Databricks Unity Catalog + Atlan: Ensuring Comprehensive Data Governance Across Your Enterprise

Updated June 07th, 2024

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Complementing Databricks Unity Catalog with Atlan is the key to implementing embedded data governance. This approach ensures that effective data governance is integral to your daily workflows.

Effective data governance is a prerequisite for innovation, as observed by Gartner’s survey of 479 chief data and analytics officers (CDAOs) in the fourth quarter of 2023. Organizations with mature D&A governance practices are 25% more likely to adopt data-driven innovations like AI.

Databricks Unity Catalog + Atlan is the winning combination for powerful, sustainable, and future-proof data governance.

In this article, we’ll see how businesses can experience the best of both worlds — Unity Catalog and Atlan — for effective data governance that’s adopted across the enterprise.


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Table of contents

  1. Databricks Unity Catalog + Atlan = Adaptable, scalable data governance
  2. Databricks Unity Catalog + Atlan: At a glance
  3. Databricks Unity Catalog + Atlan = Comprehensive data governance
  4. Related reads

Databricks Unity Catalog + Atlan = Adaptable, scalable data governance

Combining Databricks Unity Catalog and Atlan can help enterprises integrate their entire data stack seamlessly and ensure governance is embedded at every stage — within each code and workflow you use.

While Databricks Unity Catalog offers a cloud-agnostic approach to data lake governance, it isn’t enough for organizations with a broader scope and diverse use cases spanning numerous data sources, ETL tools, BI platforms, and more.

With Atlan, you get:

  • Cross-system, actionable data lineage for a single pane of glass
  • Deeper data discovery across your data asset universe
  • Unified business glossary to build a common language across the enterprise
  • Active metadata management to enable DataOps
  • Shift-left data governance and the data mesh experience
  • Automation and AI for faster time-to-value
  • Enterprise-wide adoption by data and business teams
  • Extensibility and an open platform that adapts to enterprise environments

Let’s dive into the specifics to understand how.

Cross-system, actionable data lineage for a single pane of glass


Databricks Unity Catalog provides valuable data discovery and lineage within its ecosystem, but a broader view is crucial for organizations with sprawling data landscapes.

Atlan helps you visualize your entire data estate with automated and actionable cross-system lineage. This promotes a clear understanding of data flow across diverse sources beyond Databricks.

Deeper data discovery across your data asset universe


Similarly, Atlan empowers users to search assets from all sources beyond Databricks (Tableau dashboards, dbt models, Airflow DAGs), eliminating data silos and streamlining data discovery. Such a unified approach fosters transparency in the data estate and empowers data teams.

Get insights from your enterprise-wide data estate with discovery & lineage

Get insights from your enterprise-wide data estate with discovery & lineage - Image by Atlan.

Unified business glossary to build a common language across the enterprise


Data needs a common language unifying the organization — technical and non-technical users. It should act as the connective tissue across diverse tools, personas, and outcomes.

That’s where Atlan’s powerful business glossary can help. It builds a common language for business terms and metrics, ensuring everyone understands the business context for the key data points.

Active metadata management to enable DataOps


When you pair the Databricks metadata with metadata from the rest of your data assets, you can achieve true cross-system lineage and visibility across your data stack. That’s precisely what Atlan does — activates your Databricks data with active metadata management.

Active metadata management enables DataOps by promoting collaboration, automation, and continuous improvement.

Active metadata management to enable DataOps

Active metadata management to enable DataOps - Image by Atlan.

Here’s an example. Atlan would continuously collect usage metadata from various steps of data flow — logs, query history, usage statistics, and more. Usage metrics from BI tools and Databricks, for instance, can help you understand the most/least used assets and analyze peak access times, which can optimize cloud spending.

Shift-left data governance and the data mesh experience


Databricks Unity Catalog offers basic data governance, but organizations need more to implement a truly robust data governance program.

Atlan takes data governance beyond Databricks, enabling modern paradigms like shift-left data governance and data mesh.

Unleash active data governance with DataOps-first approach

Unleash active data governance with DataOps-first approach - Image by Atlan.

The shift-left approach to data governance empowers data teams to proactively manage data and metadata quality throughout the development lifecycle.

The shift-left approach to data governance empowers data teams

The shift-left approach to data governance empowers data teams - Image by The active data governance manifesto.

Atlan facilitates shift-left data governance by providing native support for data products, domains, and contracts, allowing teams to create more value from data-driven projects.

Meanwhile, data mesh promotes decentralized ownership of data products. Atlan helps bring the data mesh to life with a repository of trusted data products, federated domain spaces, and actionable data product lineage.

Atlan activates your data mesh with trusted data products

Atlan activates your data mesh with trusted data products - Image by Atlan.

Automation and AI for faster time-to-value


Atlan also infuses its functionalities with powerful automation features. Atlan AI provides description suggestions for data asset definitions, while Atlan’s Playbooks (a no-code workflow engine) drive bulk metadata enrichment.

Advanced users can build custom automation with OpenAPIs, SDKs, and developer toolkits. Together, automation and modern data governance practices empower teams to streamline their workflows, free up more resources, and build a strong data culture across the organization.

Drive enterprise-wide data adoption for technical and non-technical users

Drive enterprise-wide data adoption for technical and non-technical users - Image by Atlan.

Enterprise-wide adoption by data and business teams


Databricks Unity Catalog can become a siloed tool primarily used by technical teams. It offers little to no integrations with collaboration tools, leaving business users out of the loop and hindering valuable collaboration and data democratization.

Atlan bridges this gap by offering a collaborative workspace designed for adoption by everyone — data engineers, data scientists, data analysts, and business users.

Atlan fosters collaboration and wider adoption through several features:

  • An intuitive UX that can be personalized based on roles
  • No-code querying
  • Embedded within your daily workflows — a Chrome extension brings Databricks context directly into BI tools used by business users
  • Proactive impact analysis results in GitHub that empower data engineers to prevent making breaking changes before they occur
  • A one-stop shop offering deep integrations with popular communication platforms like Slack and MS Teams, ensuring everyone stays informed and can collaborate efficiently on data

Extensibility and an open platform that adapts to enterprise environments


Atlan offers an open platform designed for extensibility within enterprise environments.

Atlan’s open API architecture and custom package options empower programmatic and active management of metadata. This allows for automation of tasks like data deletion and proactive alerting, streamlining data governance for complex ecosystems.


Databricks Unity Catalog + Atlan: At a glance

Combining Databricks Unity Catalog + Atlan for comprehensive data governance

Combining Databricks Unity Catalog + Atlan for comprehensive data governance - Image by Atlan.


Databricks Unity Catalog + Atlan = Comprehensive data governance

Databricks Unity Catalog offers basic data governance. For instance, it has built-in data search and discovery, automated lineage, granular access controls, AI-powered monitoring and observability, and open data sharing. These capabilities work well within the Databricks ecosystem.

However, for organizations with a broader data landscape spanning multiple tools and platforms, an ecosystem-agnostic data catalog like Atlan is needed for comprehensive data governance.

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