Enterprise Data Catalog: Definition, Importance & Benefits

September 27th, 2022

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What is an Enterprise Data Catalog?

An enterprise data catalog serves as a single access layer to find, understand and trust data. An enterprise data catalog makes finding, understanding, and governing disparate data assets much easier for organizations.

For example, when a data practitioner needs to find information, they can turn to the enterprise data catalog to not only locate the relevant data - but also use its metadata to understand where the data came from and how it can be utilized most effectively.

The problem with using confluence pages, wikis, or spreadsheets to track metadata is that they’re not scalable. These solutions are siloed and static, relying on humans to curate and document the data. Without a centralized way to organize metadata, organizations often encounter inconsistencies, redundancies, and distrust of data.

A modern enterprise data catalog, on the other hand, implements an active metadata management approach, where the system continuously collects metadata from logs, query history, and usage statistics, and also feeds it to the rest of the data tools. This ensures there is a single, up-to-date source of information for effectively working with data.

Here is what Gartner has to say about the role of active metadata management in an enterprise data catalog:

Existing purpose-built metadata management tools and solutions will be increasingly challenged as the primary metadata asset in the enterprise by adjacent data management platforms such as databases, data integration, data quality and data governance tools. As a result, the metadata management capabilities required in the enterprise will be distributed across many markets. The stand-alone metadata management platform will be refocused from augmented data catalogs to a metadata “anywhere” orchestration platform.

Role of active metadata management in an enterprise data catalog

Role of active metadata management in an enterprise data catalog. Source: Atlan


In addition, modern enterprise data catalog solutions are built around these four key pillars that make them significantly different from their old school predecessors:

  1. One size doesn’t fit all in augmented data management
  2. Context should be embedded into teams’ daily workflows
  3. Piecemeal solutions are passe. End-users need end-to-end visibility
  4. They are open by default and thus drive infinite metadata-driven use cases

To know more about what these pillars signify and how they manifest as capabilities in modern enterprise data catalog solutions:

Download: The primer on third-generation enterprise data catalogs


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Why do you need an Enterprise Data Catalog?

Since enterprises are accumulating so much data, it’s becoming more difficult for employees to find the right data assets when they need them. This often results in asking the data team to locate the data for them and ensure it’s ready for analysis.

In Anaconda’s 2021 State of Data Science survey, respondents said they spend “39% of their time on data prep and data cleansing, which is more than the time spent on model training, model selection, and deploying models combined."

An enterprise data catalog, however, creates a central access layer for data, thus reducing time spent on searching for data and preparing it for use. This enables data teams to focus their efforts on high-value tasks that improve the data capabilities of the organization and dramatically increase the amount of value a business can achieve from its data.

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The Benefits of an Enterprise Data Catalog

A modern enterprise data catalog lets you:

  1. Find the right data
  2. Understand data better
  3. Improve data collaboration
  4. Establish proper data governance
  5. Implement DataOps activities

An enterprise data catalog provides a single source of truth by crawling and cataloging data assets, metadata, classifications, and access policies across your data ecosystem.

An EDC enables self-service data discovery for any data consumer(both technical and non-technical) by making it easier to search and find the right data asset through an accessible and intuitive user interface. Self-serve discovery improves team productivity by reducing the number of data-related requests and duplication of search efforts.

A business glossary in an enterprise data catalog helps document business definitions, KPIs, metrics, related terms, classifications, and data steward certification/validation.

A data dictionary in an enterprise data catalog provides context about data sources, tables, views, schemas, column descriptions, data profiling, and data quality.

Screenshot of Google-like search interface in enterprise data catalogs

Find any data with a Google-like search interface. Source: Atlan


[Download] → Forrester Wave™: Enterprise Data Catalog for DataOps, Q2 2022


2. Enterprise data catalog for understanding data better

Enterprise data catalogs provide data lineage that helps you understand the journey of the data from its data source to dashboards.

Data lineage greatly help in solving data quality issues and resolving bugs, not just by revealing what the problem is, but also to investigate the root cause of the incidents. Looking at the DAG logs helps save that email/escalation with a data team in a different time zone.

Data lineage helps to look upstream so when a production pipeline breaks you’ll know where the data is coming from.

Looking downstream helps alert business analysts of a probable data mismatch in a dashboard because of a pipeline issue. It tells you whose pipeline/dashboard you have broken/are going to break if you are going to make a change.

A robust data lineage setup also facilitates faster onboarding of new employees into the team — The tribal knowledge is no more siloed with an experienced few.

Quality and reproducibility of data assets are key parts of data governance, these are crucial in certain industries like health and medicine that mandates certainty and trust around data provenance — for safety and regulatory compliance.

lineage visualization in enterprise data catalogs

Visualize data lineage — both upstream and downstream. Source: Atlan


A Demo of Atlan Enterprise Data Catalog Use Cases


3. Enterprise data catalog for collaboration

With an enterprise data catalog, the tribal knowledge and business context are no more siloed with an experienced few, and no more spread across multiple applications.

Modern enterprise data catalog integrates seamlessly with other collaboration tools like Slack, Jira, GitHub, etc. Collaboration through chat, upvotes, certification, notes, READMEs, tags, and shareable SQL queries help reduce repetitive questions around data validity, usage, and quality.

The culture of collaboration not only helps with getting to the right data faster but also fosters an environment of finding newer ways to derive more value from the business data.

Instances of embedded collaboration in enterprise data catalogs

Truly democratize data analytics with colloboration. Source: Atlan


4. Enterprise data catalogs for data governance

Permitting proper access to authorized users is another main benefit and function of any data catalog. An enterprise data catalog helps govern who can access which data so the data remains safe, reliable, and confidential.

Enterprise data catalog help enable role-based access controls, automatic PII classification and tagging, and propagation of classifications downstream through lineage.

A modern enterprise data catalog is less about control and more about collaboration. It enables a paradigm shift in data governance practices to one that includes analytics governance for effective data utilization, is decentralized and community-led, and is a part of employees’ daily workflows rather than merely an afterthought.

Data governance with automated PII classification and granular access control

Data governance with automated PII classification and granular access control. Source: Atlan


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5. Enterprise data catalogs for DataOps support

As the volume of data and the number of data sources grow exponentially, data pipelines have become more and more complex resembling spaghetti of connections and interconnections.

Data engineers and architects(DataOps) are finding it immensely difficult to investigate, understand and fix issues in the pipeline. With thousands of tables, without proper context and documentation, understanding the data set has become painfully difficult.

Enterprise data catalog for DataOps broadly helps solve the above problems by facilitating data observability(lineage, data quality) and data discovery(metadata search and business glossary)

Forrester defines enterprise data catalogs for DataOps as follows:

Enterprise data catalogs create data transparency and enable data engineers to implement DataOps activities that develop, coordinate, and orchestrate the provisioning of data policies and controls and manage the data and analytics product portfolio.

DataOps brings together people, processes, and technology to enable agile, automated, and secure management of data. An enterprise data catalog can form the context, collaboration, and orchestration layer for your DataOps environment. It helps implement DataOps activities like optimizing data flow and performance, automate governed data access, and maintain data and analytics products, scale data infrastructure among other things.

For instance,

  • Integrating data lineage with CI/CD workflows helps alert downstream users — automate approval workflows for pull requests(PRs) whenever metadata changes occurs in the pipeline.
  • Data lineage and data usage statistics help to archive and deprecate unused workflows and data sources and hence saving cloud computing and storage costs.

Discover, understand, trust, and collaborate

The modern data stack continues to evolve, meaning organizations need a modern metadata management solution now more than ever. An enterprise data catalog gives organizations the structure they need to effectively and efficiently work with data to drive business intelligence.

For example, applying an enterprise data catalog to a data lake provides the level of organization necessary to prevent it from becoming a useless data swamp without any heavy lifting from the data team.

The new era of enterprise data catalogs puts collaboration and automation at the forefront so users can easily find, trust and use trusted data in today’s data-centric world.

When healthcare provider Scripps needed a data catalog to enable faster data discovery and enterprise-wide collaboration, they turned to Atlan. Check out the case study for the full story


If you are evaluating an enterprise data catalog solution for your business, do take Atlan for a spin — Atlan is a third-generation enterprise data catalog built on the premise of embedded collaboration that is key in today’s modern workplace, borrowing principles from GitHub, Figma, Slack, Notion, Superhuman, and other modern tools that are commonplace today.



Photo by Christin Hume on Unsplash.

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