Competing with High Quality Data: Concepts, Tools, and Techniques for Building a Successful Approach to Data Quality

  • 2h 51m
  • Rajesh Jugulum
  • John Wiley & Sons (US)
  • 2014

Create a competitive advantage with data quality

Data is rapidly becoming the powerhouse of industry, but low-quality data can actually put a company at a disadvantage. To be used effectively, data must accurately reflect the real-world scenario it represents, and it must be in a form that is usable and accessible. Quality data involves asking the right questions, targeting the correct parameters, and having an effective internal management, organization, and access system. It must be relevant, complete, and correct, while falling in line with pervasive regulatory oversight programs.

Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality takes a holistic approach to improving data quality, from collection to usage. Author Rajesh Jugulum is globally-recognized as a major voice in the data quality arena, with high-level backgrounds in international corporate finance. In the book, Jugulum provides a roadmap to data quality innovation, covering topics such as:

  • The four-phase approach to data quality control
  • Methodology that produces data sets for different aspects of a business
  • Streamlined data quality assessment and issue resolution
  • A structured, systematic, disciplined approach to effective data gathering

The book also contains real-world case studies to illustrate how companies across a broad range of sectors have employed data quality systems, whether or not they succeeded, and what lessons were learned. High-quality data increases value throughout the information supply chain, and the benefits extend to the client, employee, and shareholder. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality provides the information and guidance necessary to formulate and activate an effective data quality plan today.

About the Author

DR. RAJESH JUGULUM, Ph.D., is a Data Quality and Analytics Professional. Rajesh held executive positions in these fields at Citi Group and Bank of America. Before joining financial industry, Rajesh was with MIT where he was involved in research and teaching. Currently, he teaches at Northeastern University in Boston. His honors include 2002 American Society for Quality’s Feigenbaum medal and 2006 International Technology Institute’s Rockwell medal.

In this Book

  • Foreword
  • Prelude
  • The Importance of Data Quality
  • The Data Quality Operating Model
  • The DAIC Approach
  • Quantification of the Impact of Data Quality
  • Statistical Process Control and its Relevance in Data Quality Monitoring and Reporting
  • Critical Data Elements—Identification, Validation, and Assessment
  • Prioritization of Critical Data Elements (Funnel Approach)
  • Data Quality Monitoring and Reporting Scorecards
  • Data Quality Issue Resolution
  • Information System Testing
  • Statistical Approach for Data Tracing
  • Design and Development of Multivariate Diagnostic Systems
  • Data Analytics
  • Building a Data Quality Practices Center
  • Index of Terms and Symbols
  • References
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