ExpertMedium1 markMultiple Choice
Domain 2.4: Design a data storage solution for non-relational dataDomain 2Non-Relational DataAzure Data ExplorerTime-series
AZ-305 · Question 28 · Domain 2.4: Design a data storage solution for non-relational data
A logistics company wants to analyze GPS tracking data from its fleet of 100,000 trucks.
The trucks send location and engine telemetry every 5 seconds. The data engineering team needs to perform complex, ad-hoc time-series analysis on this massive volume of append-only log data to identify route inefficiencies. The query language must support advanced analytics, windowing, and text search.
Which Azure data service is best suited for this workload?
A logistics company wants to analyze GPS tracking data from its fleet of 100,000 trucks.
The trucks send location and engine telemetry every 5 seconds. The data engineering team needs to perform complex, ad-hoc time-series analysis on this massive volume of append-only log data to identify route inefficiencies. The query language must support advanced analytics, windowing, and text search.
Which Azure data service is best suited for this workload?
Answer options:
A.
Azure Data Explorer (Kusto)
B.
Azure Cosmos DB
C.
Azure SQL Database
D.
Azure Cache for Redis
How to approach this question
Match 'time-series analysis', 'append-only log data', and 'massive volume telemetry' to Azure Data Explorer.
Full Answer
A.Azure Data Explorer (Kusto)✓ Correct
Azure Data Explorer (Kusto)
Azure Data Explorer (ADX) is a fast, fully managed data analytics service for real-time analysis on large volumes of data streaming from applications, websites, IoT devices, and more. It is specifically optimized for append-only, time-series, and log data. It uses the Kusto Query Language (KQL), which is highly optimized for text search and time-window analytics.
Common mistakes
Choosing Cosmos DB. While Cosmos DB is great for IoT state management, ADX is the purpose-built tool for ad-hoc analytics on the historical telemetry logs.
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