Faster Machine Learning & The Future of Data Warehousing
The impact of machine learning (ML) is changing how we manage and process data. New applications are detecting and automating insights that help differentiate a service, save money or discover new opportunities. Today, the ML production lifecycle is complex and batch oriented, opening the door to new faster architectures that can accelerate the process and expand the adoption of new ML applications.
In this session, we will discuss the future of data warehousing and how it is shaping modern ML applications. We will also cover real world examples and demonstrate how scalable SQL can accelerate and operationalize your ML applications, as well as perform live demos of MemSQL in action.
Nikita Shamgunov is CEO and co-founder of MemSQL, the real-time data warehouse you can run anywhere.
Prior to co-founding MemSQL, Nikita worked on core infrastructure systems at Facebook. He has also served as a senior database engineer at Microsoft SQL Server for more than half a decade. Nikita holds a bachelor's, master's and doctorate in computer science, has been awarded several patents and was a world medalist in ACM programming contests.