Modern Data Engineering Panel

Data Engineering is a vast field that concerns itself with efficient access to data based on the needs of a business. Though data is the prized entity from which a company extracts insights, data doesn't exist in a void. It first needs to be stored somewhere and then an API needs to be provided such that a client can access this data. Therein lie the opportunity and the challenge. We have seen an explosion in technologies in the field of data engineering (OLTP DBs, OLAP DBs, Data Streams, Big Data Processing, Search Engines, Graph Processing and Graph Serving Engines, Caches, Block and Object Stores, etc.... ). When you consider the myriad ways these puzzle pieces can be put together to build a modern data engineering stack, you soon find that no 2 stacks resemble one another. 

What does a data engineer need to know in order to be successful in today's world? What are some best practices, pitfalls, and ways to think about building a low cost-of-ownership, high-quality data platform? What technologies are non-starters and why? What technologies are hidden gems? Finally, what should the industry think about and what is coming next? Join our panel of experts as we explore these questions in order to shed light on these areas.