DocsDocsSlackSlackResources ExamplesSee what's possible with Cube.jsExamples See what's possible with Cube.jsBlogLearn more about Cube.jsBlog Learn more about Cube.jsCommunitySee how to contribute to Cube.jsCommunity See how to contribute to Cube.jsGitHubFile an issue or contribute the codeGitHub File an issue or contribute the codeCube CloudCube Cloud DocsDocsSlackSlackExamplesExamplesBlogBlogCommunityCommunityGitHubGitHubCube CloudCube Clouduser storyIt only took one frontend software engineer to build a whole analytics solution
CompanyCota Healthcare is a cancer data research company. The company combines oncology expertise with advanced technology and analytics to organize real-world, fragmented data in order to guide decisions and actions.
Patient records analyzed3000
Implementation time8 weeks
Engineering time saved14 weeks
Cube.js community Slack support was so great and our demo proof of concept app was so easy to implement, it went to production right away.Tanvi PalSenior Software Engineer at Cota Healthcare
Challenge Before Cube.js, Cota used Qlik to provide hospital administrators with analytics for cancer data. There were not many options to extend Qlik to provide users with a great user experience and different features like in-app data drill downs. These existing solution inabilities led to the decision of in-house development of such an analytics solution. Before starting development of this solution from scratch, Cota engineers were fortunate to find Cube.js, which provided a simple analytics data access API, which was exactly what they were looking for. Qlik wasn’t able to provide the required user experience level and customization features for hospital administrators. It was clear that the company needed to build a solution in-house without using third party BI tools to fulfill all the requirements. It was only one software engineer, mostly with frontend expertise, who was allocated for this project. Solution With Cube.js, in just 8 weeks Cota was able to provide hospital administrators with a solution for analyzing cancer data with a much better look, feel, performance, and custom data drill down features that the previous solution lacked. Cube.js allowed them to save 14 weeks of backend engineering and go to market time. Thanks to Cube.js community support and the very low barrier for Cube.js development entry, the whole solution was done by only one software engineer with an expertise mostly in frontend JavaScript.

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