The correct option is Azure Synapse Serverless SQL pool.

This option lets analysts run familiar SQL queries directly over files in a data lake without provisioning or managing servers. The service provides on demand T SQL query access to Parquet and CSV stored in ADLS Gen2 and charges based on query processing so the startup can explore data with minimal operational overhead.

Azure Databricks is a managed Apache Spark platform that is powerful for data engineering and machine learning but it normally involves cluster configuration and tuning which does not match the requirement to avoid server management for ad hoc SQL exploration.

Azure Data Explorer is optimized for high performance analytics on log and telemetry data and it uses the Kusto Query Language which is different from standard SQL, so it is not the best fit for analysts who want familiar SQL over a data lake.

Azure Data Factory is an orchestration and ETL service used to move and transform data and it is not an interactive SQL query engine for analysts to explore data directly in a lake.

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