[100% Off] Microsoft Dp-203 Certified: Azure Data Engineer Associate

Preparing for Azure Data Engineer Certification: DP-203 Data Engineering on Microsoft Azure Exam

Added on February 10, 2026 IT & Software 2 min read

What you’ll learn

This course is ideal for students aspiring to achieve the “Microsoft Certified: Azure Data Engineer Associate” Dp-203 certification.
It includes comprehensive content aligned to pass DP-203 exam.
Students will gain hands-on experience in implementing and managing data engineering workloads using Microsoft Azure.
The course covers key Azure services
including Azure Synapse Analytics
ADF
Azure Data Lake Storage Gen2
Azure Stream Analytics
and Azure Databricks.
Past Papers and Practice: Access to 500 exam questions to solidify knowledge and prepare for certification.

Requirements

Prerequisites:
Familiarity with any database system and basic proficiency in SQL is good to have.
A foundational knowledge of data formats is expected. e.g csv etc

Description

This course is ideal for students aspiring to achieve the “Microsoft Certified: Azure Data Engineer Associate” certification.

It includes comprehensive content aligned with the DP-203 exam.

The course objectives focus on the following areas:

Design and implement data storage (15–20%)
Develop data processing (40–45%)
Secure, monitor, and optimize data storage and data processing (30–35%)

This Course structure organizes the course into a logical progression while providing a clear breakdown of the covered topics. Here’s is the structured outline of the course sections:
1. Introduction and Setup

Overview of the course and initial setup.

2. Design and Implement Data Storage

Azure Data Lake: Understanding and implementing data storage with Azure Data Lake.
Azure SQL Server: Designing storage solutions using Azure SQL Server.
Cosmos DB: Exploring storage capabilities with Cosmos DB.
Azure Synapse Analytics: Building and managing storage in Azure Synapse Analytics.

3. Develop Data Processing

Azure Synapse Spark Pool: Leveraging Spark pools in Azure Synapse for data processing.
Azure Data Factory: Developing ETL pipelines and data flows in Azure Data Factory.
Azure Databricks: Implementing data processing workflows with Azure Databricks.
Azure Event Hubs: Streaming and processing real-time data using Azure Event Hubs.
Azure Stream Analytics: Real-time data stream processing with SQL-based queries.

4. Secure Your Data

Azure Data Lake Security: Implementing security best practices for Azure Data Lake.
Azure Synapse Analytics Security: Securing data in Azure Synapse Analytics.
Azure Data Factory and Databricks Security: Ensuring secure data workflows in Azure Data Factory and Databricks.

4. Monitor and Optimize

Azure Data Lake Storage: Monitoring and optimizing storage performance.
Azure Data Factory: Ensuring efficient operations with monitoring tools.
Azure Synapse Analytics: Performance tuning and monitoring analytics workloads.
Azure Stream Analytics and Cosmos DB: Streamlining data streams and database operations.
Data Governance with Microsoft Purview: Managing and governing data using Microsoft Purview.

5. Exam Preparation