Case Study: Heineken achieves instant data quality validation with Great Expectations

How Heineken uses GX to provide instant data quality validation and feedback to upstream data providers

Heineken, the global brewing company, needed a better way to handle data quality across its federated operating model. The Global Analytics team worked with data from many internal and external sources, including ERP, sales, marketing, media, and weather data, and struggled with inconsistent validation approaches, formatting issues, data type errors, duplicates, and harder-to-detect quality problems.

Great Expectations (GX) helped Heineken standardize validation across teams by embedding GX into its data workflows. In one use case, Heineken integrated Great Expectations into a file-upload tool that validates incoming Excel files as Pandas dataframes, instantly accepting or rejecting uploads and giving upstream providers feedback. The team is also exploring an API-based validation service; while no hard numeric impact was reported, the solution eliminated repeated reimplementation of tests and improved consistency.

Heineken

Madelon Hulsebos

Data Scientist