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Difficulty: EasyData Integration and Analytical Storage

A company stores transaction log files in an Azure Data Lake Storage Gen2 account. You need to design an analytical query solution that allows data analysts to perform ad-hoc SQL queries directly on these files with minimal operational overhead. The data must remain available even if the primary Azure region suffers a datacenter outage. Which two configurations should you include in the design? (Select TWO.)

  1. A
    Configure the storage account to use Locally Redundant Storage (LRS).
  2. Configure the storage account to use Geo-redundant storage (GRS).Answer
  3. C
    Provision a dedicated SQL pool in Azure Synapse Analytics.
  4. Use a serverless SQL pool in Azure Synapse Analytics.Answer
  5. E
    Generate long-lived Shared Access Signatures (SAS) with a lifetime of one year directly on the container URI.

Answer

Configure the storage account to use Geo-redundant storage (GRS) and use a serverless SQL pool in Azure Synapse Analytics.
The combination of a serverless SQL pool and Geo-redundant storage (GRS) meets all requirements. A serverless SQL pool enables ad-hoc queries directly on files in Azure Data Lake Storage with minimal operational overhead and cost, while GRS provides replication to a secondary region to protect against datacenter outages.

Step-by-Step Solution

1
Analyze the query patterns and operational requirements.
The requirements specify ad-hoc queries directly on raw files with minimal operational overhead, which points to Azure Synapse Analytics serverless SQL pools.
Serverless SQL pools require no resource provisioning and charge only for processed data, avoiding the overhead of managing dedicated clusters.
2
Evaluate the resilience requirements for the storage account.
The solution must survive a primary region/datacenter outage, which requires replicating data to a paired region using Geo-redundant storage (GRS).
Locally Redundant Storage (LRS) is limited to a single datacenter and cannot survive regional outages.

Key Concept

Selecting the appropriate analytical query engines and storage redundancy levels based on operational overhead, cost, and availability requirements.
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Topics

Data Integration and Analytical Storage

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