In the era of universal connectivity, the faster you can move data from point A to B the better. Equipping your organization with the ability to make frequent decisions in an instant offers information and intelligence advantages, such as staying one step ahead of the competition. This is especially important when incoming data is arriving at a relentless pace, in high volume, and from a variety of devices.
As our customers tap into new sources of data or modify to existing data pipelines, we are often asked questions like: What technologies should we consider? Where can we reduce data latency? How can we simplify data architectures?
Ideal technology stacks for building real-time data pipelines
How to simplify Lambda architectures
How to use memory-optimized technologies like Kafka, Spark, and in-memory databases to build real-time data pipelines
Use cases for real-time workloads, and the value they offer
Examples of data architectures used by companies like Pinterest and Comcast
About the Presenters
Eric Frenkiel, CEO & Co-Founder, MemSQL — Eric Frenkiel co-founded MemSQL and has served as CEO since inception. Before MemSQL, Eric worked at Facebook on partnership development. He has worked in various engineering and sales engineering capacities at both consumer and enterprise startups.
Ben Lorica, Chief Data Scientist, O’Reilly Media — Ben Lorica is the Chief Data Scientist and Director of Content Strategy for Data at O’Reilly Media, Inc. He has applied Business Intelligence, Data Mining, Machine Learning and Statistical Analysis in a variety of settings including Direct Marketing, Consumer and Market Research, Targeted Advertising, Text Mining, and Financial Engineering. His background includes stints with an investment management company, internet startups, and financial services.