Introducing DataRobot AI Catalog

Data is the fuel that drives high-scale innovation with AI. Enterprises that put a strategy in place encouraging a culture of collaboration and sharing of their data assets will benefit the most. These organizations will see exponential gains in productivity with AI. Their employees will work together on projects, sharing their ideas, things they create, and their domain expertise. 

However, according to recent studies, most businesses do not yet have a data culture in place. This is despite the increase in investments in big data and AI. Organizations today, are doing a better job of capturing data in modern platforms like Hadoop and the cloud. However,  they are not succeeding at getting that data into the hands of the right people who can turn it into valuable assets for their AI projects.

There are many reasons why organizations struggle to use their data effectively. Some of these include:

  1. The overwhelming number of sources available today. People already have access to data warehouses and marts, data lakes, BI systems, and content management systems. There is also a massive amount of data available on the web and in the cloud. With so many sources to choose from, how do they know where to start?
  2. Data isn’t typically ready. Data is rarely in the right condition to be used for modeling out of the gate. It usually needs manual preparation so that it is suitable for use in machine learning.
  3. Data Governance. IT needs the confidence that data is only made available to those who are permitted to access it, and users need to trust the data that is made available to them.

In the latest release of DataRobot’s enterprise AI platform, we are addressing the above challenges with the addition of an exciting new capability called AI Catalog.

 

Introducing DataRobot AI Catalog

AI Catalog helps people to easily find, understand, and use the data they need for their projects in a governed AI platform. It serves as a centralized source of truth for data engineers, data stewards, data scientists, and analysts to gain self-service access to AI assets they can trust. AI Catalog offers DataRobot customers the following benefits:

  • Creates a collaborative environment for enterprise AI. It does this by providing users with the ability to search for any AI asset, share new sources, comment, and tag data for greater understanding, visibility, and reuse.
  • Assists with data science productivity. AI catalog provides the ability to prepare and manage feature lists and create new projects directly from the UI. You can also use the data registered in the catalog to drive predictions from new data as it arrives.
  • Enables governed data management. With the AI Catalog, customers can tightly control access to AI assets. This means only the users who have the right permissions can see certain data and projects. Data stewards can provision ‘gold-standard’ assets to the enterprise while allowing individuals to upload and share their own personal assets at the same time. Data freshness can be managed through snapshots and versions and users can access lineage to see how the data originated.

AI Catalog is a tightly integrated component of the DataRobot AI platform. It is the heart of the system for searching, collaboration, and sharing of assets for AI projects. All existing products in the DataRobt AI platform will have access to AI Catalog and can instantly start benefiting from its capabilities.

AICatalog

AI Catalog Landing Page

 

Getting Started with AI Catalog

If you already have DataRobot, you can get started with AI Catalog right away. The feature is a part of our new 5.2 release and is available for all editions and all deployment options on-premises and in the cloud. 

AI Catalog works with your existing data connections and models and is accessible via the DataRobot UI and API. No additional licenses are needed to use AI Catalog, you just need to enable the feature in your settings. Your DataRobot account team can help you with this if needed.

 

Conclusion

At DataRobot, we believe that the best results for building AI and machine learning applications come from collaborative team efforts. We encourage you to check out this important new capability, as well as some of the other exciting new features in our latest release. Simply connect to your data and start sharing content, creating projects and generating new predictions today!

 

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About the Author:

Richard Tomlinson is a director in product marketing at DataRobot where he works closely with product, marketing, and sales teams to drive adoption and enablement of data management and data engineering capabilities in the DataRobot AI platform. Richard has been working in the data warehouse, BI and analytics space for over 20 years with the last eight years focused on Hadoop and cloud platforms. He is based in Chicago but is originally from the UK and has a degree in statistics from the London School of Economics.