Prentice Hall

Business



Modern Data Warehousing, Mining, and Visualization: Core Concepts
George M. Marakas, Kelley School of Business, Indiana University

ISBN-10: 0131014595
ISBN-13: 9780131014596

Publisher: Prentice Hall
Copyright: 2003
Format: Paper; 274 pp
Published: 11/22/2002

Suggested retail price: $84.00
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For undergraduate/graduate-level Data Mining or Data Warehousing courses in Information Systems or Operations Management Departments electives.

Taking a multidisciplinary user/manager approach, this text looks at data warehousing technologies necessary to support the business processes of the twenty-first century. Using a balanced professional and conversational approach, it explores the basic concepts of data mining, warehousing, and visualization—with an emphasis on both technical and managerial issues and the implication of these modern emerging technologies on those issues. Data mining and visualization exercises—using an included fully-enabled, but time-limited version of Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software—give students hands-on experience with real-world applications.

  • NEW - A “real-world” user's perspective, rather than a designer's perspective—Emphasizes application and implementation over design and development in all topic areas.

    • Helps student managers of tomorrow understand data warehouse design and develop the skills necessary to relate to the effective and strategic application of these technologies to advance the quality of problem identification and the associated solutions.

  • NEW - Chapter Mini-cases—All derived from actual situations. Each mini-case makes specific reference to each of the key players in the scenario.

    • Gives students a point of reference for the material presented in the chapters and facilitates additional investigation by individual students or student teams (using a variety of research tools) to further explore the situation.

  • NEW - Extensive use of graphics and examples—For each concept introduced. Wherever possible, the diagrams contained in each chapter are not only referenced in the body of the text, but are positioned in such a way that they serve as a repeated visual reference for the textual discussion.

    • Aids in students' understanding of the material.

  • NEW - Narrative Vignettes—Presents a situation using a fictitious cast of characters to further clarify concepts associated with the process of making a decision.

    • Allows students not only to see how the particular technique under discussion is applied, but also to relate it to a set of circumstances or a context in which it might be considered relevant or applicable.

  • NEW - Data Mining and Data Visualization Exercises—Based on Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software applications, the leader in the field. The version of the software included with the text is fully enabled, but has a “time out” feature built into it such that the software will only be available for use by the student during the semester in which they are studying with the text. Included with the Megaputer applications is access to several actual data sets to be used in both the tutorials for the application and for many of the Megaputer exercises included at the end of relevant chapters.

    • Gives students hands-on experience in real-world data mining and data visualization applications.

  • NEW - Questions for Review—Each chapter contains a list of 10 to 20 questions, with sample responses. Each question is phrased in such a manner that a detailed and precise answer can be readily found in the chapter.

    • Supports student retention and understanding of the material.

  • NEW - Further Discussion—Several questions at the end of each chapter ask for expanded answers on the material presented.

    • Allows students to engage in a richer thought process on each topic. The questions can be used to engage students in an open class discussion and many of them can be easily expanded into individual or team mini-projects.

  • A “real-world” user's perspective, rather than a designer's perspective—Emphasizes application and implementation over design and development in all topic areas.

    • Helps student managers of tomorrow understand data warehouse design and develop the skills necessary to relate to the effective and strategic application of these technologies to advance the quality of problem identification and the associated solutions.

  • Chapter Mini-cases—All derived from actual situations. Each mini-case makes specific reference to each of the key players in the scenario.

    • Gives students a point of reference for the material presented in the chapters and facilitates additional investigation by individual students or student teams (using a variety of research tools) to further explore the situation.

  • Extensive use of graphics and examples—For each concept introduced. Wherever possible, the diagrams contained in each chapter are not only referenced in the body of the text, but are positioned in such a way that they serve as a repeated visual reference for the textual discussion.

    • Aids in students' understanding of the material.

  • Narrative Vignettes—Presents a situation using a fictitious cast of characters to further clarify concepts associated with the process of making a decision.

    • Allows students not only to see how the particular technique under discussion is applied, but also to relate it to a set of circumstances or a context in which it might be considered relevant or applicable.

  • Data Mining and Data Visualization Exercises—Based on Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software applications, the leader in the field. The version of the software included with the text is fully enabled, but has a “time out” feature built into it such that the software will only be available for use by the student during the semester in which they are studying with the text. Included with the Megaputer applications is access to several actual data sets to be used in both the tutorials for the application and for many of the Megaputer exercises included at the end of relevant chapters.

    • Gives students hands-on experience in real-world data mining and data visualization applications.

  • Questions for Review—Each chapter contains a list of 10 to 20 questions, with sample responses. Each question is phrased in such a manner that a detailed and precise answer can be readily found in the chapter.

    • Supports student retention and understanding of the material.

  • Further Discussion—Several questions at the end of each chapter ask for expanded answers on the material presented.

    • Allows students to engage in a richer thought process on each topic. The questions can be used to engage students in an open class discussion and many of them can be easily expanded into individual or team mini-projects.

1. Introduction to Data Mining, Warehousing, and Visualization.


2. The Data Warehouse.


3. Data Mining and Data Visualization.


4. Machines that Can Learn.


5. Executive Information Systems.


6. Designing and Building the Data Warehouse.


7. The Future of Data Mining, Warehousing, and Visualization.


References.


Index.

George M. Marakas is an Associate Professor of Information Systems and the BAT Faculty Fellow in Global IT Strategy at the Kelley School of Business at Indiana University in Bloomington. His teaching expertise includes systems analysis and design, technology-assisted decision making, managing IS resources, behavioral IS research methods, and data visualitation and decision support. In addition, Marakas is an active researcher in the area of systems analysis methods, data mining and visualization, creativity enhancement, conceptual data modeling, and computer self-efficacy. Dr. Marakas is a world-renown author of textbooks. Including this text, he has written Systems Analysis and Design: An Active Approach and Decision Support Systems in the 21st Century, Second Edition, both published by Prentice Hall.

Marakas received his doctorate in Information Systems from Florida International University in Miami and his MBA from Colorado State University. Prior to his academic career, he enjoyed a highly successful career in the banking and real estate industries. His corporate experience includes senior management positions with Continental Illinois National Bank and the FDIC. In addition, Marakas served as president and CEO for CMC Group, Inc., a major RTC management contractor in Miami, for 3 years.

During his tenure at the University of Maryland and now at Indiana University, Marakas distinguished himself both through his research and in the classroom. He received numerous national teaching awards, and his research has appeared in the top journals in his field.

Beyond his academic endeavors, Marakas is also an active consultant and serves as an advisor to a number of organizations including the Central Intelligence Agency, the Department of the Treasury, the Department of Defense, British-American Tobacco, Xavier University, Citibank Asia-Pacific, Nokia Corporation, Eli Lilly Corporation, and United Information Systems, among many others. His consulting and executive education activities, spanning five continents, are concentrated primarily on e-commerce strategy, workflow reengineering, CASE tool integration, and global IT strategy formation. He is a Novell Certified Network Engineer and has been involved in the corporate beta testing program for Microsoft Corporation since 1990. Marakas is also an active member of a number of professional IS organizations, an avid golfer, a second-degree black belt in Tae Kwon Do, a PADI-certified divemaster, and a member of Pi Kappa Alpha fraternity.

Helping Future Managers Understand Data Warehousing

Written from both a technical and a managerial standpoint, this text provides a foundation for teaching the basic concepts of data warehousing, mining, and visualization.

This text places strong emphasis on helping students thoroughly understand the value of data warehouses and their associated technologies with a distinctly real-world orientation that emphasizes application and implementation over design and development in all topic areas.

An Applied Approach to Understanding Data Warehousing

With the end-of-chapter material, the Companion Website at www.prenhall.com/marakas, and Megaputer Intelligence, Inc's © PolyAnalyst™ and TextAnalyst™ data mining and visualization software applications packaged with this text, students will be hands on with the content!

  • Data Mining and Data Visualization Exercises: Based on Megaputer's PolyAnalyst and TextAnalyst software applications, these tutorials will help students associate, classify, predict, and acquire knowledge from numerical and structured data.
  • Extensive use of graphics and examples are used whenever a new concept is introduced. By referencing the material, students are able to clearly remember the .important material.
  • Narrative vignettes present situations using fictitious characters to further clarify concepts associated with the process of making a decision.

View a Sample Chapter PDF:

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