ExpertMedium1 markMultiple Choice
AZ-305 · Question 31 · Domain 2.4: Design a Data Storage Solution for Non-Relational Data
A manufacturing company generates 10 TB of telemetry data daily from sensors on their assembly lines.
The data is time-series in nature. Engineers need to run ad-hoc, complex analytical queries over billions of rows of this data to identify anomalies and optimize machine performance. The queries must return results in seconds.
Which Azure data service is best optimized for this scenario?
A manufacturing company generates 10 TB of telemetry data daily from sensors on their assembly lines.
The data is time-series in nature. Engineers need to run ad-hoc, complex analytical queries over billions of rows of this data to identify anomalies and optimize machine performance. The queries must return results in seconds.
Which Azure data service is best optimized for this scenario?
Answer options:
A.
Azure Cosmos DB
B.
Azure Data Explorer
C.
Azure SQL Database
D.
Azure Table Storage
How to approach this question
Keywords: 'time-series', 'telemetry', 'ad-hoc complex queries', 'billions of rows in seconds'. This is the exact use case for Azure Data Explorer (Kusto).
Full Answer
B.Azure Data Explorer✓ Correct
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, and IoT devices. It is specifically optimized for time-series and log data, allowing engineers to use KQL to query billions of records in seconds.
Common mistakes
Choosing Cosmos DB because it handles IoT data well. Cosmos DB is great for *ingesting* and serving individual IoT records (OLTP), but ADX is better for *analyzing* massive volumes of them (OLAP).
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