Accelerate Insights and Enhance Efficiency with AI-Generated Catalog Documentation
Webinar Speaker: David Stodder, Senior Director of Research for BI, TDWI
Date: Tuesday, April 30, 2024
Time: 9:00 a.m. PT / 12:00 p.m. ET
Excitement about AI, including generative AI, is driving organizations across industries to move quickly to assemble talent and develop and deploy models aimed at transforming customer experiences and marketing, improving operational decisions, and spurring innovation.
However, too many projects are falling short due to poor governance and disorganized information about data and AI assets. Users—data scientists, data engineers, analysts, developers—cannot locate what they need or be certain that what they’ve found is complete and correct. This leads to poor-quality data and time-consuming manual work that reduces productivity.
Better governance can help solve problems. Data and AI governance are both essential and should be closely related, but they are often separate and fragmented across diverse data platforms, tools, and applications.
By centralizing information about data, data lineage, model versions, and more, a data catalog can play a critical role in bringing data and AI governance together to support compliance. Through accurate and complete documentation, it can accelerate the ability of users focused on business-driven initiatives to find what they need, when they need it.
Register today to learn how your organization can use a catalog—in particular, a catalog’s AI-generated documentation features—to solve data and AI governance problems and enable higher user productivity. By providing a layer of data intelligence (with accurate and comprehensive descriptions) that is above diverse data platforms and AI applications, a data catalog allows data and AI teams to avoid getting dragged down in complexity and keep their focus on delivering value. Key discussion points will include:
- How to take advantage of AI-generated catalog documentation while ensuring that users retain control of documentation processes
- How users can get the most value out of a catalog to speed exploration and securely discover, access, and collaborate on trusted data and AI assets
- Best practices for using data intelligence to advance AI projects and ensure business value
Guest Speakers
Oliver Chiu
Product Marketing Leader for GenAI
Databricks
Ravishankar Rao Vallabhajosyula
Senior Director- Data Science
Impetus
Ravi leads the data science practice at Impetus. At Impetus, he has contributed extensively to various AI and ML initiatives. He has been involved in delivering successful data science engagements for several customers. Ravi has over two decades of experience working with data modeling and simulation and machine learning in engineering design, manufacturing, energy, aerospace, life sciences, healthcare, and other areas.
David Stodder