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Microsoft Certified: Azure Solutions Architect Expert · Microsoft
Step Sequence / Reordering Question
Add and arrange the steps in the correct execution order.
Hotspot Solution:
Data store for the ingested data: Azure Data Lake Storage Gen2 This is the best fit because it organizes data in a hierarchical directory structure (so you can organize by date and time), handles high-volume JSON ingestion from Event Hubs natively, and supports querying data directly (e.g., via Synapse Serverless SQL) before transforming it into a data warehouse. Data store for the data warehouse: Azure Synapse Analytics dedicated SQL pools This meets the requirements of storing 50 TB of relational data and supporting 200–300 concurrent read operations. Synapse dedicated SQL pools are purpose-built for large-scale data warehousing with high concurrency. Azure SQL Database Hyperscale supports large databases but has lower concurrency limits compared to Synapse dedicated SQL pools for reporting workloads.
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Data store for the ingested data: Azure Data Lake Storage Gen2 This is the best fit because it organizes data in a hierarchical directory structure (so you can organize by date and time), handles high-volume JSON ingestion from Event Hubs natively, and supports querying data directly (e.g., via Synapse Serverless SQL) before transforming it into a data warehouse. Data store for the data warehouse: Azure Synapse Analytics dedicated SQL pools This meets the requirements of storing 50 TB of relational data and supporting 200–300 concurrent read operations. Synapse dedicated SQL pools are purpose-built for large-scale data warehousing with high concurrency. Azure SQL Database Hyperscale supports large databases but has lower concurrency limits compared to Synapse dedicated SQL pools for reporting workloads.
Data store for the ingested data: Azure Data Lake Storage Gen2 Data store for the data warehouse: Azure Synapse Analytics dedicated SQL pools
Data store for the ingested data: Azure Data Lake Storage Gen2: This service is optimized for big data analytics and can organize data by date and time. It also supports hierarchical namespace which is useful for efficient data organization. Data store for the data warehouse: Azure Synapse Analytics dedicated SQL pools: This service is designed to handle large-scale data warehousing, can store 50 TB of relational data, and supports high concurrency for read operations, making it suitable for your needs.