An educational technology company is designing a data integration and analytics platform to process student learning platform telemetry. The platform must meet the following requirements:
- Store and analyze 12 TB of historical student activity logs currently formatted as Parquet files.
- Ingest new telemetry logs as Parquet files at a rate of 15 GB per hour.
- Support ad-hoc exploratory queries using standard T-SQL with a target latency of under 10 seconds.
- Maintain data availability even in the event of a primary Azure region failure.
- Minimize administrative and compute costs associated with the ad-hoc queries.
- Provide secure access to external research partners that can be easily revoked.
Which two actions should you recommend?
- Configure the Azure Data Lake Storage Gen2 account to use Geo-Redundant Storage (GRS).Cevap
- Use Azure Synapse Analytics serverless SQL pools to execute T-SQL queries directly on the Parquet files.Cevap
- CProvision an Azure Synapse dedicated SQL pool to import and query the Parquet files.
- DConfigure the Azure Data Lake Storage Gen2 account to use Locally Redundant Storage (LRS).
- ECreate a Shared Access Signature (SAS) token with a five-year expiration time to provide direct access for external analysts.
Cevap
Configure the Azure Data Lake Storage Gen2 account to use Geo-Redundant Storage (GRS) and use Azure Synapse Analytics serverless SQL pools to execute T-SQL queries directly on the Parquet files.
Configuring the Azure Data Lake Storage Gen2 account to use Geo-Redundant Storage (GRS) satisfies the requirement to survive a regional outage, and using serverless SQL pools enables querying the data directly in the lake using T-SQL while minimizing compute costs and administrative overhead.
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Anahtar Kavram
Selecting appropriate analytical query services and storage redundancy models based on cost, performance, and availability constraints.