Case Study: Standard Chartered Bank achieves 30x analyst productivity with Dataiku

Building Collective Intelligence with Dataiku

Standard Chartered Bank’s FP&A team faced a scaling and behavioral challenge: analysts were constrained by spreadsheet-based processes and systems that could only handle about 10 million rows of data, yet the bank’s finance problems required visibility into hundreds of millions of rows (Craig Turrell aimed to get from 10 million to 400 million rows) and better use of an under‑utilized data lake and terabyte‑level compute. To overcome this, the bank adopted the Dataiku platform to enable governed self‑service analytics and unlock the existing infrastructure.

Dataiku was used to process massive tables (turning over a 4.5 billion‑row table in a single operation), productionalize pipelines with DataOps and SLAs, build a CoE and a data marketplace, and automate daily Tableau refreshes. The result: two people using Dataiku now do the work of about 70 spreadsheet‑bound analysts (≈30× productivity improvement), three major systems run on the platform, 12 communities leverage core datasets, and manual app/ spreadsheet chaos has been dramatically reduced. Dataiku enabled the bank to scale analytics, democratize trusted data, and move toward predictive, collective‑intelligence use cases.

Standard Chartered Bank

Craig Turrell

Head of Plan to Perform (P2P) Data Strategy & Delivery