Business Intelligence 2nd Edition Efraim Turban, Ramesh Sharda, ...more - Solutions

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Understand DSS components and how they integrate
Understand important DSS classifications
Understand the essential definition of DSS
Describe DSS characteristics and capabilities
Understand the key differences and similarities between DSS and BI systems
Understand possible decision support system(DSS) configurations
Understand the major issues in implementing computerized support systems
List the major tools of computerized decision support
Describe the concept of work systems and its relationship to decision support
Describe the business intelligence (BI)methodology and concepts and relate them to DSS
Learn the conceptual foundations of the decision support systems (DSS1) methodology
Understand an early framework for managerial decision making
Define data mining as an enabling technology for business intelligence (BI)
Understand the objectives and benefits of business analytics and data mining
Recognize the wide range of applications of data mining
Learn the standardized data mining processes
Understand the steps involved in data preprocessing for data mining
Learn different methods and algorithms of data mining
Build awareness of the existing data mining software tools
Understand the pitfalls and myths of data mining
Why should Hollywood decision makers use data mining?
What are the top challenges for Hollywood managers? Can you think of other industry segments that face similar problems?
Do you think the researchers used all of the relevant data to build prediction models?
Why do you think the researchers chose to convert a regression problem into a classification problem?
How do you think these prediction models can be used? Can you think of a good production system for such mode ls?
Do you think the decision makers would easily adapt to such an information system?
What can be clone to further improve the prediction models explained in this case?
What is a neural network architecture? What are the most common neural network architectures?
How does an MLP type neural network learn?
What are the most common data mining mistakes? How can they be minimized and/or elip1inated?
Define data mining . Why there are many names and definitions for data mining?
Discuss the differences bet;veen the two most commonly used data mining process.
Are data mining processes mere seq ue ntial set of activities?
What should an organization consider before making a decision to purchase data mining software?
What is ANN? How does it compare to biological neural networks?
Visit teradatastudentnetwork.com. Identify cases about data mining. Describe recent developments in the field.
Go to te1·adatastudentnetwork.com or a URL provided by your instructor. Locate Web seminars related to data mining. In particular, watch the Web seminar given by C. Imhoff and T. Zouqes. Then answer the following questions:a. What are some of the interesting applications of data mining?b. What
For this exercise , you will replicate (on a smaller scale)the box-office prediction modeling explained in the opening vignette. Download the training dataset from Online File W4.2, MovieT1·ain.xlsx, w hich has 184 records and is in Microsoft Excel format. Use the data description given in the
Examine how new data-capture devices such as radio frequency identification (RFID) tags help organizations accurately ide ntify and segment their customers for activities such as targeted marketing. Many of these applications involve data mining. Scan the literature and the Web and then propose
Interview administrators in your college or executives in your organization to determine how data warehousing, data mining, Online Analytical Processing (OLAP), and visualization BI/ DSS tools could assist them in their work. Write a proposal describing your findings.Include cost estimates and
A ve1y good reposito1y of data that have been used to test the performance of many machine-learning algorithms is available at ics.uci.edu/-mlearn/MLRepository.htmI. Some of t11e datasets are meant to test the lin1its of cu1Tent macl1inelearning algo1itl11Tis and to compare their performance wiili
The purpose of this exercise is to develop a model to predict forest cover type using a number of cartographic measures. The given dataset (Online File W4.l) includes four wilderness areas found in the Roosevelt Natio nal Forest of northern Colorado. A total of 12 cartographic measures were
Survey some data mining tools and vendors. Start with fafrisaac.com and egain.com. Consult dmreview.com and identify some data mining products and service providers that are not mentioned in this chapter.
Go to statsoft.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?
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?
Go to nd.com. Download at least three case studies and/or customer success stories about neural network application. \"V'hat do the various success stories have in common? How do they differ?
Go to fafrisaac.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?
Go to salf01·dsystems.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?
Why do you think that consulting companies are more likely to use data mining tools and techniques? What specific va lue proposition do they offer?
Why was it important for argonauten 360° to employ a comprehensive tool that has all modeling capabilities?
What was the problem that argonauten 360° helped solve for a call-by-call service provider?
Can you think of other problems for telecommunication companies that are likely to be solved with data mining?
Understand the basic definitions and concepts of data warehouses Understand data warehousing architectures
Describe the processes used in developing and managing data warehouses
Explain data warehousing operations
Explain the role of data warehouses in decision support
Explain data integration and the extraction, transformation, and load(ETL) processes 11 Describe real~time (active) data warehousing
Understand data warehouse administration and security issues
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?
Understand the all-encompassing nature of business performance management(BPM)
Understand the closed-loop processes linking strategy to execution
Describe some of the best practices in planning and management reporting
Describe the difference between performance management and measurement
Understand the role of methodologies in BPM 111 Describe the basic elements of the balanced scorecard (BSC) and Six Sigma methodologies Describe the differences between scorecards and dashboards Understand some of the basics of dashboard design
Describe Harrah's marketing strategy. How does Harrah's strategy differ from its competitors?
What is Harrah's Total Rewards program?
What are the basic elements of Harrah's closed-loop marketing system?
What were the results of Harrah's marketing strategy?
What economic issues does Harrah's face today? Could the Total Rewards system be modified in any way to handle these issues?
Define BPM.
How does BPM differ from BI? How are they the same?
Briefly describe TSA's PIMS.
List the major BPM processes.
Why does a company need a well-formulated strategy?
What are the basic tasks in the strategic planning process?
What are some of the sources of the gap between formulating a strategy and actually executing the strategy?
What is the goal of operational planning?
What is tactic-centric planning? What is budget-centric planning?
What is the primary goal of a financial plan?
What are the critical questions that a monitoring framework answers?
What are the key elements of a diagnostic control system?
What is one of the major pitfalls of variance analysis, from a managerial perspective?
Why do 60 to 80 percent of all new projects or ventures fail?
Describe the basic steps in Harrah's closed-loop model.
According to the Saxon Group's research results, what are some of the performance management practices of the average company?
Why do few companies have time to analyze their strategic and tactical results and take corrective action based on this analysis?
What is a performance measurement system?
What is a KPI, and what are its distinguishing characteristics?
How does a KPI differ from an operational metric?
What are some of the drawbacks of relying solely on financial metrics for measuring performance?
What is the principle of obliquity?
What are some of the characteristics of a "good" collection of performance measures?
What are the characteristics of an effective performance measurement system?
What are the four perspectives in BSC?
What does the term balanced refer to in BSC?
How does a BSC align strategies and actions?

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Business Intelligence 2nd Edition Efraim Turban, Ramesh Sharda, ...more - Solutions

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