A manufacturing company collects 50 TB of telemetry data daily from factory sensors. They need a data exploration service that can ingest this massive volume of time-series data with low latency and allow engineers to run ad-hoc analytical queries using a SQL-like language. Which service should you recommend?

Answer options:

Azure Cosmos DB.

Azure Data Explorer.

Azure SQL Database.

Azure Table Storage.

How to approach this question

Identify the service designed for massive time-series telemetry and ad-hoc analytics.

Full Answer

B.Azure Data Explorer.✓ Correct

Azure Data Explorer is highly optimized for exploring large volumes of time-series and log data. It uses the Kusto Query Language (KQL) to provide fast, ad-hoc analytical queries.

Common mistakes

Selecting Cosmos DB, which is an OLTP database, not an OLAP telemetry exploration engine.

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