Databricks is one of the most valuable technologies available for data engineers working in a data-driven organization with a cloud data architecture. As a key data transformation tool, Databricks integrates seamlessly with the two top cloud providers, AWS and Azure, and harnesses the power of Spark’s distributed parallel processing engine to deliver optimal speeds on huge data volumes. Whether taking the first look at cloud technology or seeking to drive more value from current cloud architecture, it is important to understand the wide capabilities of Databricks.

This two-part webcast series helps you understand these wide-ranging capabilities through demonstrations and discussion around the considerations of each capability, with a particular focus on how their application provides value for your organization.

In this webcast, we’ll cover:

• How Databricks fits into wider cloud architecture, AWS and Azure
• Optimal set up for the Databricks notebook and cluster
• Managing costs with Databricks
• Delta Lake and file format choices
• Data exploration and debugging

Is it for you?

• Are you considering using Databricks in your cloud architecture?
• Do you currently use Databricks in your cloud architecture?
• Did you see our Databricks for Data Engineering webcast in 2019 and want an updated perspective for 2021?

The first part of this series has already broadcast.