Microsoft Azure Data Fundamentals DP-900 Practice Question
An organization is designing an Azure-based analytics platform. The team wants to ingest large volumes of raw structured and unstructured files, keep storage independent from processing clusters, and rely on open file formats such as Parquet for future analysis. Which analytical data store should they implement?
A dedicated SQL pool in Azure Synapse Analytics
An operational relational database hosted in Azure SQL Database
A globally distributed NoSQL database using Azure Cosmos DB
A data lake that uses Azure Data Lake Storage Gen2
A data lake built on Azure Data Lake Storage Gen2 is designed for large-scale analytics scenarios that require cost-effective storage of raw data in many formats. Because storage is separated from the compute engines that later process the data, the lake can scale independently and remain available to multiple analytics services that understand open standards like Parquet. Azure SQL Database, Azure Synapse dedicated SQL pools, and Azure Cosmos DB are optimized for structured or operational workloads and do not store raw files in open formats while keeping compute fully decoupled from storage, so they do not satisfy all stated requirements.
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Microsoft Azure Data Fundamentals DP-900
Describe an analytics workload
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