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Introduction to Databricks SQL

IntermediateSkill Level
4.7+
516 reviews
Updated 05/2026
Learn Databricks SQL for data engineering, analytics, and real-time data workflows in the lakehouse architecture.
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DatabricksData Engineering3 hr16 videos46 Exercises3,600 XP5,994Statement of Accomplishment

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Course Description

Every organization has a need for a data warehousing capability to run critical business intelligence analyses. Over the years, there have been many different tools to satisfy these needs, but often were separate technology stacks that struggled to keep up with modern data needs and scale.Databricks is a powerful Data Intelligence Platform that can satisfy many of an organization's analytical needs. By leveraging Databricks SQL, an organization can utilize a hyper scalable and performant data warehouse solution directly in the lakehouse architecture.In this course, you will be introduced to the key components and workflows within Databricks SQL.First, you will learn how to use Databricks SQL to perform different data engineering tasks and moving your data through the medallion architecture to serve data teams. You will earn the common techniques many data engineers use, how to choose between different data storage techniques, and how to keep your data up to date.Next, you will learn how to analyze your data in Databricks SQL like many data analysts do in the industry. You will learn the common functions and techniques using ANSI based SQL, and will then create in-platform visualizations and dashboards to better tell a story about your data.Finally, you will learn some more advanced techniques that leverage the key differentiators of the Databricks platform. You will learn how to handle high-velocity and fast changing data using window functions, and will be able to merge datasets together as they come in.

Prerequisites

Intermediate SQLIntroduction to Databricks
1

Data Warehousing in Databricks

Build a strong data warehousing foundation with the Databricks Data Intelligence Platform! You will learn how Databricks and the lakehouse architecture set your organization up for a modern SQL and BI stack. You will also explore the key components of the Databricks SQL product, ranging from data storage techniques to compute optimizations.
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2

Data engineering with Databricks SQL

Build a strong data foundation for the lakehouse architecture! You will learn how to ingest, transform, and model your data using the capabilities in Databricks SQL. You will explore GUI-based and programmatic approaches to building out the medallion architecture, and creating a data ecosystem ready for any analytics workload.
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3

Data analysis with Databricks SQL

Create powerful data insights using Databricks SQL! You will learn how to write queries, create visualizations, and power dashboards using in-platform Databricks capabilities. You will practice leveraging SQL code, filters, and parameters to create a robust analytical application for your end users.
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4

Advanced patterns with Databricks SQL

In the final chapter, you will learn some more advanced techniques that leverage the key differentiators of the Databricks platform. You will learn how to handle high-velocity and fast-changing data using window functions, and will be able to merge datasets as they come in.
Start Chapter
Introduction to Databricks SQL
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Don’t just take our word for it

*4.7
from 516 reviews
77%
19%
3%
1%
0%
  • Donte
    4 hours ago

  • Tezendra
    yesterday

  • Bilal
    yesterday

    Good course but i was expecting to make automated data pilines instead of manul ETL

  • Ankit
    2 days ago

    Nice

  • Jorge Enrique
    2 days ago

  • Ekaterina
    2 days ago

Donte

"Nice"

Ankit

Jorge Enrique

FAQs

What SQL experience do I need for this course?

You should know basic and intermediate SQL. Familiarity with the Databricks platform through Introduction to Databricks is also recommended.

What is the medallion architecture covered in this course?

The medallion architecture organizes data into bronze, silver, and gold layers. You will learn to move data through these layers using Databricks SQL.

Does this course cover both data engineering and data analysis tasks?

Yes. You will learn data engineering tasks like ingestion and transformation, then switch to analytical workflows including common functions and visualization techniques.

Who would benefit most from this course?

Data engineers and analysts who want to use Databricks as their lakehouse platform will gain practical skills for real-world data warehousing workflows.

How is the course structured?

The course has 4 chapters and 46 exercises. Most learners complete it in about 4 hours.

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