Accelerating The Success Of Our Predictive Client Insights
summary
Schroders builds a Client Insights Unit that runs 2.5 years of experiments, publishes all outputs into a single CRM platform so every access and downstream action is traceable, and proves value by linking predictions to subsequent tasks and opportunities. Early work uses Python notebooks and CSV extracts; migration to cloud and adoption of Snowflake for sharing is underway. An enterprise “factory” creates reusable components and a data product template Adapt so domains own stacks, pipelines and monitoring, speeding production and repeatability.
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chapters (6)
- 0:00Introduction and team overview
- 4:57Client insights unit purpose
- 7:27Key learnings from data science journey
- 15:44Enterprise data factory setup
- 20:19Data mesh approach explained
- 24:56Q&A on text data and tools
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