Next Event – March 21, 2024

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Driving Data Management and Analytics with Generative AI: 

Practices and Products You Need to Know

Data teams have achieved incremental productivity benefits by conversing with standalone generative AI tools such as ChatGPT, Bard, and BLOOM. The next step is to take advantage of data management and analytics tools that embed generative AI. These tools offer language model (LM) assistants that help manipulate and interpret domain-specific data through a conversational interface. Down the road, they will empower companies to weave generative AI into their internal applications and operational workflows. 

This rising generation of tools spans five categories.

  • Data engineering: Pipeline tools feature LM assistants that help data engineers build pipelines, document artifacts, and learn new techniques.
  • Cataloging: Data catalogs have LM assistants that help data engineers and stewards discover, evaluate, and describe data products.
  • Business intelligence: BI tools have LM assistants that help business users converse with data using natural language, and help power users generate, debug, optimize, and explain code.
  • Data science: AI/ML platforms enable data scientists to build, train, and implement LMs alongside other types of machine learning models.

Using these toolsets, enterprises can boost productivity and eliminate longstanding bottlenecks in their delivery of multi-structured data. This 3-hour virtual event is designed to help data & analytics leaders evaluate and select products that democratize data access and learn best practices for implementing them. Besides creating short lists of analytics products, it will review best practices for managing data analysts, teaching them business communications skills, and establishing compelling career paths.  

You Will Learn:

  • Innovative approaches to implementing language model assistants
  • Criteria to evaluate and select the right GenAI-embedded tools
  • Ways in which language models learn, process, and generate content
  • How GenAI integrates with enterprise environments