Question

Difficulty: MediumData Integration and Analytical Storage

A logistics provider is designing a telemetry analysis platform on Azure. The solution must meet the following requirements:
- Maintain regional disaster resilience for all ingested telemetry data.
- Allow data scientists to perform ad-hoc, exploratory queries on raw CSV telemetry log files without incurring ongoing costs for idle compute resources.

Which two design choices should you include in the storage and analytics architecture? (Select TWO.)

  1. Configure the telemetry storage account as Geo-Redundant Storage (GRS).Answer
  2. Use Azure Synapse Analytics serverless SQL pools to query the CSV files.Answer
  3. C
    Configure the telemetry storage account as Locally Redundant Storage (LRS).
  4. D
    Provision an Azure Synapse dedicated SQL pool to query the CSV files.

Answer

Configuring the storage account as Geo-Redundant Storage (GRS) and using Azure Synapse Analytics serverless SQL pools to query the CSV files.
Configuring the storage account as Geo-Redundant Storage (GRS) satisfies the requirement for regional disaster resilience by replicating data across regions. Using Azure Synapse Analytics serverless SQL pools meets the requirement for ad-hoc, exploratory queries on CSV files without ongoing costs because it uses a pay-per-query model and does not require provisioned compute infrastructure.

Step-by-Step Solution

1
Evaluate the storage redundancy options for regional resilience.
Geo-Redundant Storage (GRS) is selected.
Locally Redundant Storage (LRS) does not protect against a regional outage, whereas GRS replicates data to a secondary region.
2
Evaluate the query options for ad-hoc exploratory queries on CSV files.
Azure Synapse Analytics serverless SQL pools are selected.
Serverless SQL pools query files in-place and charge only per query, avoiding the costs of idle provisioned dedicated SQL pools.

Key Concept

Selecting cost-effective analytical query capabilities and disaster-resilient storage tiers in Azure Synapse and Azure Data Lake Storage.
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