Competing with High Quality Data

Competing with High Quality Data Front Cover
1 Reviews
2014-03-10
304 pages

Book Description

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 , , 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
  • 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.

Table of Contents

Chapter 1 The Importance of Data Quality

Section I Building a Data Quality Program
Chapter 2 The Data Quality Operating Model
Chapter 3 The DAIC Approach

Section II Executing a Data Quality Program
Chapter 4 Quantification of the Impact of Data Quality
Chapter 5 Statistical Process Control and Its Relevance in Data Quality Monitoring and Reporting
Chapter 6 Critical Data : Identification, Validation, and Assessment
Chapter 7 Prioritization of Critical Data Elements (Funnel Approach)
Chapter 8 Data Quality Monitoring and Reporting Scorecards
Chapter 9 Data Quality Issue Resolution
Chapter 10 Information System
Chapter 11 Statistical Approach for Data Tracing
Chapter 12 and Development of Multivariate Diagnostic Systems
Chapter 13 Data Analytics
Chapter 14 Building a Data Quality Practices Center

Appendix A EQUATIONS FOR SIGNAL-TO-NOISE (S/N) RATIOS
Appendix B MATRIX THEORY: RELATED TOPICS
Appendix C SOME USEFUL ORTHOGONAL ARRAYS

Book Details

  • Title: Competing with High Quality Data
  • Author:
  • Length: 304 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2014-03-10
  • ISBN-10: 1118342321
  • ISBN-13: 9781118342329