The first step to improving data quality is to conduct an audit of which data quality problems are prevalent in the organization. Efficient organizations seek to constantly improve data quality by looking for and eliminating various data quality issues. There are five key types of data quality problems: Data duplication, stale data, incomplete data, invalid data and data conflicts.
This Excel-based tool asks a series of questions related to common data quality symptoms and problems. Your responses will highlight areas for improvement and offer recommendations on where to concentrate data quality initiatives.
Included in this zip file are:
- Intro Doc.pdf
- Terms and Conditions.pdf