Personalized banking provider loads data from 14 different sources three to four times faster
Snowflake has rid Chime of the restriction of a rigid data modeling world, allowing for a much faster pace of business and far greater efficiencies for our small technology team.
– Ethan Erchinger, Director of Operations at Chime
Download the full report on how mobile banking provider Chime analyzes data across mobile, web, and backend server platforms to identify ways to enhance its members’ experience while delivering value to its business.
Chime uses data analytics to personalize all aspects of its mobile banking application, analyzing data from a large number of services and events from third-party analytics tools.
Chime needed a solution that would enable it to gather data from a variety of sources into a single location and make it available for near, real-time analysis.
Chime chose Snowflake because of its native integration with the Looker BI tool. It also found Snowflake to be an attractive solution to simplify its data pipeline, putting JSON data to work faster compared to other big data platforms such as Hadoop.
With the click of a button, Chime can scale its computing by spinning up additional clusters for both its data loading and analytics so they don’t compete for performance. Analysts now spend more time analyzing data and deriving value from Snowflake and far less time waiting on results from various queries.
The ability to scale performance and more easily integrate use cases for new data enables Chime to keep focused on enhancing customer value for millennials — the company’s primary target.