Azure Databricks for Beginners | PySpark, Unity Catalog &ETL

Name: Azure Databricks for Beginners | PySpark, Unity Catalog &ETL
Rating: 4.3 (12 reviews)

Learn Azure Databricks, PySpark, Unity Catalog, ETL Pipelines, Spark Architecture, Azure SQL & ADLS Gen2

Created byMallaiah Somula

Last updated 6/2026

English

What you'll learn

Understand Azure Databricks architecture, workspaces, clusters, notebooks, compute options, and real-world data engineering workflows
Build PySpark DataFrame transformations using select, filter, joins, aggregations, null handling, and ETL processing techniques
Implement Unity Catalog, Managed Identity, Azure Key Vault, and secure ADLS Gen2 access in Azure Databricks projects
Develop end-to-end ETL pipelines using Azure Databricks, Azure SQL Database, ADLS Gen2, JDBC, and reusable utility functions

Course content

8 sections • 28 lectures • 36h 20m total length

Azure Databricks Full Course | Databricks Introduction & Setup Data Engineering1:29:19
Explore Azure Databricks fundamentals and complete the Databricks introduction and setup for data engineering. Leverage PySpark, Unity Catalog, and ETL concepts to build scalable data pipelines.
Azure Databricks Tutorial for Beginners | Databricks Clusters, Notebook, Compute1:23:09
Explore Azure Databricks essentials for beginners, including Databricks clusters, notebooks, and compute, with an introduction to PySpark, Unity Catalog, and ETL.
Azure Databricks Notebook Options | Jobs & Pipelines, Interactive vs Job Cluster1:21:09
Explore Azure Databricks notebook options and understand how to run jobs and pipelines using interactive and job clusters, with practical PySpark workflows and ETL considerations.
Notebook Options End to End | dbutils Widgets | Parameterized Notebooks1:22:25
Explore end-to-end notebook options in Azure Databricks, using dbutils widgets to create parameterized notebooks for dynamic workflows.
Interview Scenarios | %run vs dbutils.notebook.run | Jobs vs Manual Run1:25:24
Explore practical interview scenarios in Azure Databricks, comparing %run and dbutils.notebook.run, and weighing jobs versus manual runs to optimize PySpark workflows.

Key Vault Integration | Secure Secrets Using Azure Key Vault Databricks Tutorial45:27
Secure secrets in Azure Databricks by integrating Azure Key Vault, enabling safe secret management for PySpark workloads and ETL pipelines within Databricks tutorials.
Unity Catalog Hands-On | Access ADLS Gen2 Using Managed Identity (No Mounts)1:43:19
Master Unity Catalog hands-on techniques to access ADLS Gen2 using managed identity with no mounts, enabling secure PySpark and ETL workflows in Azure Databricks.
Unity Catalog Classroom Practice | ADLS Gen2 Access Using Managed Identity1:30:32
Learn how to use Unity Catalog in Azure Databricks with classroom practice, focusing on ADLS Gen2 access secured by managed identity.
Migrate Databricks Workspace to Unity Catalog | Centralized Governance Explained1:28:13
Migrate your Databricks workspace to Unity Catalog to enable centralized governance, leveraging PySpark and etl fundamentals for beginners.

Python Fundamentals for PySpark | Complete Beginner Guide for Data Engineers1:27:33
Develop Python fundamentals for PySpark to start data engineering with a complete beginner guide, enabling you to build Spark workflows on Azure Databricks.
Python Strings for Data Engineering | Complete Deep Dive Before PySpark | ETL1:14:03
Master Python strings for data engineering with a complete deep dive before PySpark. Explore how string handling supports ETL on Azure Databricks, with Unity Catalog integration.
Python List vs Tuple in Data Engineering | Real-Time PySpark Use Cases1:27:58
Compare Python list and tuple choices in data engineering, and explore real-time PySpark use cases within Azure Databricks for ETL and Unity Catalog workflows.
Python Set & Dictionary for Data Engineering | Real-Time PySpark Use Cases1:30:43
Explore Python sets and dictionaries for data engineering, and real-time PySpark use cases in Azure Databricks, including Unity Catalog and ETL.
Python Functions for Data Engineers | Lambda, Map, Filter, Reduce & PySpark UDF1:11:10
Explore Python functions for data engineers, including lambda, map, filter, reduce, PySpark UDF, Unity Catalog, to streamline Azure Databricks ETL workflows.
Modules and Packages in Python | Real-Time Databricks | Import Statement Explain1:18:02
Master modules and packages in Python, explain import statements, and explore real-time Databricks workflows in Azure Databricks for beginners with PySpark, Unity Catalog, and ETL.

Spark Architecture Explained with Job Execution Flow | Azure Databricks Internal1:02:11
Explore Spark architecture and its job execution flow inside Azure Databricks, covering PySpark concepts, Unity Catalog governance, and ETL workflows.
Spark Architecture Explained | DAG, Partitions, Parallelism & Spark UI1:13:20
Explore the Spark architecture, from DAG execution to partitions and parallelism, and learn how to monitor jobs with the Spark UI.
PySpark Transformations and Actions Explained | Lazy Evaluation1:05:42
Master PySpark transformations and actions in Azure Databricks with an emphasis on lazy evaluation, unlocking efficient data processing for ETL workflows.
PySpark Lazy Evaluation Explained | Transformations vs Actions | Narrow vs Wide1:07:19
Explore how PySpark uses lazy evaluation to optimize data processing by distinguishing transformations from actions and understanding narrow versus wide dependencies.

PySpark Read CSV Files in Databricks | Delimiter, Quote, Header, File Name45:24
Master reading csv files in Databricks with PySpark, focusing on delimiter, quote, header, and file name. Explore Azure Databricks for beginners, with Unity Catalog and etl.
PySpark DataFrame Transformations Explained | select, filter, distinct, orderBy1:00:38
Learn how to apply PySpark DataFrame transformations in Azure Databricks, including select, filter, distinct, and orderBy, to build and optimize data workflows.
Transformations Null Handling, Aggregations, Like, Between, Union vs UnionByName1:12:23
Learn PySpark transformations, handle null values, perform aggregations, and apply like and between filters, plus union versus unionByName for reliable data merging in Azure Databricks.
PySpark Joins Explained | Inner, Left, Right, Full, Semi, Anti Joins in Azure Da1:19:55
Explain how to apply PySpark joins in Azure Databricks, covering inner, left, right, full, semi, and anti joins for effective ETL and data integration.
PySpark UDF Explained | Real Time Examples + Interview Questions1:20:27
Learn how PySpark UDFs work with real-time examples, and review common interview questions, in the context of Azure Databricks for beginners.

Databricks Read & Write Data From SQL DB| Spark JDBC Tutorial | Utility Function1:13:22
Learn how to read and write data from a sql database in databricks using spark jdbc, with a focus on utility functions for streamlined etl workflows.
Cluster Policies Explained | Auto Scaling, Auto Termination & Job Scheduling1:19:39
Explore cluster policies to manage auto scaling, auto termination, and job scheduling in Azure Databricks for beginners, leveraging PySpark, Unity Catalog, and ETL workflows.

Requirements

Basic computer knowledge and familiarity with using a web browser is enough to start this course
No prior Databricks or PySpark experience is required. Everything will be explained from beginner level
Basic understanding of databases, SQL, or data concepts will be helpful but is not mandatory
A free Azure account or Databricks Community Edition can be used to practice the hands-on exercises

Description

Welcome to the Azure Databricks for Beginners course designed for aspiring data engineers, ETL developers, students, and working professionals who want to build strong hands-on skills in Azure Databricks and PySpark from scratch.

In this course, you will learn Azure Databricks step by step with practical examples, real-time scenarios, interview-focused concepts, and end-to-end ETL project implementation. The course starts with Databricks fundamentals including workspace setup, clusters, notebooks, compute options, workflows, and job execution concepts.

You will then build strong Python fundamentals required for PySpark development including strings, lists, tuples, sets, dictionaries, functions, lambda expressions, modules, and packages using real-time data engineering examples.

The course also covers important Spark and PySpark concepts such as Spark Architecture, DAG, partitions, parallelism, lazy evaluation, transformations, actions, joins, aggregations, CSV processing, and PySpark UDFs.

One of the key highlights of this course is learning modern Azure Databricks features including Unity Catalog, Azure Key Vault integration, Managed Identity access, centralized governance, and secure ADLS Gen2 integration without mounts.

You will also learn how to connect Azure Databricks with Azure SQL Database using JDBC and build a complete end-to-end ETL pipeline using PySpark, Azure SQL Database, and ADLS Gen2.

By the end of this course, you will have practical hands-on experience in Azure Databricks and PySpark which will help you work on real-world data engineering projects and prepare for Databricks and Azure Data Engineering interviews.

Who this course is for:

Beginners who want to learn Azure Databricks, PySpark, and modern data engineering from scratch with hands-on examples
Data engineers, ETL developers, and SQL developers looking to transition into Azure Databricks and Spark technologies
Students and working professionals preparing for Databricks, PySpark, and Azure Data Engineering interviews
Anyone interested in building real-world ETL pipelines using Azure Databricks, Unity Catalog, Azure SQL, and ADLS Gen2

Azure Databricks for Beginners | PySpark, Unity Catalog &ETL

What you'll learn

Explore related topics

Course content

Course Introduction & Azure Databricks Basics5 lectures • 7hr 1min

Security, Unity Catalog & Governance4 lectures • 5hr 28min

Python Fundamentals for PySpark6 lectures • 8hr 9min

Spark Architecture & Internals4 lectures • 4hr 29min

PySpark DataFrame Operations5 lectures • 5hr 39min

Azure Databricks Integrations & Cluster Management2 lectures • 2hr 33min

Real-Time Azure Databricks ETL Project1 lecture • 1hr 42min

2026 Add-On Syllabus1 lecture • 1hr 20min

Requirements

Description

Who this course is for: