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Zorluk: Çok zorData Integration and Analytical Storage

An enterprise is designing a new data analytics platform in Azure to process and analyze telemetry data from global manufacturing plants. The platform must meet the following requirements:
- Ingest raw telemetry data at an ingestion rate of up to 8 GB/sec8\text{ GB/sec} with sub-second ingestion latency, resulting in an expected daily volume of 150 TB150\text{ TB}.
- Store raw data in an Azure Data Lake Storage Gen2 (ADLS Gen2) account.
- Enable data analysts to perform exploratory ad-hoc queries on raw files (CSV and Parquet) with a target query latency of under 10 seconds10\text{ seconds} for small datasets, using a serverless model to minimize operational overhead and costs.
- Provide a persistent, centralized enterprise data warehouse for complex analytical queries on historical data (volume exceeding 5 PB5\text{ PB}), supporting clustered columnstore indexes and massive parallel processing (MPP) with sub-minute query latency.
- Ensure that both the storage and analytical layers survive a primary regional outage.
- Dynamically authorize access to raw files without exposing long-lived access keys or connection strings.

Which three solutions should you recommend to meet these requirements? (Select three.)

  1. Use Azure Synapse serverless SQL pools to perform ad-hoc exploratory queries on the raw Parquet and CSV files in ADLS Gen2.Cevap
  2. Deploy Azure Synapse dedicated SQL pools to serve as the enterprise data warehouse, configuring geo-redundant backups for regional disaster recovery.Cevap
  3. Implement Microsoft Entra ID authentication combined with Azure RBAC to secure access to the ADLS Gen2 storage account.Cevap
  4. D
    Provision a dedicated SQL pool in Azure Synapse Analytics to perform all ad-hoc, exploratory queries on the raw CSV files stored in ADLS Gen2.
  5. E
    Generate Shared Access Signature (SAS) tokens with a 12-month duration to provide analysts with direct access to the ADLS Gen2 storage container.
  6. F
    Configure the ADLS Gen2 storage account to use Locally Redundant Storage (LRS) to minimize cost while meeting regional disaster resilience requirements.

Cevap

Use Azure Synapse serverless SQL pools for ad-hoc exploratory queries, provision Azure Synapse dedicated SQL pools for the historical data warehouse with geo-redundant backups, and implement Microsoft Entra ID authentication with Azure RBAC to secure the ADLS Gen2 storage account.
To meet the requirements, serverless SQL pools in Azure Synapse Analytics should be used for ad-hoc, exploratory queries on ADLS Gen2 files, as they operate on a pay-per-query model without provisioned resources. Dedicated SQL pools should be used for the central historical data warehouse because they support large-scale relational schemas, clustered columnstore indexes, and massive parallel processing. Access should be secured via Microsoft Entra ID authentication and Azure RBAC to avoid using static, long-lived access keys or token credentials.

Adım Adım Çözüm

1
Evaluate the ingestion rate and data volume requirements to select storage.
Confirm Azure Data Lake Storage Gen2 (ADLS Gen2) can handle the 8 GB/sec8\text{ GB/sec} velocity and 150 TB150\text{ TB} daily volume when properly structured.
ADLS Gen2 is the standard analytical storage layer in Azure supporting hierarchical namespaces and high-throughput workloads.
2
Determine the query model for ad-hoc exploratory queries.
Select Azure Synapse serverless SQL pools to query Parquet and CSV files directly from ADLS Gen2.
This satisfies the requirement for ad-hoc exploratory queries with no persistent compute costs and a latency target of under 10 seconds10\text{ seconds} without provisioning dedicated resources.
3
Determine the query model for the historical enterprise data warehouse.
Select Azure Synapse dedicated SQL pools with geo-redundant backups.
This meets the requirement for a persistent relational data warehouse exceeding 5 PB5\text{ PB} with support for clustered columnstore indexes, MPP, and regional resilience.
4
Design the security model for ADLS Gen2 data access.
Use Microsoft Entra ID authentication and Azure RBAC.
This eliminates the need for long-lived shared access signatures or storage keys, providing dynamic, identity-based authorization.

Anahtar Kavram

Designing integrated Azure analytical storage and query solutions using serverless and dedicated resources with proper security and resiliency.
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Konular

Data Integration and Analytical Storage

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