Keynote with Charles Kim: The Data Lakehouse for the modern data engineer

We have become a digital society. We collect data at an astronomically high volume and analyze increasing amounts of data to make better decisions as quickly as changes occur. The world as we knew it has already changed; cloud adoption is at its all-time high. Traditional on-premises solutions for data storage, data management, and analytics can no longer keep up with the rate of business data consumption. The modern data architecture gives us the best of breed data lakes and purpose-built data stores. We can store ungodly amounts of data at a low, fractional cost. We are not restricted by siloed data and can empower power users to run analytics using their preferred visualization tool. Come see what the buzz is about the modern data platform with an emphasis on the Data Lakehouse. By leveraging pipelines to build modern data-engineered platforms, you will learn patterns that define a lakehouse. Gain insights on: Comparison between a data warehouse, data lake, and a data lakehouse Comparison between a DBA, a data engineer, and a data scientist The future role of the data engineer Various types of data in a data lakehouse Advantages of a data lakehouse