Finally, passed the two exams for the Microsoft Certified: Azure Data Engineer certification. (NOTE: The DP-200 and the DP-201 exams have now been replaced with the single DP-203 exam which is much more focused and streamlined).
This is the most studying I’ve done for an exam in at least 10 years. There was so much material to cover and a wide range of topics. Such as Cosmos DB, Data Lake Storage Gen 2, Azure Stream Analytics, Azure Databricks, Azure Synapse Analytics, Azure Data Factory, Azure Monitor, Azure Log Analytics, and Azure Data Security and Compliance.
I am thankful for the opportunity that Microsoft allows me to take the time to study and practice on all this material as this will be the focus of my career going forward. (Don’t worry, I will continue to speak and blog on all things SQL Server on-premises, especially, performance tuning.)
DP-203 Study Guide: Data Engineering on Microsoft Azure
The DP-203 exam tests your ability to design and implement data solutions using Azure services. You’ll need to master data storage, data processing, and securing/optimizing data systems. Official DP-203 Study Guide on Microsoft Learn
Skills Measured
Design and Implement Data Storage (15–20%)
- Design and implement data lake storage
- Design and implement relational data stores
- Design and implement partitioning and indexing strategies
Develop Data Processing (40–45%)
- Ingest and transform data using Azure Synapse, Data Factory, and Databricks
- Implement batch and stream processing
- Manage data pipelines and activities
Secure, Monitor, and Optimize Data Storage and Processing (30–35%)
- Implement data security (RBAC, encryption, masking)
- Monitor data storage and processing
- Optimize and troubleshoot data pipelines
Microsoft Learn Training Paths
These self-paced modules align directly with the exam objectives:
| Topic | Learning Path | Modules |
| Data Engineering Basics | Get started with data engineering on Azure | 3 |
| Synapse SQL Pools | Build analytics solutions using Synapse serverless SQL | 4 |
| Apache Spark | Perform data engineering with Synapse Spark | 3 |
| Pipelines | Transfer and transform data with Synapse pipelines | 2 |
| Streaming | Implement a data streaming solution with Azure Stream Analytics | 1 |
| Lakehouse | Implement a lakehouse analytics solution with Azure Databricks | 1 |
Be the first to comment on "Azure Data Engineer"