Simpl ensures frictionless online payments for shoppers with Databricks
Indian checkout platform Simpl used Databricks SQL and Lakeflow Jobs to consolidate siloed data and speed up ML model training from several weeks to a single day, cutting time to market for ML models by 90% and improving analytics team turnaround time by 35%.
Overview
Indian checkout platform Simpl used Databricks SQL and Lakeflow Jobs to consolidate siloed data and speed up ML model training from several weeks to a single day, cutting time to market for ML models by 90% and improving analytics team turnaround time by 35%.
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Inspect the highlighted sourceThe challenge
Simpl's outdated tech stack was not built to handle its growing volume of data, causing frequent failures with no common platform for access, and siloed data meant ML models were taking several weeks to train, far too slow for the real-time demands of Simpl's analytical and reporting needs.
The solution
Simpl adopted the Databricks Data + AI Platform, relying on Databricks SQL to democratize data access for querying and dashboarding, and Databricks Lakeflow Jobs to streamline ETL, ML model training and reporting with configurable, autoscaling cluster management and simplified scheduling from the workspace or Git.
Reported business value
Simpl's ML models that previously took several weeks to train are now ready within one day, the analytics team's turnaround time for reporting tasks improved by 35%, and features, enhancements and ML models now reach production with time to market reduced by 90%.
Sources
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