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

Guide: Managing Data Quality in Databricks

Guide: Managing Data Quality in Databricks

Access this guide to understand how using Soda Library, Soda’s enterprise framework for data testing, data engineers can invoke Soda checks for data quality directly from within a Databricks Notebook.
Read the GuideRead the Guide
Contractual Data Assets at Abercrombie & Fitch

Contractual Data Assets at Abercrombie & Fitch

How Abercrombie & Fitch transitioned from reactive data management practices towards a proactive approach through the implementation of contractual data assets
Watch the VideoWatch the Video

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