Data Reconciliation in Pure SQL (UNION ALL & LEFT JOIN) – Part 2

Описание: Hey everyone, welcome back!
In Part 1, we executed individual reconciliation SQLs manually.

*DO NOT MISS* the Part 1 👇
Part 1:    • Data Reconciliation in Pure SQL(Execution)...  

But in Part 2, we take a big leap forward — you’ll learn how to run all reconciliation checks at once, in a single SQL block(with UNION ALL and LEFT JOIN combination), and instantly produce a ready-to-share reconciliation report.

All the Reconciliation SQLs are here for your reference/reuse: 👇
https://github.com/ETL-TESTING/shared...

DBeaver (Databse client IDE) : How To use: 👇
https://medium.com/@ncnayak/the-manua...

In this session, I’ll walk you through the exact method I use in real ETL projects to automate reconciliation without any tools, scripts, or frameworks — just pure SQL on any database: Oracle, Postgres, Redshift, Aurora, Sybase, etc.

Here’s what we cover in this 10-minute tutorial:
Running all recon SQLs at once (counts, mismatches, aggregations)
Generating a single consolidated result set
Exporting/share-ready recon results for stakeholders
Reusable SQL templates for daily, weekly, and pipeline-level checks

This is the SQL pattern I personally rely on to speed up reconciliation for large data warehouse migrations and daily ETL cycles.
Whether you're a data engineer, ETL tester, QA analyst — this will save you hours of manual work.

Watch to the end to download the ready-to-use SQL templates from the GitHub link!

Timestamps :
00:00 Recap Part-1 and Intro for Part-2
00:22 Run All At Once as a single SQL query
01:14 Data Mismatches & UNION ALL
02:08 Run and See All Results as Output
03:11 Introduce Some Errors For Mismatches
04:18 Catch Data Mismatches as FAILED in SQL Output
05:35 Catch Count Mismatches as FAILED in SQL Output
08:32 Catch Extra Extra In Target Mismatches
09:07 ETL Process Recap
10:07 Approach to Fully Automation
11:08 Preparing for CI CD Pipeline
09:50 End


#DataReconciliation #ETLTesting #ManualTesting #DataEngineering #DatabaseTesting #ETLAutomation #SQLQueries #DataQuality #DataValidation #DWTesting