Profiling

Making informed business decisions requires quality data. So, it is important for you to have confidence in the completeness, correctness, and validity of your data. Incomplete records, malformed fields, and a lack of context can result in misleading or inaccurate data being delivered to your business users, which can result in flawed decisions.

Data profiling can help you be confident in your data. Profiling scans your data and generates reports that identify problems related to correctness, completeness, and validity. With these reports, you can take actions to fix incorrect or malformed data.

Metadata Insights provides profiling tools to run profiling on your data assets, as well as the data feeding into the logical and physical models defined in Metadata Insights. Using this information, you can determine the reliability of your data, design data quality rules, and perform standardization and normalization routines to fix data quality issues.

The tasks involved in profiling are:

Creating a profile for your data sources
Specifying rules for analyzing the quality of your data
Creating a schedule for profile analysis, if needed
Specifying a list of users who should be notified of the analysis report

Note: You need to have the Data Integration module installed in order to use the profiling feature of Metadata Insights.