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Difficulty: Very hardData Integration and Analytical Storage

A company is designing a data analytics solution on Azure to support a team of data scientists who perform infrequent, ad-hoc exploratory queries on a 50 TB50\text{ TB} dataset stored in Azure Data Lake Storage Gen2. New data is loaded in batches every 6 hours6\text{ hours}, adding approximately 500 GB500\text{ GB} daily. The exploratory queries must execute within 30 seconds30\text{ seconds}. The entire architecture must remain resilient to a regional disaster, ensuring that both data and analytical query capabilities can be restored or accessed in a secondary region. Additionally, all access to the data lake must be secure, easily revocable, and audit-compliant, avoiding long-lived static credentials. You need to design the solution while minimizing operational overhead and idle resource costs. Which storage and analytical query configuration should you recommend?

  1. A
    A dedicated SQL pool in Azure Synapse Analytics querying Azure Data Lake Storage Gen2 configured with Geo-Redundant Storage (GRS), using Microsoft Entra ID integration for authentication.
  2. B
    Azure Synapse Analytics serverless SQL pools querying Azure Data Lake Storage Gen2 configured with Locally Redundant Storage (LRS), using Microsoft Entra ID integration for authentication.
  3. Azure Synapse Analytics serverless SQL pools querying Azure Data Lake Storage Gen2 configured with Geo-Redundant Storage (GRS), using Microsoft Entra ID integration for authentication.Answer
  4. D
    Azure Synapse Analytics serverless SQL pools querying Azure Data Lake Storage Gen2 configured with Geo-Redundant Storage (GRS), using ad-hoc Shared Access Signature (SAS) tokens with a five-year expiration date embedded in the connection configuration.

Answer

The configuration using Azure Synapse Analytics serverless SQL pools querying Azure Data Lake Storage Gen2 configured with Geo-Redundant Storage (GRS), using Microsoft Entra ID integration for authentication.
The configuration using serverless SQL pools with Geo-Redundant Storage (GRS) and Microsoft Entra ID meets all requirements. Serverless SQL pools provide an on-demand query engine that charges only for data processed, minimizing costs for infrequent ad-hoc queries. GRS ensures data is replicated to a secondary region to survive regional outages. Microsoft Entra ID integration ensures secure, identity-based access control without key management overhead.

Step-by-Step Solution

1
Analyze the query frequency and cost tradeoffs.
The requirement specifies infrequent, ad-hoc queries. Dedicated resources (Dedicated SQL Pool) incur continuous idle costs, whereas serverless SQL pools charge per TB of data processed, aligning cost directly with usage.
To minimize idle resource costs and operational overhead.
2
Determine the storage redundancy model based on disaster recovery requirements.
Locally Redundant Storage (LRS) is restricted to a single region. Geo-Redundant Storage (GRS) replicates data asynchronously to a secondary region, ensuring disaster resilience.
To satisfy the requirement that the architecture must survive a regional outage.
3
Evaluate the authentication mechanism against security policies.
Microsoft Entra ID provides identity-based, auditable access control that is easily revocable. Long-lived SAS tokens represent a security vulnerability because they are static and hard to revoke.
To ensure audit compliance and avoid static long-lived credentials.

Key Concept

Selecting analytical query engines and storage redundancy configurations to balance disaster recovery, security compliance, and consumption-based cost models.
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Topics

Data Integration and Analytical Storage

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