What is Extract, Transform, Load (ETL)
ETL stands for Extract, Transform, Load. It’s a common process used to move data from one system to another. First, data is extracted from a source (like a spreadsheet, ERP, or supplier file), then transformed into the right format or structure, and finally loaded into a destination system (like a PIM, database, or data warehouse).
Examples
| Use case | How it works |
| Standardizing supplier data | Extract data from supplier files, transform inconsistent names and units (like changing cms to inches, or kg to pounds), then load into your PIM system |
| Preparing data for retailers | Extract product information, transform it to the retailer’s required format using a template, load it into the retailer’s platform |
| Merging data from different systems | Extract data from multiple systems (like spreadsheets, ERPs, or ecommerce platforms); transform it to a consistent structure; load into your PIM |
A brief history
The ETL process has been around since the 1970s, when companies needed a way to consolidate data from different systems into one place for reporting and analysis. Originally used in big enterprise data projects, it’s now a standard approach in ecommerce and product data management, especially when companies need to clean up or reformat messy data before using it.
Good to know
ETL isn’t just about moving data; it’s about preparing it. The “Transform” step is key here: you might change column names, standardize units, map categories, or enrich product attributes. Good ETL processes make sure that the data you load into your system is ready to use.
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