Telmai’s Integration for Databrick’s Unity Catalog

Introduction

In the current data landscape, where data engineers and analysts grapple with the complexity and volume of data, the focus should be extended to enhancing data discoverability and usability while prioritizing data accuracy and reliability.  In this context, data catalogs are emerging as crucial tools. 

As perfectly articulated by Madison Schott in her article focusing on Data Catalogs, they act as comprehensive inventories for a company’s data, detailing metadata and connecting various data stack elements. They boost data transparency and quality, categorizing assets and assigning domain experts and owners to ensure data is accurate and readily accessible.

Amongst the various offerings in the market, Databricks Unity Catalog emerges as a leading choice in this segment. It enables data access control, data access audit, data lineage, and data discovery. Unity Catalog is set at the account level, allowing admins and data stewards to manage users and their access to data centrally across all workspaces.

When merged with data observability tools, data catalogs transform data management by simplifying data navigation and helping us understand data better. As explored in our recent blog by Ankur Gupta,  this fusion leads to a more robust data governance approach, where data catalogs provide structured information about data assets, while data observability tools offer real-time insights into data health and quality. 

Telmai’s Integration For Unity Catalog In Action

Telmai’s integration with Databricks Unity Catalog is a prime example of this synergy in action. It not only aids teams in making well-informed decisions but also optimizes data management workflows, ensuring data integrity and reliability throughout the pipeline.

With this integration, Telmai would simplify data management processes, enabling teams to swiftly access and analyze vital data quality metrics without constant platform switching. Watch the video below to understand how the integration works. 

Telmai’s integration with Databricks Unity Catalog is demonstrated through a browser extension. This extension identifies and interacts with the tables and datasets you view in the Databricks unity catalog. It overlays critical information, including metadata, data quality insights, and observability details. For instance, when viewing a table, the extension displays key data health indicators, such as completeness and correctness percentages, alongside alerts for ongoing issues. 

Accurate and reliable data isn’t just a goal. It’s the backbone of effective data management. With the integration of Telmai and Databricks Unity Catalog, you’re addressing data discrepancies and preemptively detecting and isolating them, ensuring a consistent and trustworthy data stream.

Are you interested in taking your data quality to the next level? Discover how Telmai can refine your data management by requesting a demo today.