Retail & ecommerce · Databricks
The Swing: Making day-to-day transportation personalized and effortless
Public case study · not a Metric Oak engagement
- Less time spent analyzing data
- 30%
- Reduction in business operating costs
- 40%
- Increase in revenue through the analysis of custom data
- 20%
What happened
The story in brief
Korea's leading personal mobility provider, with millions of users and a large fleet of e-bikes and scooters, was limited by legacy data systems. Analysing its data on Databricks helped it grow revenue.
How it compares
- 40% reduction in business operating costs, against a median reported cost reduction of 50% across 16 retail & ecommerce results.
Planning something similar?
Cloud data migration
Legacy warehouse to lakehouse, with parallel-run validation. Senior engineers, fixed scope, measured results.
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Related insights
Frequently asked questions
What results did The Swing report?
The Swing reported 30% less time spent analyzing data; 40% reduction in business operating costs; 20% increase in revenue through the analysis of custom data, according to its customer story published by Databricks.
Which platform and technologies did The Swing use?
The Swing used Databricks on AWS, including Unity Catalog, Databricks SQL, MLflow, Genie, Apache Spark, Kafka.
How do these results compare with other retail & ecommerce programs?
40% reduction in business operating costs, against a median reported cost reduction of 50% across 16 retail & ecommerce results.
Source
Customer story published by Databricks: Making day-to-day transportation personalized and effortless (opens databricks.com in a new tab) on databricks.com. Figures as published, retrieved 27 October 2026. The summary above is Metric Oak's own. This is not a Metric Oak engagement.
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