Data-driven organizations rely on ETL (extract, transform, load) tools to consolidate data from various sources into a data warehouse. The most common approach to consolidation is using ETL software as the plumbing within the business, supporting data pipelines that optimize data movement and aggregation. When selecting an ETL tool, it's essential to consider factors such as compatibility with third-party tools, extensibility and future-proofing, usability, documentation and support, security and compliance, pricing, batch and stream processing, reliability and stability, and data transformations. A suitable ETL tool should provide a user-friendly interface, robust error handling, logging mechanisms, and pushdown optimizations, while also supporting high-performance ELT availability and providing strong authentication capabilities to protect data integrity. Ultimately, the chosen ETL tool should be able to meet growing data volumes without service degradation, offer versatility in adapting to changing data processing needs, and provide a secure solution that can pipe data into and out of databases without copying it into their systems.