- Shopping Bag ( 0 items )
A comprehensive guide to quality improvement from the leading expert in information and data warehouse quality.
Each year, companies lose millions as a result of inaccurate and missing data in their operational databases. This in turn corrupts data warehouses, causing them to fail. With information quality improvement and control systems, like the ones described in this book, your company can reduce costs and increase profits from quality information assets. Written by an internationally recognized expert in information quality improvement, Improving Data Warehouse and Business Information Quality arms you with a comprehensive set of tools and techniques for ensuring data quality both in source databases and the data warehouse. With the help of best-practices case studies, Larry English fills you in on:
* How and when to measure information quality.
* How to measure the business costs of poor quality information.
* How to select the right information quality tools for your environment.
* How to reengineer and cleanse data to improve the information product before it reaches your data warehouse.
* How to improve the information creation processes at the source.
* How to build quality controls into data warehouse processes.
AUTHORBIO: Larry P. English is the leading international expert in the field of information and data warehouse quality. He is a columnist for Data Management Review and a featured speaker at numerous Data Warehousing Conferences. Larry chairs Information Quality Conferences held around the world.
"--data warehouses store the info that business managers rely upon to make critical decisions. --focuses on maintaining data integrity (improving,cleansing & reengineering collection processes)--not creating a DW."
PRINCIPLES OF INFORMATION QUALITY IMPROVEMENT.
The High Costs of Low- Quality Data.
Defining Information Quality.
Applying Quality Management Principles to Information.
PRINCIPLES FOR IMPROVING INFORMATION QUALITY.
An Overview of Total Quality Data Management (TQdM).
Assessing Data Definition and Information Architecture Quality.
Information Quality Assessment.
Measuring Nonquality Information Costs.
Information Product Improvement: Data Reengineering and Cleansing.
Improving Information Process Quality: Data Defect Prevention.
Information Quality Tools and Techniques.
ESTABLISHING THE INFORMATION QUALITY ENVIRONMENT.
The 14 Points of Information Quality.
Information Stewardship: Accountability for Information Quality.
Implementing an Information Quality Improvement Environment.
Epilogue: Reaping the Benefits of Quality Information.