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Difficulty: MediumData Integration and Analytical Storage

An online streaming media platform needs to analyze user engagement metrics collected from smart TV applications. The platform logs are continuously ingested into Azure Data Lake Storage (ADLS) Gen2 in Parquet format. Analysts need to run ad-hoc exploratory queries to investigate user behavior patterns over the past 24 hours. The platform must minimize operational overhead and avoid paying for idle compute resources, as these ad-hoc queries are unpredictable and infrequent. Which analytical query solution should you recommend to meet these requirements?

  1. Azure Synapse Analytics serverless SQL pools querying the Parquet files directly in Azure Data Lake Storage Gen2Answer
  2. B
    Azure Synapse Analytics dedicated SQL pools with tables loading the Parquet files via PolyBase
  3. C
    Azure Data Lake Storage Gen2 configured with Locally Redundant Storage (LRS) to survive regional outages, queried using Azure Synapse Analytics
  4. D
    Azure Data Lake Storage Gen2 with files immediately moved to the Archive tier to minimize costs, queried using Azure Synapse Analytics

Answer

Azure Synapse Analytics serverless SQL pools querying the Parquet files directly in Azure Data Lake Storage Gen2
Using Azure Synapse Analytics serverless SQL pools to query Parquet files directly in Azure Data Lake Storage Gen2 is the most cost-effective and low-overhead solution. It uses a pay-per-query model, which avoids costs for idle resources during periods with no ad-hoc query activity.

Step-by-Step Solution

1
Analyze the operational and resource requirements of the scenario.
Identified that queries are ad-hoc, unpredictable, infrequent, and require minimizing costs for idle compute.
To determine the appropriate pricing model and compute tier.
2
Evaluate compute models in Azure Synapse Analytics.
Serverless SQL pools charge per query based on data processed, while Dedicated SQL pools charge continuously for provisioned resources.
To choose between serverless and dedicated SQL pools based on cost efficiency.
3
Assess storage tier and redundancy requirements.
Archive tier data cannot be queried directly, and Locally Redundant Storage (LRS) does not survive regional outages.
To eliminate configurations that fail to meet retrieval latency and resiliency requirements.

Key Concept

Data Integration and Analytical Storage
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Topics

Data Integration and Analytical Storage

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