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Data profiling

Definition:

Data profiling is the process of analyzing and assessing data for accuracy, completeness or other statistically unique values. Data profiling helps organizations proactively manage their data quality, so they can stop small errors from becoming major challenges.

What is data profiling?

With an estimated 2.5 quintillion bytes of data created every day, organizations are having trouble keeping up with the quality of the data they’re collecting. That’s where data profiling tools can help.

Experian Data Quality’s 2015 global benchmark report found that 32 percent of organizations are leveraging data profiling tools today. By using data profiling software, you can clarify if the structure and content of your data follows organizational guidelines put in place by your data stewards or other data owners.

Data profiling software helps you truly understand your data, so you can take the necessary steps to improve it. While a major benefit of data profiling tools is greater data quality, profiling data can also help you:

  • Identify data anomalies at the source that should be corrected
  • Discover data quality issues that must be addressed when migrating from one system to another
  • Highlight which areas suffer from the most serious or numerous data quality issues
  • Discover problems such as illegal values, misspellings, missing values, varying value representation and duplicates
  • Shorten the implementation cycle of major projects
  • Improve your understanding of data

Profiling data helps you identify where data quality problems exist within your systems, and by extension, where to look to fix those problems.

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Learn more about data governance

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