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BI & Analytics

ETL Extract, Transform, Load

A process that extracts data from source systems, transforms it and loads it into a data warehouse.

Full definition

ETL (Extract, Transform, Load) is the classic process of populating a data warehouse with data from multiple operational sources. Three steps: Extract (pull data from the ERP, POS, CRM, external files), Transform (clean, validate, enrich, standardise formats, apply business rules) and Load (load the result into the data warehouse).

The value of ETL is in the transformation. Data from different systems uses different codes for the same concept (customer 'ABC123' in the ERP may be '0001-ABC123' in the CRM), comes in inconsistent formats (dates in different formats, numbers with different separators) and has errors or omissions. ETL standardises everything before the data reaches the dashboards.

For MyBusiness-ITV, INFOS implements robust ETL pipelines between the MULTI ERP (or other client source systems) and the Qlik Sense model. The frequency depends on the case: daily for sales and stock, hourly for active order books, continuous (streaming) for operations where latency counts. The modern alternative is ELT — load first and transform at the destination — suitable when the data warehouse has sufficient compute power.

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