Information Quality for Executives
This course is in development for 2013 or beyond. The below description should be taken as an example of content and is subject to change. If you are interested in this course, please
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This intensive course aims to give participants the capability and skills to understand and solve information quality problems, and to deliver the benefits of improved information quality. State-of-the-art research to discover ways to increase the value of data warehouse initiatives, reduce costs associated with poor-quality data, and more are discussed. By attending this course, you will learn information quality principles, methods, and techniques, and successful implementations. You will be able to increase the value of your data warehouse initiatives, reduce costs associated with poor-quality data in your Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Intelligent Commerce applications.
This course will give you the skills to implement a successful information quality program by helping you to:
- Develop an understanding of the characteristics of information products
- Learn the processes to develop data element maps
- Apply the principles of managing information as a product for your organization
- Learn the principles that lead to a continuous improvement cycle for information quality
- Develop information quality metrics
- Conduct information quality audits
Fundamentals: Core concepts, understandings and tools (50%)
Latest Developments: Recent advances and future trends (15%)
Industry Applications: Linking theory and real-world (35%)
Lecture: Delivery of material in a lecture format (60%)
Discussion or Groupwork: Participatory learning (30%)
Labs: Demonstrations, experiments, simulations (10%)
Introductory: Appropriate for a general audience (40%)
Specialized: Assumes experience in practice area or field (30%)
Advanced: In-depth explorations at the graduate level (30%)
- Understand how to investigate data quality problems and identify solutions.
- Understand principles of managing information as product.
- Understand state-of-the-art research and practice in the information quality field.
- Discuss cost and benefits associated with improving information quality.
- Discuss information quality principles, methods, and techniques successfully implemented in public and private organizations.
- Discuss how to increase the value of investment in data warehouse initiatives.
- Examine how to reduce costs associated with poor-quality data in Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Intelligent Commerce applications.
- Understand various techniques and methods for assessing, measuring, and auditing information quality.
- Discuss developing practical information quality policy for an organization's information quality practice and product.
- Discuss practical principles for leading continuous improvement cycle for information quality.
Journey to Data Quality by Yang Lee, Leo Pipino, James Funk, and Richard Wang, MIT Press, 2006. This book will be given out on the first day of class but it is recommended that you read it beforehand.
Introduction to Information Quality by Craig Fisher, Eitel Lauria, Shobha Chengalur-Smith, and Richard Wang (MITIQ Publication, 2006)
For technically oriented participants, we also recommend Data Quality by Richard Wang, Mostapha Ziad, and Yang Lee, Kluwer Academic Publishers, 2001 (ISBN# 0-7923-7215-8).
Who Should Attend
This course is designed for, but not limited to, senior executives, line managers, corporate planning and policy analysts, information quality managers, quality assurance managers, data warehouse managers, and data administrators. Enrollment is limited in number in order to ensure diversity while permitting informal class interactions. Teams of two participants with complementary responsibilities are strongly encouraged, especially those from technical and functional areas. We also encourage international participants to apply. Preference is given to early applicants.
About The Lecturers
Dr. Richard Wang
Dr. Wang is Director of the MIT Information Quality (MITIQ) Program at the Center for Technology, Policy, and Industrial Development (CTPID) and Co-Director for the Total Data Quality Management (TDQM) Program at MIT Sloan School of Management. He is also the University Professor of Information Quality at University of Arkansas at Little Rock. Dr. Wang has served as a Professor at MIT for a decade, as a Professor at the University of Arizona and Boston University, and as a Visiting Professor at the University of California, Berkeley.
At MITIQ Program, Dr. Wang has developed a well-received information quality curriculum to certify practitioners for positions such as corporate IQ analyst, manager, and trainer. His outreach programs such as the MITIQ consortium extend information quality principles and theories to intelligence quality in homeland security, information architecture in both public and private sectors, and intelligent commerce. At TDQM Program, Dr. Wang co-heads the innovative Corporate Household research that investigates relationships of business units within the firm and across organizational boundaries such as those in supply chains.
Dr. Wang has put the term Information Quality on the intellectual map with myriad journal and conference publications. His books on information quality include Quality Information and Knowledge (Prentice Hall, 1999), Data Quality (Kluwer Academic, 2001), Introduction to Information Quality (MITIQ Publication, 2006), and Journey to Data Quality (MIT Press, 2006).
In 1996, Dr. Wang organized the premier International Conference on Information Quality at MIT, which he has served as the general conference chair, and currently Chairman of the Board. In 2005, Dr. Wang was the recipient of the DAMA International Academic Achievement Award. Previous recipients of this award include: Dr. Peter Chen (father of the Entity Relationship Model), Dr. E. F. Codd (father of the Relational Model), and William H. Inmon. In addition, Dr. Wang has received special recognition from the U.S. Government, the German Society of Information Quality, and the University of Arkansas at Little Rock for his contribution to the field.
Dr. Yang Lee
Dr. Lee is an Associate Professor at Northeastern University in the Information, Operations and Analysis Group. She holds a Ph.D. from MIT. Dr. Lee's research interests include data quality, IT-mediated institutional learning, systems integration, and enterprise architecture. She is the Editor-in-Chief of the ACM Journal of Data and Information Quality and has co-authored three books on data quality: Quality Information and Knowledge (Prentice Hall, 1999), Data Quality (Kluwer Academic Publishers, 2000) and Journey to Data Quality (MIT Press, 2006). Her writings have been translated into German, Spanish, and Japanese. Dr. Lee's publications have appeared in leading journals such as Communications of the ACM, Sloan Management Review, Journal of Management Information Systems, Information & Management, and IEEE Computer. She co-founded a firm that specializes in information quality. She co-chaired the International Conference on Information Quality (ICIQ), was Associate Director of MIT's Total Data Quality Management Program, and was a visiting professor at MIT. Dr. Lee has provided consultation for many companies and agencies in private and public sectors in the US and internationally.
This course takes place on the MIT campus in Cambridge, Massachusetts. We can also offer this course for groups of employees at your location. Please contact the Short Programs office for further details.
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