A Better Approach to Data Quality
According to The Data Warehousing Institute (TDWI), data quality problems cost U.S. businesses more than $600 billion a year. Forty percent of companies have suffered losses due to poor data quality. These companies risk losing millions of dollars annually due to poor quality data; in fact, the cost of poor data can often be up to 10–25% of total revenues. Even the most sophisticated organizations frequently overestimate the quality of their data while underestimating the cost of data errors.
Bitwise Data Quality Framework
Bitwise Data Quality Framework is designed to provide measurable quality enhancements across five critical parameters:
- Completeness. All the required values are electronically recorded.
- Standards-based. Data conforms to industry standards.
- Consistency. Data values are aligned across systems.
- Accuracy. Data values are correct.
- Time Stamped. Validity timeframe of data is clear.
Bitwise Data Quality Framework is comprised of Data Discovery – Profile and Analyze; Data Standardization, Matching and Cleansing; Data Environment; Reporting and Real-Time Monitoring; and Data Quality Policy Repository.
Our Data Quality Framework methodology fully integrates into existing functional processes at an or all stages of the software development lifecycle.
Bitwise Data Quality Framework for the Enterprise
Bitwise Data Quality Framework eliminates many of the challenges associated with poor data quality, delivering a number of important benefits:
- Less time needed to reconcile data
- Fewer delays in deploying a new system
- Greater confidence in the integrity of the system
- No revenue loss due to poor data quality
- Reduced costs (from duplicate mailings, for example)
- Higher customer satisfaction
- More stringent compliance