Introduction to Spark and Databricks ~ Ike Ellis

Part 1 of a 4-part series

Introduction to Spark and Databricks
Description:
Apache Spark has become the de facto standard for large-scale data processing, powering everything from ETL pipelines to machine learning and real-time analytics. Databricks builds on Spark to provide a unified, collaborative, and production-ready platform for data engineering, analytics, and AI.
In this one-hour introductory session, we’ll demystify what Spark is, how it works, and why it has become so widely adopted. You’ll learn the core concepts behind Spark’s execution model, understand where it fits in a modern data architecture, and see how Databricks simplifies development, collaboration, and operations on top of Spark.
We’ll walk through typical use cases such as data preparation, large-scale analytics, and basic machine learning workflows, and show how Databricks notebooks and workflows make it easier for teams to be productive. By the end of the session, you’ll have a clear mental model of when and why to use Spark and Databricks, and what your next steps should be to get started.
This session is aimed at data professionals, developers, and architects who are new to Spark and Databricks or want a practical, high-level introduction—no prior experience required.