DP-201: Designing an Azure Data Solution

DP-201: Designing an Azure Data Solution is part of the requirements for the Microsoft Certified: Azure Data Engineer Associate

Exam requirements

The official exam document are published here: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-201

Exam preparation

Books covering the exam

Video training for the exam

Microsoft Partner Network

• DP-200: Implementing an Azure Data Solution
  https://partner.microsoft.com/en-us/training/assets/collection/dp-200-implementing-an-azure-data-solution#/
• DP-201: Designing an Azure Data Solution
  https://partner.microsoft.com/en-us/training/assets/collection/dp-201-designing-an-azure-data-solution#/

PluralSight

• Microsoft Azure Data Engineer (DP-200)
  https://app.pluralsight.com/paths/certificate/microsoft-azure-data-engineer-dp-200
• Azure Data Solution (DP-201)
  https://app.pluralsight.com/paths/certificate/azure-data-solution-dp-201

SQLBits

• XVIII (2019) Conference
  https://sqlbits.com/content/Event18?type=3

Online training

Microsoft Learn (free)

• Azure Fundamentals
  https://docs.microsoft.com/en-us/learn/paths/azure-fundamentals/
• Azure for the Data Engineer
  https://docs.microsoft.com/en-us/learn/paths/azure-for-the-data-engineer/
• Store data in Azure
  https://docs.microsoft.com/en-us/learn/paths/store-data-in-azure/
• Work with relational data in Azure
  https://docs.microsoft.com/en-us/learn/paths/work-with-relational-data-in-azure/
• Work with NoSQL data in Azure Cosmos DB
  https://docs.microsoft.com/en-us/learn/paths/work-with-nosql-data-in-azure-cosmos-db/
• Large-Scale Data Processing with Azure Data Lake Storage Gen2
  https://docs.microsoft.com/en-us/learn/paths/data-processing-with-azure-adls/
• Implement a Data Streaming Solution with Azure Streaming Analytics
  https://docs.microsoft.com/en-us/learn/paths/implement-data-streaming-with-asa/
• Implement a Data Warehouse with Azure Synapse Analytics
  https://docs.microsoft.com/en-us/learn/paths/implement-sql-data-warehouse/

• Data engineering with Azure Databricks
  https://docs.microsoft.com/en-us/learn/paths/data-engineer-azure-databricks/
• Perform data science with Azure Databricks
  https://docs.microsoft.com/en-us/learn/paths/perform-data-science-azure-databricks/

Instructor-led training

Microsoft Learning Partner

• Course DP-200T01-A: Implementing an Azure Data Solution
  https://docs.microsoft.com/en-us/learn/certifications/courses/dp-200t01
• Course DP-201T01-A: Designing an Azure Data Solution
  https://docs.microsoft.com/en-us/learn/certifications/courses/dp-201t01

Exam Objectives

Design Azure Data Storage Solutions (40-45%)

• Recommend an Azure data storage solution based on requirements
  • Choose the correct data storage solution to meet the technical and business requirements
    https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview
    https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage
  • Choose the partition distribution type
    https://docs.microsoft.com/en-us/azure/architecture/best-practices/data-partitioning-strategies
    https://docs.microsoft.com/en-us/azure/architecture/best-practices/data-partitioning
• Design non-relational cloud data stores
  • Design data distribution and partitions
    https://docs.microsoft.com/en-us/azure/cosmos-db/partition-data
    https://docs.microsoft.com/en-us/azure/cosmos-db/global-dist-under-the-hood
  • Design for scale (including multi-region, latency, and throughput)
    https://docs.microsoft.com/en-us/azure/cosmos-db/set-throughput
    https://docs.microsoft.com/en-us/azure/cosmos-db/partition-data
  • Design a solution that uses Cosmos DB, Data Lake Storage Gen2, or Blob storage
    https://docs.microsoft.com/en-us/azure/cosmos-db/social-media-apps
    https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-static-website-how-to
  • Select the appropriate Cosmos DB API
    https://docs.microsoft.com/en-us/learn/modules/choose-api-for-cosmos-db/
  • Design a disaster recovery strategy
    https://docs.microsoft.com/en-us/azure/cosmos-db/how-to-backup-and-restore
  • Design for high availability
    https://docs.microsoft.com/en-us/azure/cosmos-db/high-availability
• Design relational cloud data stores
  • Design data distribution and partitions
    https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
    
  • Design for scale (including multi-region, latency, and throughput)
    https://docs.microsoft.com/en-us/azure/cosmos-db/scaling-throughput
    https://docs.microsoft.com/en-us/azure/cosmos-db/optimize-cost-throughput
    https://docs.microsoft.com/bs-latn-ba/azure/cosmos-db/consistency-levels-tradeoffs
  • Design a solution that uses SQL Database and Azure Synapse Analytics (SQL Data Warehouse)
  • Design a disaster recovery strategy
    https://docs.microsoft.com/en-us/azure/azure-sql/database/active-geo-replication-overview
    https://docs.microsoft.com/en-us/azure/azure-sql/database/disaster-recovery-guidance
    https://docs.microsoft.com/en-us/azure/azure-sql/virtual-machines/windows/business-continuity-high-availability-disaster-recovery-hadr-overview
  • Design for high availability
    https://docs.microsoft.com/en-us/azure/azure-sql/database/high-availability-sla

Design Data Processing Solutions (25-30%)

• Design batch processing solutions
  • Design batch processing solutions that use Data Factory and Azure Databricks
    https://www.youtube.com/watch?v=0PjSYaV85t0
    
  • Identify the optimal data ingestion method for a batch processing solution
    https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing#technology-choices-for-batch-processing
    https://docs.microsoft.com/en-us/azure/data-explorer/ingest-data-overview#choosing-the-most-appropriate-ingestion-method
  • Identify where processing should take place, such as at the source, at the destination, or in transit
  • Identify transformation logic to be used in the Mapping Data Flow in Azure Data Factory
• Design real-time processing solutions
  • Design for real-time processing by using Stream Analytics and Azure Databricks
    https://docs.microsoft.com/en-us/azure/azure-databricks/databricks-stream-from-eventhubs
    https://docs.microsoft.com/en-us/azure/architecture/reference-architectures/data/stream-processing-databricks
    
  • Design and provision compute resources
    https://docs.microsoft.com/en-us/azure/batch/batch-pool-vm-sizes

Design for Data Security and Compliance (25-30%)

• Design security for source data access
  • Plan for secure endpoints (private/public)
    https://docs.microsoft.com/en-us/azure/storage/common/storage-private-endpoints
  • Choose the appropriate authentication mechanism, such as access keys, shared access signatures (SAS), and Azure Active Directory (Azure AD)
    https://docs.microsoft.com/en-us/azure/storage/common/storage-auth-aad
    https://docs.microsoft.com/en-us/azure/storage/common/storage-sas-overview
    https://docs.microsoft.com/en-us/azure/storage/common/storage-account-manage#access-keys
    https://docs.microsoft.com/en-us/azure/sql-database/sql-database-control-access
    https://docs.microsoft.com/en-us/azure/sql-database/sql-database-manage-logins
    https://docs.microsoft.com/en-us/azure/sql-database/sql-database-aad-authentication
• Design security for data policies and standards
  • Design data encryption for data at rest and in transit
    https://docs.microsoft.com/en-us/azure/security/fundamentals/encryption-overview#encryption-of-data-at-rest
    https://docs.microsoft.com/en-us/azure/security/fundamentals/encryption-overview#encryption-of-data-in-transit
    
  • Design for data auditing and data masking
    https://docs.microsoft.com/en-us/azure/sql-database/sql-database-auditing
    https://docs.microsoft.com/en-us/azure/sql-database/sql-database-dynamic-data-masking-get-started
  • Design for data privacy and data classification
    https://docs.microsoft.com/en-us/azure/security/fundamentals/protection-customer-data
    https://docs.microsoft.com/en-us/azure/information-protection/deploy-aip-scanner
  • Design a data retention policy
    https://docs.microsoft.com/en-us/azure/sql-database/sql-database-long-term-backup-retention-configure
  • Plan an archiving strategy
    https://azure.microsoft.com/en-us/solutions/architecture/backup-archive-on-premises/
    https://azure.microsoft.com/en-us/blog/announcing-the-public-preview-of-azure-archive-blob-storage-and-blob-level-tiering/
    https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers#archive-access-tier
  • Plan to purge data based on business requirements
    https://docs.microsoft.com/en-us/azure/storage/blobs/storage-lifecycle-management-concepts?tabs=azure-portal