Top 10 Root Causes of Data Quality Problems
sponsored by Talend

Data quality problems can undermine your organization's ability to work efficiently, comply with government regulations and make revenue. The specific technical problems include missing data, misfielded attributes, duplicate records and broken data models to name just a few.


But rather than merely patching up bad data, most experts agree that the best strategy for fighting data quality issues is to understand the root causes and put new processes in place to prevent them. This white paper discusses the top ten root causes of data quality problems and suggests steps the business can implement to prevent them.

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