork.com. Identify the latest articles, research reports, and cases on data warehousing. Describe recent developments in the field.Include in your report how data warehousing is used in BI and DSS.
10. Consider the future of data warehousing. Perform a Web search on this topic. Also, read these two articles: L.Agosta, “Data Warehousing in a Flat World: Trends for 2006,” DM Direct Newsletter, March 31, 2006; and J. G.Geiger, “CIFe: Evolving with the Times,” DM Review, November 2005,
9. At teradatastudentnetwork.com, watch the Web seminars “Data Integration Renaissance: New Drivers and Emerging Approaches,” “In Search of a Single Version of the Truth: Strategies for Consolidating Analytic Silos,” and “Data Integration: Using ETL, EAI, and EII Tools to Create an
8. At teradatastudentnetwork.com, watch the Web seminars titled “Real-Time Data Warehousing: The Next Generation of Decision Support Data Management”and “Building the Real-Time Enterprise.” Read the article “Teradata’s Real-Time Enterprise Reference Architecture: A Blueprint for the
7. At teradatastudentnetwork.com, read and answer the questions with the assignment “Ad-Vent Technology:Using the MicroStrategy Sales Analytic Model.” The MicroStrategy software is accessible from the TUN site.Also, you might want to use Barbara Wixom’s PowerPoint presentation about the
6. At teradatastudentnetwork.com, read and answer the questions of the assignment “Data Warehousing Failures.”Because eight cases are described in that assignment, the class may be divided into eight groups, with one case assigned per group. In addition, read Ariyachandra and Watson (2006a),
5. At teradatastudentnetwork.com, read and answer the questions to the case “Harrah’s High Payoff from Customer Information.” Relate Harrah’s results to how airlines and other casinos use their customer data.
4. Read the full Continental Airlines case (summarized in the end-of-chapter case) at teradatastudentnetwork.com and answer the questions.
3. Explain when you should implement a two- or three-tiered architecture when considering developing a data warehouse.
2. Read the Ball (2005) article and rank-order the criteria(ideally for a real organization). In a report, explain how important each criterion is and why.
1. Consider the case describing the development and application of a data warehouse for Coca-Cola Japan (a summary appears in Application Case 8.4), available at the DSS Resources Web site, dssresources.com/cases/cocacolajapan/index.html. Read the case and answer the nine questions for further
9. Investigate current data warehouse development implementation through offshoring. Write a report about it. In class, debate the issue in terms of the benefits and costs, as well as social factors.
8. Discuss security concerns involved in building a data warehouse.
7. Compare the Kimball and Inmon approaches toward data warehouse development. Identify when each one is most effective.
6. Describe how data integration can lead to higher levels of data quality.
5. List the differences and/or similarities between the roles of a database administrator and a data warehouse administrator.
4. Discuss the major drivers and benefits of data warehousing to end users.
3. A data mart can replace a data warehouse or complement it. Compare and discuss these options.
2. What is a data warehouse, and what are its benefits? Why is Web accessibility important with a data warehouse?
1. Compare data integration and ETL. How are they related?
2. What skills should a DWA possess? Why?
1. What steps can an organization take to ensure the security and confidentiality of customer data in its data warehouse?
4. List some of the drivers for RDW.
3. What are the major differences between a traditional data warehouse and an RDW?
2. List the benefits of an RDW.
1. What is an RDW?
3. Why is the ETL process so important for data warehousing efforts?
2. Describe the three steps of the ETL process.
1. Describe data integration.
5. List the different types of data warehouse architectures.
4. Describe the major similarities and differences between the Inmon and Kimball data warehouse development approaches.
3. Does a bottom-up data warehouse development approach use an enterprise data model?
2. List several criteria for selecting a data warehouse vendor, and describe why they are important.
1. List the benefits of data warehouses.
3. List the alternative data warehousing architectures discussed in this section.
2. How has the Web influenced data warehouse design?
1. What are the key similarities and differences between a two-tiered architecture and a threetiered architecture?
5. Explain the importance of metadata.
4. Differentiate among a data mart, an ODS, and an EDW.
3. What is an ODS?
2. How does a data warehouse differ from a database?
1. What is a data warehouse?
3. Identify the role of middleware tools.
2. Describe the major components of a data warehouse.
1. Describe the data warehousing process.
5. Why do you think large organizations like DirecTV cannot afford not to have a capable data warehouse?
4. What strategic advantage can DirecTV derive from the real-time system as opposed to a traditional information system?
3. Identify the major differences between a traditional data warehouse and an active data warehouse, such as the one implemented at DirecTV.
2. What were the challenges DirecTV faced on its way to having an integrated active data warehouse?
1. Why is it important for DirecTV to have an active data warehouse?
4. In what other areas, in your opinion, can HP use text mining?Hewlett-Packard Company (HP), founded in 1939 by William R. Hewlett and David Packard, is headquartered in Palo Alto, California. The company provides products, technologies, solutions, and services to individuals, small and
3. What were HP’s challenges in text mining?How were they overcome?Hewlett-Packard Company (HP), founded in 1939 by William R. Hewlett and David Packard, is headquartered in Palo Alto, California. The company provides products, technologies, solutions, and services to individuals, small and
2. How do you think text mining techniques could be used in other businesses?Hewlett-Packard Company (HP), founded in 1939 by William R. Hewlett and David Packard, is headquartered in Palo Alto, California. The company provides products, technologies, solutions, and services to individuals, small
1. What is the practical application of text mining?Hewlett-Packard Company (HP), founded in 1939 by William R. Hewlett and David Packard, is headquartered in Palo Alto, California. The company provides products, technologies, solutions, and services to individuals, small and medium-sized
9. Go to kdnuggets.com. Explore the sections on applications as well as software. Find names of at least three additional packages for data mining and text mining.
8. Go to salfordsystems.com. Download at least three white papers on applications. Which of these applications may have used the data/text/Web mining techniques discussed in this chapter?
7. Go to fairisaac.com. Download at least three white papers on applications. Which of these applications may have used the data/text/Web mining techniques discussed in this chapter?
6. Go to teradata.com. Download at least three white papers on applications. Which of these applications may have used the data/text/Web mining techniques discussed in this chapter?
5. Go to spss.com. Download at least three white papers on applications. Which of these applications may have used the data/text/Web mining techniques discussed in this chapter?
4. Go to sas.com. Download at least three white papers on applications. Which of these applications may have used the data/text/Web mining techniques discussed in this chapter?
3. Go to statsoft.com. Select Downloads and download at least three white papers on applications. Which of these applications may have used the data/text/Web mining techniques discussed in this chapter?
2. Find recent cases of successful text mining and Web mining applications. Try text and Web mining software vendors and consultancy firms and look for cases or success stories. Prepare a report summarizing five new case studies.
1. Survey some text mining tools and vendors. Start with clearforest.com and megaputer.com. Also consult with dmreview.com and identify some text mining products and service providers that are not mentioned in this chapter.
3. Go to your library’s online resources. Learn how to download attributes of a collection of literature (journal articles) in a specific topic. Download and process the data using a methodology similar to the one explained in Application Case 7.5.
2. Interview administrators in your college or executives in your organization to determine how text mining and Web mining could assist them in their work. Write a proposal describing your findings. Include a preliminary cost/benefits analysis in your report.
1. Examine how textual data can be captured automatically using Web-based technologies. Once captured, what are the potential patterns that you can extract from these unstructured data sources?
3. Browse the Web and your library’s digital databases to identify articles that make the natural linkage between text/Web mining and contemporary business intelligence systems.
2. Go to teradatastudentnetwork.com or locate white papers, Web seminars, and other materials related to text mining and/or Web mining. Synthesize your findings into a short written report.
1. Visit teradatastudentnetwork.com. Identify cases about text and Web mining. Describe recent developments in the field. If you cannot find enough cases at the Teradata University network Web site, broaden your search to other Web-based resources.
15. Provide two exemplary business applications of Web usage mining; discuss their usage and business value.
14. What is Web usage mining? Draw a picture of the Web usage mining process and explain/discuss the major steps in the process.
13. Discuss the expected benefits of Web structure mining.Provide examples from real-world applications that you are familiar with.
12. What is Web structure mining? What are authoritative pages and hubs? How do they relate to Web structure mining?
11. What is Web content mining? How does it differ from text mining?Discuss and justify your answers with concrete examples.
10. What are the three main areas of Web mining? Discuss the differences and commonalities among these three areas.
9. Discuss the relationship between Web mining and Web analytics.
8. List and discuss three prominent application areas for text mining. What is the common theme among the three application areas you chose?
7. What is the role of natural language processing in text mining? Discuss the capabilities and limitations of NLP in the context of text mining.
6. What does it mean to induce structure into the text-based data? Discuss the alternative ways of inducing structure into text-based data.
5. Discuss the similarities and differences between the data mining process (e.g., CRISP-DM) and the threestep, high-level text mining process explained in this chapter.
4. In your own words, define text mining and discuss its most popular applications.
3. Discuss the differences and commonalities between text mining and Web mining.
2. What should an organization consider before making a decision to purchase text mining and/or Web mining software?
1. Explain the relationship among data mining, text mining, and Web mining.
3. What are the common characteristics of Web mining success stories?
2. In your own words, what are the pros and cons of Web mining?
1. Why do we need Web mining?
5. Identify value-added features developed by major e-commerce sites that may be based on Web usage mining.
4. What types of information do Web servers collect when users visit a Web page and engage in an interactive activity?
3. What is a clickstream? Why is it important in Web usage mining?
2. In an e-commerce environment, what are the potential applications of Web usage mining?
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