Profiling for data integration and migration

After you create a project, import metadata into the metadata repository, and then register the metadata to the project, you can use data profiling to evaluate your data in preparation of an integration or migration project. To profile your data, you run column analysis and key and cross-domain analysis to evaluate the content and structure of the data.

To profile your data for a data integration or migration project, you use the following data profiling tasks:

1. Running a column analysis job

   To determine the structure and content of your data and identify anomalies and inconsistencies in your data, you can analyze columns. Column analysis results are used as the foundation for all other data profiling tasks.

2. Identifying a single column primary key

   To identify a primary key for a table or file, you locate a column whose values uniquely identify the rows in the selected table. Additionally, you can verify that a primary key defined in the data source is the true primary key.

3. Running a foreign key analysis job

   To identify the foreign key candidates in one or multiple tables, you can run a key and cross-domain analysis job. Key and cross-domain analysis jobs compare the primary key of one table to the columns of another table to determine if there is a relationship between the two tables.

4. Locating overlapping data across domains

   To determine if columns contain overlapping or redundant data, you can run a key and cross-domain analysis job across columns in one or multiple tables or sources.