A healthcare provider is designing an analytical data platform to analyze telemetry from patient monitoring devices. The platform must meet the following requirements:
- Ingest telemetry data at a rate of events per second.
- Store raw events in Azure Data Lake Storage (ADLS) Gen2 in JSON format, with an expected annual volume of .
- Enable analysts to perform ad-hoc, exploratory queries on the raw JSON data with a latency of less than .
- Provide regional disaster resilience for the stored data.
- Minimize administrative overhead and run-time costs.
Which two configurations should you include in the design? (Select two.)
- Configure the ADLS Gen2 storage account to use Geo-redundant storage (GRS).Answer
- Use Azure Synapse Analytics serverless SQL pools to query the raw JSON files in the data lake.Answer
- CProvision an Azure Synapse dedicated SQL pool to load and query the raw JSON files.
- DConfigure the ADLS Gen2 storage account to use Locally redundant storage (LRS).
- EGenerate a Shared Access Signature (SAS) token with a 5-year lifetime to authorize analysts' ad-hoc query tools.
Answer
To satisfy the requirements, the storage account must be configured to use Geo-redundant storage (GRS) for regional disaster resilience, and Azure Synapse Analytics serverless SQL pools must be used to perform ad-hoc queries on the raw JSON files stored in ADLS Gen2.
Geo-redundant storage (GRS) provides the required regional disaster resilience by asynchronously replicating data to a secondary region. Azure Synapse Analytics serverless SQL pools provide an on-demand, serverless query engine to run ad-hoc queries directly on the JSON files stored in ADLS Gen2, minimizing administrative overhead and costs since you only pay for queries executed.
Step-by-Step Solution
Key Concept
Designing an analytical architecture using Azure Synapse serverless SQL pools for ad-hoc data lake queries and ADLS Gen2 with Geo-redundant storage (GRS) for disaster recovery.