Soda
Databricks

Databricks.

Ensure good data quality in Databricks.

About Databricks

Databricks is a cloud-based data engineering platform that is widely used to explore, process, and transform large quantities of data. Databricks helps organizations to leverage the full benefit that comes from combining their data, ETL processes, and machine learning models and algorithms.

How Soda integrates with Databricks

Using Soda Core, Soda’s open-source framework, data engineers can check for data quality directly from within a Databricks Notebook, then push results to Soda Cloud. Data producers and data consumers can use Soda Cloud to define quality expectations and implement SLAs that ensure that data in Databricks Delta Lakes is, and remains, fit-for-purpose.

Integrate Soda with Databricks to:

  • Detect, analyze, and resolve data issues to decrease data downtime
  • Reduce the risk and cost of migrating data from source to the Lakehouse
  • Discover and share Unity Catalog data that every user can trust
Databricks
integration information coming soon!
Access docs to learn how this integration works with Soda and follow a step-by-step technical guide to get started.
Documentation

Contractual Data Assets at Abercrombie & Fitch

Contractual Data Assets at Abercrombie & Fitch

Watch how Abercrombie & Fitch transformed their data quality in Databricks by moving from reactive management to a proactive approach using contractual data assets.
Watch the VideoWatch the Video
Guide: Managing Data Quality in Databricks

Guide: Managing Data Quality in Databricks

Download this guide to learn how Soda Library, an enterprise framework for data testing, enables data engineers to run Soda quality checks directly from a Databricks Notebook.
Read the GuideRead the Guide
Pipeline Testing in Databricks

Pipeline Testing in Databricks

Learn how to run Soda data quality checks in Databricks notebooks to test data quality at various stages in Databricks pipelines.
Watch the VideoWatch the Video

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