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Data lakes and Lakehouses with Spark and Azure Databricks

Course

Learn about the big data ecosystem and how to use Spark to work with massive datasets. Learners will also store big data in a data lake and develop Lakehouse architecture on the Azure Databricks platform.

Learn about the big data ecosystem and how to use Spark to work with massive datasets. Learners will also store big data in a data lake and develop Lakehouse architecture on the Azure Databricks platform.

  • Intermediate

  • 3 weeks

  • Last Updated May 21, 2024

Skills you'll learn:

Big data fluencyDatabricks

Prerequisites:

No experience required

Intermediate

3 weeks

Last Updated May 21, 2024

Skills you'll learn:

Big data fluency • Databricks • Data lakes • Apache Spark

Prerequisites:

No experience required

Course Lessons

Lesson 1

Course Introduction

In this lesson, you'll learn about the course, including the prerequisites, tools, environment, and course project.

Lesson 2

Big Data Ecosystem, Data Lakes, and Spark

In this lesson, you will learn about the problems that Apache Spark is designed to solve. You'll also learn about the greater Big Data ecosystem and how Spark fits into it.

Lesson 3

Data Wrangling with Spark

In this lesson, we'll dive into how to use Spark for cleaning and aggregating data.

Lesson 4

Spark Debugging and Optimization

In this lesson, you will learn best practices for debugging and optimizing your Spark applications.

Lesson 5

Azure Databricks

In this lesson, you'll create Spark Clusters and Spark code on the Azure Databricks platform.

Lesson 6

Data Lakes and Lakehouse with Azure Databricks

In this lesson, you'll create data lakes and Lakehouse architecture on the Azure Databricks platform

Lesson 7 • Project

Building an Azure Data Lake for Bike Share Data Analytics

In this project, you'll implement Lakehouse architecture on the Azure Databricks platform.

Taught By The Best

Photo of Matt Swaffer

Matt Swaffer

General Manager, MBS

Matt has been working in software development and data science for over 20 years. Matt's career is centered on the intersection of technology, data, and human psychology. He is passionate about using data science to have a meaningful impact on our people and our planet.

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