Implement Data Engineering Solutions Using Azure Databricks (DP-750)

Course 8776

Duration: 3 days
Exam Voucher: Yes
Language: English
Level: Intermediate

This course teaches data professionals how to implement data engineering solutions using Microsoft Fabric. Participants learn how to ingest, transform, orchestrate, and manage enterprise data solutions using Fabric workloads including Data Factory, Data Engineering, Data Warehouse, Real-Time Analytics, and Lakehouse architectures.

Learners will gain hands-on experience building scalable analytics solutions, implementing medallion architectures, managing pipelines, and optimising data workflows using Microsoft Fabric’s unified analytics platform.

The course focuses on practical implementation scenarios that support modern enterprise analytics and AI initiatives.

Azure Databricks Training Delivery Methods

In-Person
Online
Upskill your whole team by bringing Private Team Training to your facility.

Azure Databricks Training Information

Course Benefits
- Learn how to build AI agents using Azure AI Foundry
- Gain practical experience integrating AI models and tools
- Develop conversational AI and automation workflows
- Implement prompt orchestration and agent behaviors
- Understand responsible AI and governance practices
- Build enterprise-ready intelligent applications
- Gain hands-on experience with Microsoft official labs
- Supports hybrid and remote attendance through AnyWare®
Prerequisites
- Experience developing software applications
- Basic knowledge of Azure services
- Familiarity with REST APIs and JSON
- Understanding of AI and cloud concepts recommended
Exam Information
- Microsoft Certified: Azure Databricks Data Engineer Associate

Azure Databricks Training Outline

Learning Objectives

Explore Azure Databricks

Describe Azure Databricks architecture
Identify Azure Databricks workloads
Navigate the Azure Databricks workspace
Use notebooks in Azure Databricks
Use clusters in Azure Databricks

Use Apache Spark in Azure Databricks

Describe Apache Spark concepts
Work with Spark DataFrames
Query data using Spark SQL
Transform data with PySpark
Visualise data in notebooks

Configure Azure Databricks workspaces

Configure Azure Databricks workspaces
Manage clusters and compute resources
Configure cluster policies
Configure workspace settings
Manage Azure Databricks access

Use Azure Databricks for data engineering workloads

Ingest data into Azure Databricks
Transform and clean data
Work with Delta Lake tables
Optimise data processing workloads
Implement batch and streaming solutions

Use Delta Lake in Azure Databricks

Describe Delta Lake capabilities
Create Delta tables
Manage table versions
Use Delta Lake transactions
Optimise Delta Lake performance

Build data pipelines with Azure Databricks

Create Azure Databricks workflows
Schedule jobs and pipelines
Configure pipeline orchestration
Monitor pipeline execution
Troubleshoot pipeline failures

Secure data with Unity Catalog

Describe Unity Catalog capabilities
Configure Unity Catalog metastore
Manage catalogs and schemas
Secure data assets
Implement fine-grained access controls

Govern Azure Databricks data assets

Implement data governance practices
Manage permissions and roles
Audit data access
Apply governance policies
Manage secure data sharing

Process streaming data in Azure Databricks

Configure structured streaming workloads
Process real-time data streams
Manage checkpoints and triggers
Monitor streaming queries
Optimise streaming performance

Deploy and maintain Azure Databricks workloads

Deploy Azure Databricks solutions
Configure CI/CD workflows
Monitor Databricks workloads
Troubleshoot operational issues
Optimise performance and cost management

Commercial Pricing

29 350 kr

4-day instructor-led training course
Microsoft Official Course content
Hands-on Training
One-on-one after-course instructor coaching included

Would you like to take this course as a team?

Include dates with afternoon start times

sep 1 - 4 15:00 - 22:30 CEST

Herndon, VA or AnyWare
sep 22 - 25 9:00 - 16:30 CEST

Stockholm or AnyWare
sep 22 - 25 10:00 - 17:30 CEST

London or AnyWare
okt 13 - 16 15:00 - 22:30 CEST

Ottawa or AnyWare
nov 3 - 6 9:00 - 16:30 CET

Stockholm or AnyWare
nov 3 - 6 10:00 - 17:30 CET

London or AnyWare
dec 1 - 4 15:00 - 22:30 CET

Herndon, VA or AnyWare
dec 15 - 18 9:00 - 16:30 CET

Stockholm or AnyWare
dec 15 - 18 10:00 - 17:30 CET

London or AnyWare
jan 12 - 15 15:00 - 22:30 CET

Ottawa or AnyWare
feb 2 - 5 9:00 - 16:30 CET

Stockholm or AnyWare
feb 2 - 5 10:00 - 17:30 CET

London or AnyWare
mar 2 - 5 15:00 - 22:30 CET

Herndon, VA or AnyWare
mar 22 - 25 9:00 - 16:30 CET

Stockholm or AnyWare
mar 22 - 25 10:00 - 17:30 CET

London or AnyWare
apr 13 - 16 15:00 - 22:30 CEST

Ottawa or AnyWare
apr 27 - 30 9:00 - 16:30 CEST

Stockholm or AnyWare
apr 27 - 30 10:00 - 17:30 CEST

London or AnyWare
jun 1 - 4 15:00 - 22:30 CEST

Herndon, VA or AnyWare

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Azure Databricks Training FAQs

You will learn how to implement data engineering and analytics solutions using Microsoft Fabric workloads and services.

Participants should have foundational knowledge of analytics, SQL, and data workflows.

Yes. The course includes practical Microsoft Fabric exercises and labs.

Yes. The course includes real-time analytics and streaming data concepts.

Yes. The course is well suited for Azure and Microsoft analytics professionals transitioning to Microsoft Fabric.

Implement Data Engineering Solutions Using Azure Databricks (DP-750)

Azure Databricks Training Delivery Methods

Azure Databricks Training Information

Azure Databricks Training Outline

Learning Objectives

Live Instructor 29 350 kr

Azure Databricks Training FAQs

What will I learn in this course?

Is prior data engineering experience required?

Does the course include hands-on labs?

Will I learn real-time analytics concepts?

Is this course appropriate for Azure data professionals?

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