This session will review existing technologies and their advantages and pitfalls, including Hadoop, data lakes, data warehouses, data marts, and more. I will cover what data lakehouses are, how they are architected, what workloads can run on them or adjacent to them, and more. This session will also cover: 

• The use cases that an organization can solve with data lakehouses
• How one can meld in brownfield environments 
• Examples of various data store elimination strategies 
• The simplification of the platform, including its advantages and drawbacks 
• Examples of data ingest and egest using Spark dataframes 

The solution stack examples will include popular workloads such as Kafka, Spark, NoSQL, Elastic, RDBMs, Delta Lake, and more.

Speaker: Mike King

Mike has 32-plus years of core IT experience, including stints at FedEx, Xerox, Autozone, IBM, and some boutique consulting firms. Roles have included solution architecture, enterprise architecture, data architecture, technology management, data management, DBA, analytics, data warehousing, data governance, performance and tuning, system administration, and programming.

Mike has been a presenter at Oracle Open World, the International Sybase User Group, and MidSouth DAMA. While at FedEx, he has led POCs for Big Data, EA tools, databases, archiving, and database tools. Mike delivered FedEx's initial DBaaS offering for Oracle on Linux. He also architected the 2nd generation solution that is still in use today. Mike served as a domain architect in the customer service space for an application rationalization effort. He chaired the Data Architecture Council and led a variety of data architecture efforts.