You have 12 on-premises data sources containing customer information (SQL Server, MySQL, Oracle). You will consolidate this data into an Azure Data Lake Storage account for analysis and reporting. To automatically extract, transform, and load new data into the lake while minimizing administrative effort, which service should you use?

Azure Data Factory (ADF) is the correct choice because it is a cloud-based ETL (Extract, Transform, Load) service designed for orchestrating and automating data movement and transformation. It has built-in connectors for various on-premises data sources like SQL Server, MySQL, and Oracle, enabling seamless data ingestion into Azure Data Lake Storage. ADF also supports scheduling and monitoring pipelines, minimizing administrative effort for ongoing data consolidation. Azure Data Explorer is a fast, highly scalable data exploration service for telemetry and time-series data, not primarily for ETL from diverse on-premises sources. Azure Data Share is for sharing data with other organizations, not for internal ETL processes. Azure Data Studio is a cross-platform database tool for developers and DBAs, not an ETL service.