Data Quality Health Check Tool

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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 elimating various data quality issues. There are five key types of data quality problems:

  • Data duplication
  • Stale data
  • Incomplete data
  • Invalid data
  • Data conflicts

This tool will ask 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.

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