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Difficulty: MediumData Integration and Analytical Storage

A media company stores user activity logs in Azure Data Lake Storage (ADLS) Gen2 in CSV format. You need to design an analytical solution to meet the following requirements:
- Storage Volume: 8 TB8 \text{ TB} of historical CSV log files.
- Ingestion Velocity: Logs are uploaded hourly at a rate of 5 GB5 \text{ GB} per hour.
- Query Pattern: Data analysts perform ad-hoc, exploratory queries intermittently to identify user trends.
- Query Latency: Response times of up to 6060 seconds are acceptable.
- Resiliency: The analytical data must survive a primary datacenter outage within the region.
- Cost: Minimize compute cost when no queries are running.

Which combination of storage redundancy and query engine should you configure?

  1. Configure ADLS Gen2 with Geo-Redundant Storage (GRS) and use Azure Synapse Analytics Serverless SQL pools to query the CSV files.Answer
  2. B
    Configure ADLS Gen2 with Locally Redundant Storage (LRS) and use Azure Synapse Analytics Serverless SQL pools to query the CSV files.
  3. C
    Configure ADLS Gen2 with Geo-Redundant Storage (GRS) and load the logs into an Azure Synapse Dedicated SQL Pool for analysis.
  4. D
    Configure ADLS Gen2 with Geo-Redundant Storage (GRS), grant analyst access using an ad-hoc Shared Access Signature (SAS) token with a 55-year lifetime, and use Azure Synapse Analytics Serverless SQL pools.

Answer

Configure ADLS Gen2 with Geo-Redundant Storage (GRS) and use Azure Synapse Analytics Serverless SQL pools to query the CSV files.
The correct solution uses Geo-Redundant Storage (GRS) to ensure that the data survives a primary datacenter outage, and queries the CSV files directly using Azure Synapse Serverless SQL pools. Serverless SQL pools charge only for data processed per query, making them highly cost-effective for ad-hoc, intermittent query patterns on files stored in a data lake.

Step-by-Step Solution

1
Determine the appropriate query model based on query patterns and cost constraints.
Since the queries are ad-hoc, intermittent, and performed on CSV files in a data lake, Azure Synapse Serverless SQL pools are selected to minimize compute costs via pay-per-query pricing.
Dedicated SQL pools incur ongoing provisioned compute costs even when idle, which violates the requirement to minimize costs during periods of inactivity.
2
Evaluate the resiliency requirements for the underlying storage.
Select Geo-Redundant Storage (GRS) for Azure Data Lake Storage Gen2.
Locally Redundant Storage (LRS) only replicates data within a single datacenter, failing the requirement to survive a primary datacenter outage.
3
Ensure secure access configuration.
Avoid long-lived Shared Access Signature (SAS) tokens without stored access policies.
Ad-hoc SAS tokens with long lifetimes cannot be revoked easily, presenting a significant security risk.

Key Concept

Selecting the optimal Azure Synapse query model (Serverless vs. Dedicated) and storage redundancy based on cost, latency, and resiliency requirements.
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Topics

Data Integration and Analytical Storage

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