Can Collibra Data Governance Meet the Evolving Needs of Your Dynamic Data Strategy?

Updated November 28th, 2023

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Are you considering Collibra for your data governance needs? Here’s what Collibra has to offer and where people say it falls short - and how Atlan addresses those gaps.

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Collibra data governance features
Data classification
Data privacy
Data quality
Data lineage
Where Collibra falls short
Consider Atlan

Collibra data governance features

Entering the market a full decade and a half ago, Collibra is an enterprise data catalog comprising several products and features under the Collibra Data Intelligence umbrella.

In addition to cataloging data assets for your business, Collibra also supports data privacy, protection, quality, and lineage. A few of these include:

Data classification . Manual and automated classification of Personally Identifiable Information (PII) and other sensitive data, with an option to create custom data classes.
Data privacy. Adoption and adherence to data protection and privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
Policy management . Creation of policies for various teams, organizational units, user groups, etc.
Data lineage. Representation of the flow of data from one data pipeline step to another, from source to destination.

Data classification

To help you manage and protect your data, Collibra automatically applies classification to data assets when you set up ingestion from a data source. With pre-built rules and patterns, Collibra classifies your data into various packaged data classes.

Collibra offers a Data Classification Dashboard that helps you understand the data classes defined within your organization. It also provides some popular built-in, packaged data classes. However, you can only utilize these data classes after enabling automatic data classification.

Data privacy

Collibra offers a managed solution for adhering to data protection and privacy regulations, such as GDPR and CCPA.

Like other standalone Collibra applications, data privacy has its own asset model. The module focuses on three asset types: business processes, data-sharing agreements, and security issues.

The data privacy application also identifies and captures personal and business-related sensitive information, a feature enabled by automatic data classification and guided stewardship. Even with all these guardrails, the risk of exposure is only partially eliminated. So Collibra also helps you manage actual and potential security breaches.

Data quality

Collibra’s Data Quality (DQ) is a framework you can install as a standalone application on Collibra Cloud, Google Cloud, or AWS.

Collibra detects data anomalies by tracking the behavior of data assets through monitoring and observing statistical changes in the data. This gives an adaptive view of data quality and observability.

Collibra’s adaptivity is driven by rules that Collibra uses to learn what “normal” means as the underlying data changes over a period of time. This data quality framework allows you to write your own tests and rules within Collibra.

Data lineage

Collibra’s data lineage is another feature for better understanding and governing your data assets. However, this feature is limited to their cloud edition for some reason.

Collibra automatically adds data sources to the lineage graph. It then stitches together all relevant data assets from those data sources - such as tables, views, columns, etc. - to create the lineage diagram. This diagram shows how the shape of data changes through the pipeline - i.e., how it is transformed.

Where Collibra falls short

Collibra offers many of the basic features you’d find in other commercial data governance platforms. But the tool shows its age and limitations in several areas:

Collibra and other previous-generation data governance solutions are notorious for their long implementation cycles. In a large organization, it can take over a year to get Collibra up and running.
Some users complain that, despite years of raising issues, basic features like search remain hard to use.
It’s hard to extend Collibra beyond its set data model. This is partly the reason why Collibra needs separate applications for separate features. Those separate apps raise both the cost and the administrative burden associated with investing in Collibra.

Consider Atlan

Modern data governance is more than just reporting issues after they’re discovered. It’s about finding and fixing problems before they become problems. That means shifting data governance to the left - i.e., moving it earlier in the data lifecycle - via data democratization, automation, and embedded collaboration.

This is where Atlan distinguishes itself.

With design and implementation principles like adaptive and programmatic governance, Atlan makes it easier to shift governance left and detect problems before they become problems.
Atlan is one of the few data governance products that doesn’t keep your data locked in a separate tool. Embedded collaboration enables bringing data governance into your favorite tools such as Slack, Jira, Tableau, and many others.
Atlan supports DIY setup. Atlan is also super easy to set up. No expensive consultants are required. You can install, configure, and yield value from Atlan in two weeks - not a year.

Atlan has many other practical features, such as popularity and usage tracking, integration with open-source tools like dbt, advanced tag management, and more. It’s designed to provide the best data governance experience for all purposes and personas within your organization.