Profiling and Monitoring

Data Profiling

Successful decision making is heavily dependent on reliable, correct, complete, and valid 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 scans your data records from all the data sources - irrespective of its volume and complexity. It identifies problems related to correctness, completeness, and validity in the data, and suggests actions to fix the issues. Thus, it improves the quality and utility of your data with very little manual effort.

Benefits of data profiling
  • It is the first step in analyzing your data and predicting how much effort is needed to make it usable
  • It improves your trust on the data set you have
  • It is one of the mandatory steps for taking control of your organizational data and using it across the enterprise.


Monitoring is one of the indispensable aspects of data governance and good decision making. Constant monitoring of data quality helps you to take measures to improve the consistency, reliability, and accuracy of your data. Scorecards help you measure the quality of your data and assign score cards to it by tracking key matrices defined by you. It represents your data health in a graphical form, making assessment all the more easy and swift for you.


Trends help you measure the improvement in the quality of your data over a period of time. For example, in a merger between two companies (Company A and Company B), company A needs to migrate customer data in its system from company B. It will run a scorecard on the data at the beginning of the process to see the quality and may thereafter do this scoring after every cleansing. Trends plot a chart based on your recent runs or for a specified date range to give you a clearer picture on the improvement index.

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