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Difficulty: EasyData Integration and Analytical Storage

An organization stores 25 GB25\text{ GB} of sales log files in CSV format within an Azure Data Lake Storage Gen2 account. Data analysts need to run occasional, ad-hoc SQL queries against these files to inspect anomalies. You need to recommend an Azure Synapse Analytics query solution that minimizes costs by ensuring there are no ongoing compute charges when queries are not executing. Which resource type should you recommend?

  1. A
    Dedicated SQL pools
  2. Serverless SQL poolsAnswer
  3. C
    Locally Redundant Storage (LRS)
  4. D
    A long-lived Shared Access Signature (SAS) token

Answer

Serverless SQL pools
The correct option is Serverless SQL pools. They are specifically designed for ad-hoc, exploratory queries on files stored in Azure Storage. Since there are no provisioned resources, charges are based strictly on the volume of data processed by each query, resulting in zero costs during idle periods.

Step-by-Step Solution

1
Analyze the requirements for data querying and cost optimization.
The scenario requires querying CSV data in Azure Data Lake Storage Gen2 without paying for idle compute time.
This establishes the need for an on-demand, serverless query model instead of a provisioned database cluster.
2
Compare the cost models of the query options.
Serverless SQL pools charge only per TB of data processed, whereas dedicated SQL pools charge per hour of provisioned resources.
Choosing the serverless model ensures no ongoing costs are incurred when analysts are not running queries.

Key Concept

Selecting serverless vs dedicated analytics compute models in Azure Synapse
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Topics

Data Integration and Analytical Storage

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