A data engineer needs to conduct Exploratory Data Analysis (EDA) on data residing in a...

A SQL Serverless Warehouse is the most suitable option for running SQL-based exploratory data analysis at scale while minimizing operational and cost overhead. Serverless SQL warehouses are fully managed by Databricks, meaning Databricks automatically provisions and scales compute resources, applies Photon acceleration, and optimizes query execution without requiring the user to manage infrastructure. This makes them ideal for workloads involving large numbers of ad hoc or interactive SQL queries, which is common during EDA. Because the data resides in a custom-defined cloud network, serverless SQL warehouses can still securely access governed data when Unity Catalog and networking requirements are satisfied. All-purpose clusters (option A) are designed for collaborative development and mixed workloads, not cost-efficient high-concurrency SQL querying. Classic SQL warehouses (option D) are legacy and lack the performance and cost optimizations of newer serverless offerings. Pro SQL warehouses (option B) require user-managed sizing decisions, whereas serverless warehouses optimize both performance and cost automatically. Databricks documentation recommends SQL Serverless Warehouses for fast, scalable, and cost-effective SQL analytics.

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