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How to Perform Row Count Reconciliation?

In this use case, we will explore how to compare the counts between a source table and a target table using the powerful data quality tool, iceDQ. By following these steps, you can ensure data consistency and identify any discrepancies between the tables.

Steps​

Below steps have been followed in the video.

Create Rule​

To begin, create a checksum rule within the iceDQ platform. Give the rule an appropriate name. In this example, we will compare the counts between the "Human Resources Employees" table (source) and the "Dim Employees" table (target).

Set-up Connections​

Set up the connection to the source table. In this case, we connect to the AdventureWorks database, selecting the "Human Resources" schema and the "Employee" table. Similarly, set up the connection to the target table, which in this example is the AdventureWorks Data Warehouse. Choose the "DPO" schema and the "DimEmployee" table.

Add Checks​

The source count and target count checks are automatically populated by default in the rule. This means that iceDQ will compare the counts between the two tables and identify any differences.

Publish & Run​

Publish the rule and execute it. After execution, a status warning is generated if there are discrepancies in the counts. For example, if the source count is 290 and the target count is 296, a difference of six will cause the rule to fail.

Video: How to Perform Row Count Reconciliation?​

Conclusion​

By following this use case with iceDQ, you can easily compare counts between a source and a target table, ensuring data consistency. By applying similar techniques to other tables and datasets, organizations can maintain accurate and reliable data, supporting data quality efforts and decision-making processes.

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