When you are ready to start data quality analysis, the first thing you'll need to do is select the data assets (schemas, tables, columns) that you want to monitor. You'll configure the selected tables with default settings, which will be inherited by metrics, and you'll turn on a variety of auto metrics to bootstrap your analysis.

Before you begin

• If you haven't already, add the datasource.
• Add the schemas that have tables you want to include in your data quality analysis to your Explorer tree. For details, view Add schemas.
• Consider profiling your data - this will give you details about your tables that will help you configure them for analysis.

Configure your table for data quality analysis

• Add tables and then Configure them to enable data quality analysis for a table. For details on the available settings, view the Table configuration documentation.
• Amazon S3 and Azure datasources don't contain tables. Instead of adding tables, you add virtual tables.

Add auto metrics

• Enable auto metrics once your table is configured. This is optional, but we recommend that you enable them all as they provide a good starting point for analysis.