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 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?
- Azure Synapse Analytics serverless SQL pool querying data stored in Geo-Redundant Storage (GRS)Cevap
- BAzure Synapse Analytics dedicated SQL pool querying data stored in Locally Redundant Storage (LRS)
- CAzure Cosmos DB using a low-cardinality partition key to store and query the transaction logs
- DAzure SQL Database Serverless querying data with external tables using a multi-year Shared Access Signature (SAS) token configured without a stored access policy
Cevap
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.
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Anahtar Kavram
Selecting the appropriate Azure Synapse query model and storage redundancy level for ad-hoc analytical workloads.
Tahmini Süre:1m 30s