ETL processes are vital tools for feeding a data warehouse. By extracting, transforming and loading data from applications and systems, ETL supports reporting, analytics, and business intelligence, which provides essential visibility for consolidated data.
Many ETL tools, however, are cumbersome to use. Connections need to be built for each data source. The resulting data needs to be modeled for analysis. Data warehouses need to be setup and managed as the destination for the data. Analytics tools and dashboards need to be integrated.
A faster, easier and more modern ETL process crafts a universal schema, one that integrates the entire data pipeline. Such an ETL operates with a deep knowledge of fields — from mapping relationships and merging, to matching records and handling conflicts — so you have quick access to clean, usable data across all of your SaaS applications.