Hotspot Question You are designing a data pipeline that will integrate large amounts of data from multiple on- premises Microsoft SQL Server databases into an analytics platform in Azure. The…

Question

Exhibit

Answer Area

• To implement the data warehouse:An Azure Synapse Analytics dedicated SQL pool
  An Apache Spark pool in Azure Synapse AnalyticsAn Azure Synapse Analytics dedicated SQL poolAzure Data Lake Analytics
• To implement the serving layer:Azure Analysis Services
  Azure Analysis ServicesAn Apache Spark pool Azure Synapse AnalyticsAn Azure Synapse Analytics dedicated SQL pool

Explanation

This question tests your ability to select the correct Azure services for a data warehouse layer and a managed OLAP serving layer in a large-scale analytics pipeline.

Approach. For the data warehouse layer, Azure Synapse Analytics (formerly SQL Data Warehouse) is the correct choice because it supports massively parallel processing (MPP) for large-scale data ingestion and querying, integrates natively with Azure Blob Storage, and is purpose-built for enterprise data warehousing. For the managed serving layer (OLAP model refreshed per batch and used by thousands of end users), Azure Analysis Services is the correct choice because it provides a fully managed, enterprise-grade OLAP/tabular model serving layer that supports large concurrent user loads, semantic modeling, and can be refreshed programmatically after each batch load from the data warehouse.

Concept tested. Selecting appropriate Azure services for each layer in a modern data warehouse architecture: Azure Synapse Analytics for the scalable data warehouse (MPP engine) and Azure Analysis Services for the managed OLAP/semantic serving layer supporting high concurrency end-user queries.

Reference. https://learn.microsoft.com/en-us/azure/architecture/solution-ideas/articles/enterprise-data-warehouse

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