A leading e-waste recycling company wanted to improve business efficiency and fuel growth by deep diving into¬†its¬†kiosk transaction data collected over the last four years.¬†The insights from this¬†historical¬†data were key to several important managerial decisions like¬†the location for¬†the next kiosk¬†set-up, ways to reduce user wait times, negotiation of quotations, etc.
They built a BI architecture on top of AWS with Snowflake and Tableau.¬†However, they were facing several analytical challenges on their Snowflake¬†platform.¬†An attempt¬†to analyze multiple years of data on Snowflake resulted in significantly¬†reduced query performance.¬†Moreover, the¬†volatility¬†of querying costs¬†resulted in skyrocketed bill amounts.
Download this case study to learn how¬†Kyvos¬†enabled them¬†to:
- Achieve OLAP on AWS with Snowflake as the data source
- Perform faster and more cost-effective analytics on the cloud vs. running queries directly on Snowflake
- Deliver¬†5-second response time for ad hoc queries
- Conduct interactive analytics on four years of data with the capability to extend it to ten years to meet future requirements
- Generate accurate predictions on daily¬†and¬†monthly payouts for better decision making