SP805-Az: Getting Started with Apache Spark SQL (Azure Databricks)

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The training is priced from $ 75.00 USD per participant

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Note: For Self Paced courses, you are purchasing for 1 user for 1 year

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Summary

This hands-on self-paced training course targets Analysts and Data Scientists getting started using Databricks to analyze big data with Apache Spark™ SQL. The course ends with a capstone project demonstrating Exploratory Data Analysis with Spark SQL on Databricks.

NOTE: This course is specific to the Databricks Unified Analytics Platform (based on Apache Spark™). While you might find it helpful for learning how to use Apache Spark in other environments, it does not teach you how to use Apache Spark in those environments.

Description

Length

3-6 hours, 75% hands-on

Format: Self-paced

The course is a series of six self-paced lessons plus a final capstone project performing Exploratory Data Analysis using Spark SQL on Databricks. Each lesson includes hands-on exercises.

Platform

This version of the course is intended to be run on Azure Databricks.

Learning Objectives

During this course learners

Use the interactive Databricks notebook environment.
Examine external data sets.
Query existing data sets using Spark SQL.
Visualize query results and data using the built-in Databricks visualization features.
Perform exploratory data analysis using Spark SQL.

Lessons

Getting Started and Accessing the Course
Querying Files with SQL
Aggregations, JOINs and Nested Queries
Uploading and Accessing Data
Querying JSON & Hierarchical Data with SQL
Querying Data Lakes with SQL
Capstone Project: Exploratory Data Analysis

Target Audience

Primary Audience: Data Analysts

Prerequisites

Knowledge of SQL required.

Lab Requirements

Please be sure to use a supported browser.

License Limitations

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.

Terms

The use of the self-paced training course is subject to the Terms of Service and the Databricks Privacy Policy.

Duration

6 hours