One such certification that enables specialists to create some of the greatest analytics solutions using the Microsoft Azure platform is the Data Engineering on DP-203 Microsoft to Azure certification.
The Microsoft Azure DP-203 exam, titled “Data Engineering on Microsoft Azure,” covers topics like designing and implementing data storage solutions, developing data processing pipelines using various Azure services (including Azure Data Factory, Azure Synapse Analytics, Azure Stream Analytics, Azure Databricks), securing and optimizing data storage and processing, and managing data ingestion, transformation, and batch/stream processing across different Azure data services, with a focus on practical application and scenario-based questions.
Key areas covered in DP-203:
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Data Storage Design and Implementation:
- Partitioning strategies for different data types and workloads
- Data exploration layer design
- Choosing appropriate storage options based on data characteristics (Azure Data Lake Storage Gen2, Azure Blob Storage)
- Partitioning strategies for different data types and workloads
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Data Processing Development:
- Ingestion and transformation of batch and streaming data
- Building data pipelines with Azure Data Factory
- Utilizing Azure Synapse Analytics for data warehousing and transformation
- Implementing data processing with Apache Spark on Azure Databricks
- Stream processing with Azure Stream Analytics
- Ingestion and transformation of batch and streaming data
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Security, Monitoring, and Optimization:
- Implementing data security measures
- Monitoring data pipelines and performance optimization
- Troubleshooting data processing issues
- Data lineage tracking
- Implementing data security measures
Important skills required for DP-203:
- Proficiency in SQL and at least one programming language like Python or Scala
- Understanding of data warehousing concepts
- Knowledge of data architecture patterns
- Familiarity with distributed processing frameworks like Apache Spark
- Experience with Azure data services like Azure Data Lake Storage, Azure Synapse Analytics, Azure Stream Analytics, and Azure Databricks
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