Diverse, Integrated, & Real Time: Delivering the Right Data for AI/ML Success

Artificial intelligence and machine learning, however dazzling, fails without the right inputs. Nearly half of companies say they lack data quality and governance controls to support their AI/ML projects, and only one third say their models usually make it to production.

To overcome such challenges, data teams must train, feed, and tune their AI/ML models with refined datasets that bring together diverse sources on a real-time basis. They must ensure these algorithms assimilate the right knowledge and thereby make the right inferences.

Our upcoming webinar: "Diverse, Integrated, and Real Time: Delivering the Right Data for AI/ML Success" with Kevin Petrie, VP of Research at BARC, and Nick Golovin, SVP Enterprise Data Platform at CData, explores how to make this happen with a multi-faceted approach to data integration, including Change Data Capture (CDC), Real-time streaming, and virtualization of distributed dataset.

Such a data management foundation also enables data scientists and engineers alike to spend more time optimizing their AI/ML models and less time preparing its data inputs.

Key Takeaways:

• Data management challenges in AI/ML initiatives to look out for
• Data integration as a crucial element in AI/ML initiatives
• Real-life customer use cases

To receive all the info you need to join the webinar please register via the form on our landing page - [https://go.datavirtuality.com/delivering-the-right-data-for-ai-ml-success](https://bit.ly/3X0E7ok)