ETL stands for Extract, Transform, and Load. That exact order is the traditional and much practiced process which many companies use to make use of data. Take building a performance monitoring dashboard for an example, where source data is extracted from multiple sources. In this case, the sources can be an enterprise system such as ERP or WMS, or from manually maintained spreadsheets. The data are combined, blended, cleaned, aggregated and calculated in a central processing platform such as Acho Studio or Python. And a final clean output table is then loaded into a dashboard tool such as Tableau or Power BI where end users will access to perform the monitoring. It is common for the E, T, and L processes to be broken up and completed by different people using different tools.
It is common to have an IT department responsible for Extraction of data, a Development Team or Data Engineering Team to perform the Transformation, and a separate BI Team or Analyst Team to perform the final Load step.
Acho Studio is capable of completing the entire ETL process in one spot and by one member, because it is code-free and therefore does not require much of the tool specific skill sets needed in an otherwise traditional ETL project. It can integrate with multitudes of data sources, perform all data transformations, and load the result in an Acho Dashboard or pipe into multitude of downstream applications, which is not just limited to visualization outlets.