B. 3 essay questions. Samples of potential questions are available in part IV. This list is not exhaustive it is just a sample.

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1 IS482/682 Information for First Test I. What is the structure of the test? A multiple-choice questions. B. 3 essay questions. Samples of potential questions are available in part IV. This list is not exhaustive it is just a sample. II. What should I bring to the test? A. Supplies: #2 pencil (for multiple choice), B. One page (8.5 x 11) of notes. Front and back OK. C. Essays will be completed on a computer in the College of Business computing lab. We will meet in AB208 for the test. III. What are the general concepts we have covered so far this semester? A. Concept of Business Intelligence 1. Definitions of business intelligence, big data, and data analytics 2. Business intelligence in profit making vs. non-profit making organizations. 3. The goals of business intelligence. 4. History of business intelligence. 5. Relationship of a business intelligence system to business performance management. 6. Problems with BI systems, historically and currently. B. The components of a business intelligence system. 1. Data warehouse 2. ETL methods 3. Metadata repository 4. Analytical tools 5. Data visualization methods C. The data environment/architecture of an organization: 1. Types of data stored by organizations.

2 a) Internal, external b) Structured, unstructured c) Master (reference) data vs. transaction data 2. Sources of data stored by organizations. a) Transaction processing systems. b) External data source examples: (1) Data from customers (2) Data from suppliers (3) Data from government (4) Data from paid sources 3. Questions that must be answered to create a data architecture for an organization: D. Data quality. a) How is data obtained? b) Where is the data stored? c) How is the data stored? d) Who is responsible for data management? 1. Definition. 2. Examples of data quality problems. 3. Examples of how data can go bad. 4. Methods of identifying bad quality data. 5. Methods to solve the problems with data quality and improve data quality. E. Database design/data modeling. 1. Database design life cycle. 2. Definition and Purpose of a data model. 3. Components of a data model: entities, attributes, relationships, keys (primary and foreign).

3 4. Best practices in creating a data model 5. Differences between a transaction database design and a data warehouse design. Definition of each, purpose of each, structure of each, etc. 6. Similarities and differences between Kimball and Inmon data warehouse design methods and results. 7. Process for creating a data warehouse design. 8. Tools to help support the process for creating a data warehouse design. a) Stakeholder analysis table. b) Decision analysis table. c) Bus matrix for conformed dimensions 9. Overall differences between transaction database design and data warehouse design goals. 10. Normalizing vs. non-normalizing a data warehouse. 11. Differences between a transaction database, reconciled database, data mart design. 12. Periodic vs. transient data 13. Slowly changing dimensions 14. Understanding the basic differences required to make a database longitudinal. 15. Snowflake v. star schema. 16. Three differing data models a) Transaction b) Reconciled (longitudinal data warehouse that might provide the data for multiple data marts) c) Derived (data mart) 17. Data warehousing vocabulary. Examples: fact, dimension, conformed dimension, factless fact table, data granularity, derived facts, etc. 18. Impact/relative importance of time in data warehouse design

4 F. Business Performance Management or figuring out what you want a business intelligence system to do 1. Business Intelligence Competency Center 2. Strategic planning process 3. Performance measurement 4. Key performance indicators 5. Effective performance measurement G. Information visualization methods. 1. Purpose of methods, 2. Pre-attentive visualization techniques. a) Contours, color, motion, segmentation, size, orientation b) Expressions 3. Dashboards, scorecards, reports, queries. 4. Differences between design and art 5. Principles of good visualization design a) Tufte s principles b) Nielsen s usability heuristics 6. Tables vs. graphs for information visualization. a) Relative benefits and drawbacks of each? b) When should each be used? c) Description of appropriate applications for each 7. Tables best used to display: a) Quantitative to categorical relationships b) Quantitative to quantitative relationships 8. Table design a) Unidirectional b) Bidirectional 9. Graphs are best used to display relationships:

5 a) Nominal comparison b) Time series c) Ranking d) Part-to-whole e) Deviation f) Distribution g) Correlation 10. Types of graphs a) Pie b) Line c) Bar d) Bubble e) Box plot IV. Essay questions A. Tips about writing essays. 1. The number one tip for an essay is to: Make sure each question includes one thesis statement. This is really important advice for any and all essays, reports, projects, etc. This is especially important for an essay written by a graduating undergraduate senior or a graduate student!!!! Seriously: Include a thesis statement. An essay must have a strong thesis statement. If you aren t familiar with the contents of a thesis statement, then look at these websites: Integrate examples into your answers. a) Use examples from the readings. The chapters (in the Business Intelligence: A Managerial Perspective on Analytics text) provide many example cases. Use these examples to support your essay arguments. We did not directly discuss the example cases in class, but I expect to see them incorporated into your answers. b) Use examples from your personal experience, if you have experience that is relevant to the topic.

6 c) Please note: An essay without examples will not get a good grade. 3. Avoid making unsupported assertions make sure that you can provide evidence for your answers rather than simply providing your opinion in the answers. 4. Use bullet points and/or tables to structure your answers. B. Sample essay questions 1. Assume that there is a relatively high failure rate for the implementation of business intelligence systems in organizations. How might failure be defined when related to the implementation of a business intelligence system? What are at least three main contributors to the failure of these systems? What can an information technology professional do to prevent the failure of a business intelligence system? 2. How does big data differ from not-so-big-data? Is an organization that is using a data warehouse incorporating the use of big data? Is big data required for an organization to be using business intelligence effectively? 3. Should an organization have a business performance management system in place prior to the implementation of a business intelligence system? How does BI rely on BPM and how does BPM rely on BI? 4. What is the relevance of key performance indicators to the implementation success of a business intelligence system? Do you believe that information technology professionals need to understand the key performance indicators of an organization? Why or why not? 5. Some authors posit that an organization s strategy for data management should be similar to a strategy for the management of any other organizational asset. Do you agree that data is an organizational asset and should be managed like other organizational assets? Why or why not? 6. Describe four problems that an organization could have with data quality. Explain how those problems could be fixed. Explain how they might be prevented. 7. Explain how data warehousing is used as a solution to data quality and data integration problems for some organizations. 8. Is real-time data warehousing appropriate for all organizations? What factors should be considered when choosing between a real-time data warehouse (also called an active data warehouse) and a more traditional batch-oriented data warehouses?

7 9. Compare and contrast two different architectures for a data warehouse. Do you believe that the architecture for a data warehouse affects the relative success of a business intelligence system? 10. What are the issues that an organization should consider when deciding to implement a business intelligence system? Should all organizations embrace business intelligence? 11. Governmental organizations are not driven by profit and are not usually concerned with gaining market share. What are the benefits and drawbacks of using business intelligence and analytics within a governmental organization? 12. Do you believe that technical problems contribute to the failure of business intelligence in an organization? What are at least three important technical problems that could occur during the implementation of a business intelligence system using a data warehouse? 13. Must an organization have a data warehouse in order to conduct business intelligence practices? 14. Do the methods used for information visualization affect how data is perceived by people? What is the impact of information visualization on the analysis and use of data? What is the impact of pre-attentive techniques on information visualization? 15. Compare and contrast the purpose of a reconciled data model versus a data mart in the design of a data warehouse. Should all organizations using data warehousing have both a data mart and a reconciled data model design?

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