Real-time big data at hyperscale for AI, ML and IoT - what's needed?

Presented by
– Theresa Melvin, Chief Architect of AI-Driven Big Data Solutions, HPE
– Noel Yuhanna Principal Analyst, Forrester

About this talk

Processing big data in real-time for artificial intelligence, machine learning, and the Internet of Things poses significant infrastructure challenges. Whether it is for autonomous vehicles, connected devices, or scientific research, legacy NoSQL solutions often struggle at hyperscale. They’ve been built on top of existing RDBMs and tend to strain when looking to analyze and act upon data at hyperscale – petabytes and beyond.

Please join guest presenter, Noel Yuhanna, Principal Analyst Forrester, and Theresa Melvin, Chief Architect of AI-Driven Big Data Solutions, HPE as they cover:

• Trends in what enterprises are doing to manage big data in real-time
• The role that enterprise tools like Kafka and Spark play
• How to manage data from device to edge to core to cloud
• Independent testing of NoSQL vendor performance at scale