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Microsoft Certified:Azure Data Engineer Associate

DP-203Azure Data Engineer Associate

The Microsoft Certified: Azure Data Engineer Associate certification validates your expertise in integrating, transforming, and consolidating data from various systems into a suitable schema for analytics solutions. It is designed for data engineers who build and maintain secure and compliant data processing pipelines using Azure services.

Practice Free Questions

367 practice questions · Updated 2023-10-01

3Domains
9Objectives
100Concepts
367Questions

DP-203 Curriculum

Every domain, objective, and concept the DP-203 exam measures.

Implement a partition strategy

5 concepts · 30 questions
  1. File Partition Strategy
  2. Analytical Workload Partitioning
  3. Streaming Workload Partitioning
  4. Azure Synapse Analytics Partitioning
  5. Partitioning Need Identification in ADLS Gen2

Design and implement the data exploration layer

7 concepts · 38 questions
  1. SQL Serverless Queries
  2. Spark Cluster Queries
  3. Azure Synapse Database Templates
  4. Implement Synapse Database Templates
  5. Data Lineage in Microsoft Purview
  6. Metadata Browsing in Purview
  7. Metadata Searching in Purview

Ingest and transform data

18 concepts · 57 questions
  1. Incremental Data Loads
  2. Apache Spark Transformation
  3. T-SQL Transformation in Synapse
  4. Azure Synapse Pipelines
  5. Azure Data Factory Transformation
  6. Azure Stream Analytics Transformation
  7. Data Cleansing
  8. Duplicate Data Handling
  9. Exactly Once Delivery
  10. Missing Data Handling
  11. Late-Arriving Data Handling
  12. Data Splitting
  13. JSON Shredding
  14. Data Encoding and Decoding
  15. Error Handling Configuration
  16. Data Normalization
  17. Data Denormalization
  18. Exploratory Data Analysis

Develop a batch processing solution

16 concepts · 42 questions
  1. Azure Data Lake Storage Gen2
  2. Azure Databricks
  3. Azure Synapse Analytics
  4. Azure Data Factory
  5. PolyBase SQL Pool Loading
  6. Azure Synapse Link
  7. Data Pipelines Creation
  8. Resource Scaling
  9. Batch Size Configuration
  10. Data Pipeline Testing
  11. Jupyter Notebook Integration
  12. Batch Data Upsert
  13. Data Reversion
  14. Exception Handling Configuration
  15. Batch Retention Configuration
  16. Delta Lake Operations

Develop a stream processing solution

16 concepts · 47 questions
  1. StreamAnalyticsSolution
  2. SparkStructuredStreaming
  3. WindowedAggregates
  4. SchemaDriftHandling
  5. TimeSeriesDataProcessing
  6. CrossPartitionProcessing
  7. SinglePartitionProcessing
  8. CheckpointsWatermarking
  9. ResourceScaling
  10. DataPipelineTesting
  11. PipelineOptimization
  12. InterruptionHandling
  13. ExceptionHandlingConfiguration
  14. StreamDataUpsert
  15. ArchivedStreamDataReplay
  16. DeltaLakeIntegration

Manage batches and pipelines

7 concepts · 32 questions
  1. Batch Triggering
  2. Failed Batch Handling
  3. Batch Load Validation
  4. Pipeline Management
  5. Pipeline Scheduling
  6. Pipeline Version Control
  7. Spark Job Management

Implement data security

13 concepts · 37 questions
  1. Data Masking
  2. Data Encryption at Rest
  3. Data Encryption in Motion
  4. Row-Level Security
  5. Column-Level Security
  6. Azure RBAC
  7. POSIX-like ACLs
  8. Data Retention Policy
  9. Secure Endpoints
  10. Resource Tokens in Azure Databricks
  11. Load DataFrame with Sensitive Information
  12. Write Encrypted Data
  13. Manage Sensitive Information

Monitor data storage and data processing

10 concepts · 46 questions
  1. Azure Monitor Logging
  2. Monitoring Service Configuration
  3. Stream Processing Monitoring
  4. Data Movement Performance Measurement
  5. System Data Statistics Monitoring
  6. Data Pipeline Performance Monitoring
  7. Query Performance Measurement
  8. Pipeline Test Scheduling and Monitoring
  9. Azure Monitor Metrics and Logs Interpretation
  10. Pipeline Alert Strategy Implementation

Optimize and troubleshoot data storage and data processing

8 concepts · 38 questions
  1. File Compaction
  2. Data Skew Management
  3. Data Spill Prevention
  4. Resource Management Optimization
  5. Query Indexing
  6. Query Caching
  7. Spark Job Troubleshooting
  8. Pipeline Run Troubleshooting
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Practice Free Questions

Percentages reflect share of the current practice bank, not official exam weightings — no structured per-skill weight is published for DP-203, so none is invented.