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To build, train and deploy AI models that perform effectively, you need AI-ready data that is relevant, clean, accurate and well-structured. This is simple in theory, but far more difficult to achieve in the real world.
AI applications typically require large volumes of data from different sources and in different formats. This makes collecting, storing, processing and integrating data more challenging. Ensuring that the data used in AI systems is managed effectively and responsibly is essential, but often complex. As a result, data quality and data governance have emerged as critical priorities for enterprises on the path to greater AI adoption.
New advancements in data management in areas such as active metadata, data catalogs and data observability are helping to close the gap. To dive into the key technologies and emerging best practices in achieving AI-ready data, DBTA is hosting a special webinar on November 7th.
Reserve your seat today!
Register Now to attend the webinar, Achieving AI-Ready Data: Active Metadata, Data Catalogs, and Data Observability. Don't miss this live event on Thursday, November 7th, 11 AM PT / 2 PM ET.
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MODERATOR |
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Danny Sandwell
Technology Strategist
Erwin by Quest |
Helen Kinsella
Community of Practice Leader
for Data Governance & Privacy
Informatica |
Stephen Faig
Research Director
Unisphere Research
and DBTA |
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