Build and maintain trust scorecards for Databricks

Build and maintain trust scorecards with Secoda. Learn more about how you can automate workflows to turn hours into seconds. Do more with less and scale without the chaos.

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Overview

One way to enhance the trust scorecard in data literacy is through the integration of Databricks. By tagging data from Databricks, important aspects such as data reliability, quality metrics, source credibility, compliance with governance standards, accessibility, and lineage documentation can be incorporated into the scorecard. This integration ensures that stakeholders are educated about the integrity and trustworthiness of the data, enabling them to make informed decisions. It also promotes improvements in data practices and builds confidence by providing transparent and accountable assessments of data quality.

How it works

With Secoda's integration with Databricks, users can easily automate workflows using Triggers and Actions. Triggers allow users to schedule the activation of workflows based on specific time frames, providing a structured framework for subsequent actions. Actions, on the other hand, encompass various operations like filtering and updating metadata, allowing users to create detailed workflows tailored to their team's requirements. One key capability is the ability to perform bulk updates to metadata in Databricks, which can greatly streamline data management processes. Through this integration, Secoda enables the automatic tagging of data for trust scorecards using documentation completeness, usage, and other variables specified in Databricks, offering enhanced data governance and reliability.

About Secoda

Databricks integration with Secoda enhances data teams' scalability in their data enablement practices. By utilizing Secoda's data management platform, teams can easily maintain their trust scorecards. Secoda acts as a centralized index, consolidating various aspects like data catalog, lineage, documentation, and monitoring for streamlining data knowledge within the company. This integration boosts efficiency and collaboration in data management processes.

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