Overcoming Data Management Challenges in Machine Learning


The adoption of machine learning in the enterprise continues to grow as more businesses – hungry for automation and intelligence – look to digitally transform legacy processes to enable greater efficiency, agility, and innovation. From collaboration and security to customer service and sales, established use cases are paving the way for new best practices and an expanding array of applications. At the same time, many machine-learning projects are still subject to ongoing technical challenges, including data quality, integration, and governance issues as well as problems architecting and optimizing models and pipelines.

To educate its readers about emerging best practices and strategies for overcoming data management challenges in machine learning, DBTA is kicking off 2022 with a special roundtable webinar on January 27th. Reserve your seat today to dive into this exciting new area with our experts!

Don't miss this live event on Thursday January 27th, 11:00 AM PT / 2:00 PM ET.

Register Now to attend the webinar Overcoming Data Management Challenges in Machine Learning.

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Louise Baldwin
Solution Director
Sujatha Sagiraju
SVP, Product
Denis Coady
Technical Product Manager
Stephen Faig
Research Director
Unisphere Research and DBTA