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    PracticeAzure Solutions Architect Expert (AZ-305)Azure Solutions Architect Expert AZ-305 Practice Exam 5Question 28
    Medium1 markMultiple Choice
    Domain 2.4: Non-Relational Data StorageDomain 2Data StorageAzure Data ExplorerAnalytics

    AZ-305 · Question 28 · Domain 2.4: Non-Relational Data Storage

    Your company is building a centralized logging and analytics platform for a fleet of autonomous drones.

    The drones generate 5 TB of time-series log data daily. Data scientists need to run complex, ad-hoc analytical queries over billions of rows of this telemetry data to identify flight anomalies. The queries must return results in seconds.

    Which TWO Azure services are best suited for storing and querying this massive volume of time-series log data? (Select TWO)

    Answer options:

    A.

    Azure Cosmos DB

    B.

    Azure Data Explorer

    C.

    Azure Cache for Redis

    D.

    Kusto Query Language (KQL)

    E.

    Azure Table Storage

    How to approach this question

    Identify the Azure service purpose-built for time-series log analytics and its associated query language.

    Full Answer

    Azure Data Explorer (ADX) is a highly scalable data exploration service designed specifically for log and telemetry data. It excels at handling massive volumes of append-only, time-series data and allows for ad-hoc querying with sub-second latency. To query data in ADX, you use the Kusto Query Language (KQL), which is optimized for searching and analyzing text and time-series data. Cosmos DB is too expensive for this volume of append-only logs, and Table Storage cannot do complex analytics.

    Common mistakes

    Selecting Cosmos DB. While it handles JSON well, ADX is the architectural standard for high-volume time-series telemetry analytics.
    Question 27All questionsQuestion 29

    Practice the full Azure Solutions Architect Expert AZ-305 Practice Exam 5

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