2020 Forrester Wave:
Machine Learning Data Catalogs


Report Description

“Organizations seeking to start with a solid modern data platform foundation and grow to accommodate governance and analytics use cases will have a good partner in” — The Forrester Wave™: Machine Learning Data Catalogs, Q4 2020

With the top scores in user experience, collaboration, security, and data engineering criteria, debuts as a Strong Performer in the Forrester Wave for Machine Learning Data Catalogs.

“Enterprises that aren’t able to put data at the heart of their resilience are failing and closing,” according to a blog post by Forrester VP, Principal Analyst and Wave author Michele Goetz*. With such high stakes at play, we believe Forrester recognizes our data catalog’s flexibility, serving governance, analytics, and marketplace objectives with a clean and intuitive user experience.

In this report, Forrester highlights the most important capabilities for data management and governance in the Machine Learning Data Catalog market, noting that emerges with a “new vision for data management and governance.”

* “Why Wait? The Future of Data Is Now.” Michele Goetz, VP, Principal Analyst, Forrester Research.


Get the report debuts in the Forrester Wave with the highest possible scores in:

User Experience Icon

User Experience

No matter your technical level, you can find, understand, and use data. Our platform is built to support both technical and business users to enable everyone to use data.

Collaboration Icon


Data producers and consumers can work together like never before. Bring data and subject matter expertise together to make better business decisions and drive rapid ROI.



It’s time for agile data governance. Get data in the hands those who need it, and quickly put your knowledge into action without sacrificing security and compliance.

Data Engineering

Data Engineering uniquely supports DataOps use cases. Connect your diverse stack of data tools and technologies together through integrations, federated queries, and built-in data virtualization.

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