DP-203: Data Engineering on Microsoft Azure Practice Exam

Azure Data Engineer: Master Data Pipelines and Data Warehousing

Become a proficient Azure Data Engineer and unlock the power of data! This comprehensive course equips you with the skills to design, build, and maintain robust, scalable, and secure data pipelines and data solutions on the Azure platform. Learn to manage the entire data lifecycle, from data ingestion and data processing to data storage and analysis.

Key Skills You'll Develop:

• Data Storage Design & Implementation: Master various data storage solutions, including modern data warehouse (MDW), big data architectures, and Lakehouse architectures. Learn to implement effective partition strategies for Azure Data Lake Storage Gen2 across different workloads (batch, streaming, analytical).
• Data Processing Expertise: Develop advanced data processing skills using tools like Apache Spark, Azure Synapse Analytics, Azure Data Factory, and Azure Stream Analytics. Learn to ingest and transform data using T-SQL (Transact-SQL), Spark, and Azure Synapse Pipelines.
• Data Security & Optimization: Implement comprehensive data security measures, including data masking, encryption at rest and in motion, role-based access control (RBAC), and POSIX-like ACLs. Focus on optimizing data storage and data processing for performance, efficiency, and cost-effectiveness.
• Data Pipeline Development: Design and implement both batch processing and stream processing solutions. Learn to handle schema drift, windowed aggregates, and time series data. Develop skills in data quality management, including handling duplicate data, missing data, and late-arriving data.
• Data Governance & Metadata Management: Utilize Microsoft Purview to manage data lineage and browse/search metadata within the Data Catalog.
• Pipeline Orchestration & Automation: Develop and manage data pipelines using Azure Data Factory and Azure Synapse Pipelines. Implement version control for pipeline artifacts and automate pipeline scheduling.

Core Topics Covered:

• Data Ingestion: Connect to diverse data sources and ingest data into Azure.
• Data Transformation: Cleanse, transform, and enrich data using various techniques.
• Data Storage: Design and implement data storage solutions in Azure, including Azure Data Lake Storage Gen2, Azure Synapse Analytics, and more.
• Data Pipelines: Build and manage robust data pipelines for batch and stream processing.
• Data Security: Implement security best practices to protect sensitive data.
• Data Monitoring & Optimization: Monitor pipeline performance, troubleshoot issues, and optimize resource utilization.
• Delta Lake: Develop solutions leveraging Delta Lake for reliable data lakes.
• Azure Synapse Analytics: Utilize Azure Synapse Analytics for data warehousing and big data analytics.
• Azure Event Hubs & Stream Analytics: Build real-time data processing pipelines.

Exam Preparation:

This course prepares you for the Azure Data Engineer Associate (DP-203) certification exam. The exam features a variety of question formats, including hotspots, use cases, multiple-choice, and drag-and-drop. Practice tests provide hands-on experience and detailed explanations to help you master the exam content. A strong understanding of data processing languages and data architecture patterns is essential for success. The exam duration is approximately 100 minutes with 40-52 questions.

Ideal for: Data engineers, data architects, and anyone seeking to validate their skills in building and managing data solutions on Azure.