Story
Databricks
SantanderSantander Uses Mosaic AI for Feature Pipelines
Santander, a financials organization in Spain, uses Mosaic AI from Databricks to support applied machine learning for data scientists and ML engineers.
Mosaic AI sits in the daily path at Santander, especially for data scientists and ML engineers.
“Financials work at Santander spans more than one site, even when headquarters sits in Spain.”
“Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.”
Independent write-up. Figures come from public sources or are illustrative.
Value results
| Category | Value result |
|---|---|
| Productivity | Fewer stalled items because feature pipelines has a clear owner |
| Productivity | Handoffs in applied machine learning sit in a shared queue instead of a mailbox trail |
| Capability | New joiners can see how applied machine learning actually runs |
Story
Financials work at Santander spans more than one site, even when headquarters sits in Spain. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.
Databricks (Mosaic AI) is what they standardized on. Databricks provides a lakehouse platform for data engineering, analytics, and AI, with Unity Catalog and Mosaic AI for governed models. Santander uses it as the system of record for feature pipelines, with data scientists and ML engineers as the primary operators and other groups coming in through the same queue.
Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.
