By Wayne Eckerson and Sanjeev Mohan

We are happy to say that after months of planning, the inaugural CDO TechVent on data catalogs was a big success. It paves the way for our next event on April 26, which will focus on a related topic, “data governance platforms.” 

More than 125 attendees gained a better understanding of how to evaluate, select, and implement data catalogs thanks to insights shared by industry experts, representatives from leading data catalog vendors, and data leaders from a variety of organizations. An additional 300 registered attendees will hopefully watch the event recording in the coming weeks and view and rate the Virtual Bakeoff videos. We also shared a report on data catalog trends and a scoring spreadsheet with a comprehensive set of criteria for evaluating multiple data catalog products. 

In our wrap-up session, we shared our key takeaways from the event. Here is a summary. Please send along your key takeaways!

Market Trends

• Most attendees are still in the process of evaluating data catalogs for purchase.

• Data catalogs are moving from a cost-center to a strategic initiative.

• Data governance and data management will soon converge into “data work”—there will be no more distinction between the two. Metadata will be the glue.

Data Governance Practices

• Organizations need a data governance foundation before implementing a data catalog, otherwise it won’t take root.

• Every asset exposed in a data catalog needs to be curated.

Deployment Strategies

• Organizations need a well-defined use case to guide the initial implementation of a data catalog or it won’t deliver value. 

• Data catalogs grow incrementally, use case by use case.

•  Data catalogs can be utilized for several use cases. But, don’t boil the ocean, Be very focussed on your initial goals and iterate as you gain adoption.

Role of Technology

• Data catalog vendors bring different capabilities to the market; for example, some focus on discovery, others on collaboration, and some partner with each other to bring the best of both worlds.  

• Technology is the easy part, people and process is the hard part.

• Machine learning is key to the success of a data catalog, but its primary use cases are to auto-classify data and auto-generate recommendations. Other use cases are possible but only once an organization has sufficient data upon which to train the models.

Organizational best practices

• Business should lead the charge with close alignment with technical teams. The biggest challenge is adoption of catalogs.

• Create a center of excellence and introduce innovative approaches such as gamification to improve adoption.