AI is a competitive advantage that businesses need to power innovation and digital transformation across all industries.

With the emergence of Generative AI and large language models (LLMs), the ability to generalize knowledge and understanding across diverse domains will turbocharge AI initiatives and revolutionize numerous industries. However, the effectiveness and reliability of AI and ML models depend on a robust data engineering practice that provides high-quality, trusted, and governed data at scale.
  • Jumpstart Generative AI projects with an easy, efficient, and cost-effective data engineering solution
  • Build, deploy and operationalize LLMs with high-quality, governed, and trusted data
  • Process high-volume data engineering workloads in a cost-performant manner
Jesse Davis, Moderator
Chief Technologist, DZone
As the Chief Technologist @ DZone, Jesse is responsible for guiding the strategic direction of products and helping customers build the world’s largest, most engaging developer communities for companies like Disney, Amazon, SAP, Pixar, and Unity. Jesse has been building enterprise software and engineering teams for 25 years and is a respected executive, author, speaker, and coach. Jesse serves as a software industry advisor and, prior to Devada, Jesse developed the first data access for Java and served as an expert an innovator on industry data standards including JDBC, ODBC, and ANSI SQL.
Abhilash Mula
Senior Manager, Product Management at Informatica
In his role as a Senior Manager in Product Management, Abhilash has a track record of effectively overseeing end-to-end data engineering product life cycles, conducting comprehensive market research, and devising compelling value propositions. At Informatica, his sphere of responsibility encompasses all AI & Data Analytics products, covering Data Engineering, Serverless, AI/ML, and MLOps. Abhilash's primary focus is to ensure the smooth and efficient product development and delivery of these products to Informatica's valued customers.
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