Credit Suisse needed to be able to process and store more than 30 million rows of data per month, plus make that data accessible to end-users for ad-hoc analysis through a web-based interface. Today they're doing all that and more with the Elastic Stack.
Learn how the team uses R to extract, transform, and enrich data from various raw data sources. Also, see how the resulting dataset is indexed in Elasticsearch and visualized in Kibana. Hear how the the team has evolved their approach and which improvements they've made with Elastic Stack updates, as well as lessons learned.