Data Engineering on Microsoft Azure (DP-203)
Training at a glance
Level
Intermediate
Duration
4 Days
Experience
1 year: Microsoft
Average Salary
$155,000
Labs
Yes
Training Details
- 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)
- 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
- Data Engineers
- Data Architects
- Business Intelligence (BI) Professionals
- 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)
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