Customer Service
Production vs. Development QA Automation
Created an app where the user can input the production table name and dev table name. He can then review the columns - Data Type, Dimension/Measure, can be used for duplicate key.
The challenge
Why it exists
As an analyst whenever we push changes to production we require to perform a through QA between production dataset and dev dataset. This app automates the same.
The approach
How it works
Created an app where the user can input the production table name and dev table name. He can then review the columns - Data Type, Dimension/Measure, can be used for duplicate key. He can also enter the %diff which is acceptable for a result to pass. After initial review he can go for QA where the o/p is a brief summaty and a google sheet link with the summary and breakdown of the QA. This will help him in realizing if there is an error in his code which may break the production.
Key capabilities
What it does
Created an app where the user can input the production table name and dev table name.
He can then review the columns - Data Type, Dimension/Measure, can be used for duplicate key.
He can also enter the %diff which is acceptable for a result to pass.
After initial review he can go for QA where the o/p is a brief summaty and a google sheet link with the summary and breakdown of the QA.
Typically used by
Analysts
Business impact
This is a handy tool for data analysts and will save there time in performing QA and prevent from pushing incorrect code to production
Built with
Technology
Tools & Frameworks
Integrations
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