Case Study: Société Générale achieves faster, more productive machine learning with Alation

Data catalogues offer boost in the machine learning race

Société Générale faced a common enterprise AI blocker: data was scattered across Teradata, SAS, Excel, SharePoint and data lakes, making it hard for business teams and data scientists to find trustworthy, well-documented sources and move models into production. Without clear provenance, quality or access rules, data scientists were wasting time copying data, and IT was reluctant to operationalize models built outside governance controls.

The bank piloted Alation’s data catalogue (recommended by Teradata), which uses machine learning to map datasets to business language, surface recommendations, show lineage and enable collaboration. After an eight-week proof of concept marketing users rated search and recommendations highly; with governance and access rules defined, the catalogue reduced time spent finding data, connected users to data owners, improved data understanding and boosted data-science productivity — positioning the tool as a scalable, strategic platform for self-service analytics.

Société Générale

Pascale Assémat

Director Data Marketing, Retail