DP-3011: Implementing a Data Analytics Solution with Azure Databricks

Course Description

Unlock the full potential of Azure Databricks in this intensive, instructor-led course designed for data professionals. DP3011 teaches you how to build end-to-end data analytics solutions using Apache Spark, Delta Lake, and Databricks Workflows. You’ll learn to design efficient lakehouse architectures, ingest and transform large datasets, deploy scalable pipelines, and integrate with Azure Data Factory for enterprise-grade orchestration. Ideal for data engineers and data scientists, this course aligns with the DP203 Data Engineer Associate certification.

Target Audience

This course is perfect for:

• Data Engineers, Data Analysts, and Data Scientists responsible for architecting scalable data analytics pipelines using Azure Databricks and Delta Lake

• Professionals preparing for the DP203: Data Engineering on Azure certification

Prerequisites:

• Experience with data processing and analytics

• Familiarity with Python, SQL, and cloud data storage formats like Parquet or Delta

Course Outline 

Module 1: Explore Azure Databricks

• Provision workspaces and configure collaborative environments

• Identify key use cases and personas for Databricks analytics 

Module 2: Perform Data Analysis with Azure Databricks

• Ingest, explore, and transform data using notebooks and DataFrames

• Visualize data insights and patterns at scale 

Module 3: Use Apache Spark in Azure Databricks

• Understand Spark architecture and create optimized clusters

• Perform large-scale data processing and file transformations 

Module 4: Manage Data with Delta Lake

• Implement Delta Lake for ACID transactions, schema enforcement, and time travel

• Build reliable data storage models to ensure data consistency 

Module 5: Build Data Pipelines with Delta Live Tables

• Design declarative, real-time data pipelines using Delta Live Tables

• Automate and monitor streaming and batch processing pipelines 

Module 6: Deploy Workloads with Azure Databricks Workflows

• Orchestrate jobs, notebooks, and production pipelines using Databricks Workflows

• Integrate notebooks into orchestrated workflows using Azure Data Factory pipelines 

HandsOn Experience

Expect 40–50% of course time to be hands-on: deploying Databricks clusters, performing exploratory data analysis, building Delta Lake tables, constructing pipelines, and implementing orchestrated workflows—all reinforcing Azure Databricks analytics capabilities.

Skills You’ll Gain

By the end of DP3011, you’ll be able to:

• Set up and manage Azure Databricks workspaces and clusters

• Analyze large datasets using Apache Spark and notebooks

• Build robust Delta Lake architectures with ACID compliance

• Automate data ingestion pipelines using Delta Live Tables

• Orchestrate production-grade workflows and integrate with Azure Data Factory