Part I: Introduction to Profiles > Introduction to Profiles > Profiling Process
  

Profiling Process

When you begin a data integration project, profiling is often the first step. You can create profiles to analyze the content, quality, and structure of data sources. As a part of the profiling process, you discover the metadata of data sources.
You use different profiles for different types of data analysis, such as a column profile. You uncover and document data quality issues. Complete the following tasks to perform profiling:
  1. 1. Find and analyze the content of data in the data sources. Includes datatypes, value frequency, pattern frequency, and data statistics, such as minimum value and maximum value.
  2. 2. Review profiling results.
  3. 3. Create reference data.
  4. 4. Drill down on profile results.
  5. 5. Document data issues.
  6. 6. Create and run rules.
  7. 7. Create scorecards to monitor data quality.