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ETL Automation - Apache Airflow

ETL Automation - Apache Airflow

ETL Automation - Apache Airflow

Tune Protect Group

1 month

Automation

Tune Protect Group

1 month

Automation

Tune Protect Group

1 month

Automation

Colaborators

Project Overview

The historical table in MYSQL databases is updated manually which consumes a lot of time. Building an automated ETL Pipeline ensure efficiency in detecting new data entries in MSSQL and performing ETL before loading into MYSQL Historical Tables.

Objective

  • Automate ETL pipeline for Tune Protect EMEIA & Tune Protect Re.

  • Monitor the Pipeline to ensure each task runs without error.

  • Analyze the query performance of each table update.

Skills & Tools Used

Project Overview

The historical table in MYSQL databases is updated manually which consumes a lot of time. Building an automated ETL Pipeline ensure efficiency in detecting new data entries in MSSQL and performing ETL before loading into MYSQL Historical Tables.

Objective

  • Automate ETL pipeline for Tune Protect EMEIA & Tune Protect Re.

  • Monitor the Pipeline to ensure each task runs without error.

  • Analyze the query performance of each table update.

Skills & Tools Used

Project Overview

The historical table in MYSQL databases is updated manually which consumes a lot of time. Building an automated ETL Pipeline ensure efficiency in detecting new data entries in MSSQL and performing ETL before loading into MYSQL Historical Tables.

Objective

  • Automate ETL pipeline for Tune Protect EMEIA & Tune Protect Re.

  • Monitor the Pipeline to ensure each task runs without error.

  • Analyze the query performance of each table update.

Skills & Tools Used

Outcomes

Designed DAGs with a total of six tasks each, including two grouped tasks per DAG. The DAGs performed status and data checks before further transformation.

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© Copyright 2025. All rights Reserved.

Made by

Bavenraj

in

© Copyright 2025. All rights Reserved.

Made by

Bavenraj

in

Available for Work

Available for Work