Why Learn Azure Databricks?

Azure Databricks is a critical platform for organizations building modern data solutions. It helps data teams:

Build scalable data pipelines for batch and streaming workloads
Process large volumes of structured and unstructured data
Develop Lakehouse architectures for analytics and AI
Integrate with Azure data services and enterprise data platforms
Accelerate data transformation and reporting workloads
Support machine learning and AI-driven solutions

As organizations increasingly adopt cloud-based analytics platforms, Azure Databricks skills are becoming highly valuable for Data Engineering and Analytics professionals.

Why Do These Hands-on Labs Matter?

These practical labs are designed to bridge the gap between theoretical knowledge and real-world implementation.

By completing these exercises, you’ll learn:

Why Azure Databricks is widely used in enterprise data engineering environments
What core Databricks components and capabilities are required for building data pipelines
Where Azure Databricks fits within modern Azure analytics architectures
How data engineers interact with clusters, storage, Spark DataFrames, and transformation logic on a daily basis

The labs provide foundational skills that are valuable when preparing for Azure Databricks projects, Data Engineering roles, and advanced Azure Databricks certifications.

What You Will Learn?

Azure Databricks workspace fundamentals
Creating and managing Spark DataFrames
Reading and writing data using multiple file formats
Configuring and managing Databricks compute resources
Working with Databricks File System (DBFS)
Using dbutils commands for storage and workspace operations
Implementing User Defined Functions (UDFs)
Performing advanced analytics using Window Functions
Processing semi-structured data using JSON and Parquet
Applying real-world data transformation techniques

Key Features

100% hands-on lab-based learning
Real-world Azure Databricks scenarios
Beginner-friendly practical exercises
Guided implementation approach
Covers core Data Engineering concepts
Learn industry-relevant Databricks skills
Build practical experience through labs

Skills You Will Gain

Azure Databricks Fundamentals
Apache Spark DataFrames
Cluster Management
DBFS Operations
Data Transformation
UDF Development
Window Function Analytics
JSON Processing
Parquet File Handling
Data Engineering Best Practices

Recommended Experience

Basic familiarity with:

Cloud computing concepts
Data and analytics fundamentals
SQL basics
Python fundamentals (helpful but not mandatory)

Prerequisites

There are no mandatory prerequisites.

However, the following knowledge will be helpful:

Basic understanding of data concepts
Familiarity with databases and SQL
Interest in Data Engineering and Analytics
Basic Azure knowledge (optional)

Who Should Take This Course?

Aspiring Data Engineers
Azure Data Professionals
Data Analysts
Data Scientists
Cloud Engineers
Big Data Developers
Students exploring Data Engineering
Professionals preparing for Azure Databricks projects

Benefits of This Course

Gain practical Azure Databricks experience
Learn by implementing real-world scenarios
Build confidence working with Spark workloads
Understand enterprise data engineering workflows
Develop skills applicable to modern analytics projects
Strengthen your Azure and Databricks knowledge
Prepare for advanced Databricks and Data Engineering learning paths

Career Relevance

The skills covered in this course are commonly used by:

Data Engineers
Analytics Engineers
Cloud Data Engineers
Big Data Developers
Azure Data Professionals
Data Platform Engineers

These foundational Azure Databricks skills can also support future learning paths in Data Engineering, Lakehouse Architecture, Apache Spark, Machine Learning, and AI-driven analytics solutions.

Note:

As part of our beta launch, each hands-on lab includes up to 5 lab attempts. This allows you to practice, experiment, and complete the exercises while helping us optimize the learning experience and cloud infrastructure.

If you require additional attempts, simply raise a request with our support team. We'll review your requirement and assist accordingly.