The input file is an Aurora PostgreSQL table that contains the employee details from all the departments in the organization.

Create an Aurora PostgreSQL data object read operation. Configure the Aurora PostgreSQL connection and specify the table that contains the employee data as a source for the data object. Drag the source data object into the mapping and specify the data object access as read.

The input files are two Aurora PostgreSQL tables, one containing the employee details and the other containing the department details from the entire organization. Use the Join query to get data from the employee and the department tables.

Add a Filter transformation to filter details of employees from the

Engineering

department.

The Filter transformation filters the source data based on the value you specify for the

Dept

column. The Data Integration Service returns the rows that meet the filter condition.

Create a flat file data object write operation. Configure the flat file connection and specify the flat file object as the target data object. Drag the target data object into the mapping and specify the data object access as write.

The output file is a flat file that contains the details of the employees working in the Engineering department.

The following image shows the mapping example:

When you run the mapping, the Data Integration Service reads the employee records from the Aurora PostgreSQL table, filters out the Engineering employee details, and writes that data to a flat file.