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Difficulty: MediumData Integration and Analytical Storage

A retail chain is designing a data analytics solution to analyze customer purchase history logs. The logs are uploaded nightly as CSV files to Azure Storage and total approximately 10 GB10\text{ GB} per day. The data analysts require the ability to run ad-hoc T-SQL queries directly against these CSV files to identify shopping trends. The queries are run infrequently, primarily during business hours. The solution must minimize operational overhead, avoid costs for idle compute resources, and ensure the storage tier survives a primary datacenter outage.

Which of the following database and storage configurations should you recommend?

  1. Azure Synapse Analytics serverless SQL pool querying data stored in Geo-Redundant Storage (GRS)Answer
  2. B
    Azure Synapse Analytics dedicated SQL pool querying data stored in Locally Redundant Storage (LRS)
  3. C
    Azure Cosmos DB using a low-cardinality partition key to store and query the transaction logs
  4. D
    Azure SQL Database Serverless querying data with external tables using a multi-year Shared Access Signature (SAS) token configured without a stored access policy

Answer

Azure Synapse Analytics serverless SQL pool querying data stored in Geo-Redundant Storage (GRS)
A serverless SQL pool in Azure Synapse Analytics is the ideal cost-effective choice for ad-hoc exploration of CSV files in storage, as users are billed only for data processed and there is no active cluster footprint or idle compute cost. Geo-Redundant Storage (GRS) provides durability against a primary datacenter outage by replicating the data to a secondary region.

Step-by-Step Solution

1
Analyze the query and resource requirements
Infrequent ad-hoc queries against CSV files with zero idle compute costs require a serverless query engine such as Synapse serverless SQL pools.
Dedicated compute models incur ongoing execution costs when no queries are running, whereas serverless models only bill per TB of data processed.
2
Analyze the resiliency requirements
Survival of a primary datacenter outage requires geo-replication.
Locally Redundant Storage (LRS) is confined to a single datacenter, so Geo-Redundant Storage (GRS) is required to ensure data survivability in another region.
3
Combine query and resiliency components to form the optimal recommendation
Azure Synapse Analytics serverless SQL pool combined with Geo-Redundant Storage (GRS).
This configuration meets all requirements for query format, cost efficiency, low operational overhead, and regional resilience.

Key Concept

Selecting the appropriate Azure Synapse query model and storage redundancy level for ad-hoc analytical workloads.
Estimated Time:1m 30s
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Topics

Data Integration and Analytical Storage

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