7. Orchestration & ETL (10 Qs)

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ETL, Orchestration

 which stands for Extract, Transform, and Load, is a process used to move data from one or more sources into a destination, such as a data warehouse. It involves three key steps:

Extract: Data is pulled from various sources (databases, files, APIs, etc.).

Transform: The extracted data is cleaned, enriched, and formatted to meet the business rules and requirements of the destination system. This can include data cleansing, deduplication, and aggregation.

Load: The transformed data is loaded into the target data warehouse or database.

Orchestration is the automated coordination and management of complex data pipelines, including ETL processes. It involves defining, scheduling, and monitoring the sequence of tasks to ensure they run in the correct order and at the right time. For example, an orchestration tool like Apache Airflow can manage a pipeline where an extraction task must complete successfully before the transformation task begins, and the transformation must finish before the data is loaded. Orchestration also handles error handling, retries, and dependencies between different jobs, making the data workflow reliable and efficient.

Key Difference

While ETL is about the what—the steps of moving and preparing data—orchestration is about the how—the automation and management of that entire process. Orchestration provides the framework that ensures the ETL jobs run smoothly and in the correct order, handling dependencies and failures to create a robust and automated data workflow.

Read More

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