This hands-on self-paced training course targets Analysts and Data Scientists getting started using Databricks to analyze big data with Apache Spark™ DataFrames. The course ends with a capstone project demonstrating Exploratory Data Analysis with Spark DataFrames on Databricks.
Version 1.2.5: Bug fixes to the Optional/01-WhySpark module.
3-6 hours, 75% hands-on
The course is a series of six self-paced lessons plus a final capstone project performing Exploratory Data Analysis using Spark DataFrames on Databricks. Each lesson includes hands-on exercises.
Supported platforms include Azure Databricks, Databricks Community Edition, and non-Azure Databricks.
- If you're planning to use the course on Azure Databricks, select the "Azure Databricks" Platform option.
- If you're planning to use the course on Databricks Community Edition or on a non-Azure version of Databricks, select the "Other Databricks" Platform option.
During this course learners
- Use the interactive Databricks notebook environment.
- Examine external data sets.
- Query existing data sets using Spark DataFrames.
- Visualize query results and data using the built-in Databricks visualization features.
- Perform exploratory data analysis using Spark DataFrames.
- Learn to translate SQL statements to DataFrame syntax.
- Getting Started and Accessing the Course
- Querying Files with DataFrames
- Aggregations and JOINs
- Uploading and Accessing Data
- Querying JSON & Hierarchical Data with DataFrames
- Querying Data Lakes with DataFrames
- Capstone Project: Exploratory Data Analysis
- Primary Audience: Data Scientists and Engineers
- Secondary Audience: Data Analysts
- Programming in Scala or Python required.
- Please be sure to use a supported browser.
This self-paced training course may be used by 1 user for 12 months from the date of purchase. It may not be transferred or shared with any other user.