Data Lineage

Automate pipelines with Apache Airflow ..

Data lineage in a data catalog outlines the lifecycle of data, detailing its journey from origin to endpoint across various processes and transformations. It offers a clear, visual map of data's provenance, its modifications, and its final location. This mapping includes tracing data from source to destination, capturing all steps, transformations, and processes it encounters along the way.

The importance of data lineage lies in its role in ensuring data integrity, supporting compliance with regulations, facilitating error root cause analysis, and enhancing overall data governance and management. By providing a comprehensive view of data’s journey, data lineage is an indispensable tool for maintaining high-quality, reliable data in a data catalog.

Data Lineage - ETL

An automated data pipeline with Apache Airflow, OpenLineage, and Marquez consists of several integral components.

Apache Airflow serves as the orchestrator, managing the execution of workflows and ensuring tasks run in the correct sequence.

OpenLineage acts as the standard for tracking and reporting data lineage, offering a clear way to record the flow of data across different jobs and transformations.

Marquez functions as the metadata repository, storing detailed information about datasets, jobs, and their executions, enabling rich lineage tracking and metadata querying.

Together, these tools provide a robust framework for orchestrating, monitoring, and managing data workflows, ensuring data integrity, compliance, and ease of troubleshooting.

Apache Airflow

Apache Airflow plays a crucial role in orchestrating data pipelines by managing and scheduling complex workflows. It enables users to define dependencies between tasks, ensuring they run in the correct sequence.

Airflow provides a user-friendly interface to monitor task execution, visualize data flow, and troubleshoot any issues that arise. With its ability to integrate with various data processing tools, Airflow automates the entire data lifecycle, from extraction and transformation to loading and reporting, making it an essential component for scalable and reliable data pipeline management.

Link to Apache Airflow

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