DataOps

Applying DevOps principles to data pipeline development, testing, and deployment to improve data quality and delivery speed.

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Future-Proof

Why It Matters

AI models require fresh, reliable data delivered through automated pipelines, and DataOps practitioners who can build and maintain these pipelines are the backbone of production AI systems.

How to Get Started

Learn data orchestration tools like Apache Airflow or Dagster, study CI/CD for data pipelines, and practice building automated data quality tests with Great Expectations or dbt.

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