Data Engineering on Microsoft Azure Training
This course equips participants with the knowledge and skills to design and build secure, scalable, and efficient data processing solutions on Microsoft Azure. Students will learn how to integrate, transform, and consolidate data from various structured and unstructured sources into a format suitable for analytics. The course also covers implementing data storage, managing data pipelines, and optimizing data solutions for performance and cost.
Data Engineering on Microsoft Azure (DP-203)
Course Overview
- Design and implement data storage solutions on Azure
- Build and manage data pipelines for batch and streaming data
- Integrate and transform data using Azure Data Factory and Synapse Analytics
- Implement security and compliance features for data solutions
- Monitor, troubleshoot, and optimize data processing systems
- Work effectively with Azure Databricks, Data Lake, and related services
- Identify design decisions to ensure security and recoverability (disaster recovery)
Course Outline
- Module 1: Introduction to Data Engineering on Azure
- Overview of Azure data services and architecture
- Roles and responsibilities of a Data Engineer
- Core principles of data engineering in the cloud
- Module 2: Designing and Implementing Data Storage
- Choosing the right data storage option
- Implementing Azure Data Lake Storage Gen2
- Managing and securing data in Azure storage solutions
- Module 3: Data Ingestion and Integration
- Designing data ingestion strategies
- Building pipelines with Azure Data Factory
- Working with event-based and streaming data ingestion
- Module 4: Data Transformation and Processing
- Using Azure Synapse Analytics for ETL/ELT
- Data transformation using Azure Databricks
- Working with structured and unstructured data
- Module 5: Designing and Developing Data Solutions
- Implementing batch and real-time data processing
- Managing data pipelines and orchestration
- Handling data partitioning and performance tuning
- Module 6: Securing and Monitoring Data Solutions
- Applying data security and governance
- Implementing data masking and encryption
- Monitoring and troubleshooting data pipelines
- Module 7: Performance Optimization and Cost Management
- Optimizing queries and storage performance
- Managing cost through data lifecycle policies
- Automating performance tuning and scaling
- Module 8: Preparing for the DP-203 Exam
- Review of key concepts and best practices
- Sample questions and hands-on exercises
- Exam tips and study strategies
Intended Audience
- Data Engineers
- Data Architects
- Business Intelligence (BI) Professionals
Prerequisites
- Basic understanding of cloud concepts and Azure services
- Experience with data processing languages such as SQL or Python
- Familiarity with core data concepts (relational and non-relational data)
Follow-On Courses
Related training topics
Justify your training
Use this sample request letter — copy it into an email to your manager and personalize the bracketed details to make the case for the time and budget.
Sample training request letter
Subject: Request for Data Analytics & Databases training from Applied Technology Academy
[Decision Maker Name],
I'm writing to request time and budget approval to complete Applied Technology Academy's course, Data Engineering on Microsoft Azure Training. The information below outlines how this training benefits our organization, the tasks I'll be able to perform after completing it, and relevant cost and funding details.
Course Description
This course equips participants with the knowledge and skills to design and build secure, scalable, and efficient data processing solutions on Microsoft Azure. Students will learn how to integrate, transform, and consolidate data from various structured and unstructured sources into a format suitable for analytics. The course also covers implementing data storage, managing data pipelines, and optimizing data solutions for performance and cost. Applied Technology Academy is an award-winning, SBA-certified woman-owned training provider (est. 2008) whose instructors are active practitioners; the course is hands-on with virtual labs and a learn-by-doing methodology.
Course Objectives
Once I've completed the course, I'll have hands-on, job-ready skills in data analytics & databases that I can apply immediately to our work.
Expected Organizational Benefits
After completing this course, I will be better equipped to apply these skills directly to our projects, reduce our reliance on outside expertise, strengthen our team's capabilities, and share what I learn with colleagues.
Expected Cost & Funding
Course fee: [request an itemized quote at the link below]. Applied Technology Academy supports multiple funding paths that may reduce or cover this cost: GSA MAS purchasing and government purchase orders, military credentialing funding (Army CA, AF COOL, CG COOL), VA GI Bill and VR&E, ATA Flexible Spending, and student financing. Private team cohorts are available if colleagues should attend with me.
Conclusion
This training provides practical, hands-on experience I can apply immediately to strengthen our work in data analytics & databases. Additional course information is available at https://appliedtechnologyacademy.com/microsoft-training/data-engineering-on-microsoft-azure-training/.
Thank you for your consideration,
[Your Name]
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