sublimd's Custom Client Dashboards: A Cube Semantic Layer Success Story
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Application Infrastructure & Middleware - Middleware, SDKs & Libraries
Applicable Industries
- Cement
- Healthcare & Hospitals
Services
- System Integration
About The Customer
The customer for sublimd's new analytics module is a healthcare provider. They were in need of a solution that could reduce paperwork in hospitals, enhance treatment quality, and revolutionize clinical research. The customer required an analytics module that could pre-process and visualize thousands of health data points in appealing charts. They were looking for a high-performance analytics tool that could reveal unprecedented information about processes in the hospital. The customer was pleased with the new version of the product, which worked like a charm.
The Challenge
sublimd, an award-winning medical software platform based in Switzerland, was facing a significant challenge in early 2019. They had received a request for a new module, sublimd Analytics, from a client. At that time, they had an open-source business intelligence server solution in their product. However, they were struggling with preconfiguring their analytics dashboards and delivering them ready-to-use to their non-technical customers. They needed a solution that would allow them to have full control over the customer configuration, which would be tracked in a version-control system. The challenge was to find a solution that would fit their technology stack, which included Node.js, MySQL, and Redis, and allow for a simpler deployment process.
The Solution
The solution came in the form of Cube, a framework that sublimd discovered on an independent comparison website. Cube was a perfect fit for sublimd's technology stack, which meant a much simpler deployment process than before. Moreover, Cube allowed developers the freedom to implement the frontend with a custom look and feel. After creating a small prototype, sublimd found that a seamless integration into their software suite was possible. During the integration process, sublimd was pleased with how mature Cube was and received premium support from the Cube team. In return, sublimd provided a lot of feedback and occasionally contributed to the project with commits to GitHub. After some initial teething troubles, the new version of the product was successfully rolled out to their first sublimd Analytics customer.
Operational Impact
Quantitative Benefit
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