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Microsoft

Microsoft Certified: Azure Data Engineer Associate

The DP-203 certification by Microsoft validates expertise in data engineering on Azure.

Código de examen

DP-203

Requisitos previos oficiales

  • Basic understanding of data engineering concepts, including ETL/ELT, data modeling, and data storage
  • Proficiency in SQL and at least one programming language used for data processing (Python, Scala)
  • Hands-on experience with cloud platforms and Azure services (Azure Storage, Azure SQL Database)
  • Familiarity with big data processing and frameworks such as Apache Spark and distributed processing
  • Experience building and monitoring data pipelines; knowledge of performance tuning and security best practices
Microsoft Certified: Azure Data Engineer Associate

Profesiones específicas

Data Engineer Azure Data Engineer ETL Developer Big Data Engineer Data Platform Engineer
Artículos relacionados

Plano de dominio

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This domain involves designing and implementing the management, monitoring, security, and privacy of data using the full stack of Azure data services to satisfy business needs.
Focuses on designing and developing processing solutions to load and transform data using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.
Covers implementation of data security policies, securing sensitive data, and configuring security solutions in Azure using tools like Azure Key Vault and Azure Active Directory.
Concentrates on the configuration and management of monitoring tools to improve processing and storage performance in Azure data services.
Design and implement efficient and scalable storage solutions including partitioning strategies, logical and physical structures, data lakes and analytical layers to support exploration and analytics workloads on Azure services such as Data Lake Storage Gen2 and Synapse Analytics.

Dominio 5

Design and implement data storage

Design and implement efficient and scalable storage solutions including partitioning strategies, logical and physical structures, data lakes and analytical layers to support exploration and analytics workloads on Azure services such as Data Lake Storage Gen2 and Synapse Analytics.

Dominio 6

Develop data processing

Ingest, transform, batch and stream process data using tools like Azure Data Factory, Databricks, Synapse, Event Hubs, and Stream Analytics; handle schema drift, late-arriving, duplicated or missing data; manage pipelines and batch orchestration.

Dominio 7

Secure, monitor, and optimize data storage and data processing

Implement security controls like encryption, masking, RBAC, row‐ and column-level security; monitor pipelines, queries, storage and stream processing using Azure Monitor and related services; optimize performance, resource usage and troubleshoot storage and processing issues.

Consejo de estudio

Hands-on practice with Azure Data Factory, Synapse, Databricks, and SQL; review the DP-203 skills outline, complete timed practice exams and labs.

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