Big Data analysis software for dental clinics
Our client serves more than 200 dental clinics in the US, allowing management to make data-driven business decisions.
The main aim of our client’s company is to help dental clinic owners, consultants, and dental CPAs analyze clinic performance in terms of revenue opportunities and profit leaks by analyzing data from the top three dental CRMs globally.
Our client wanted to improve their product's user experience. The existing product connected to and collected data from clinics' CRMs, but it was inefficient at processing the collected data.
The client asked SysGears to develop a new version of their software product with improved performance and new functionality for processing data and presenting it in real time in the form of dashboards and graphs.
As documentation for the supported CRMs was insufficient to determine the further course of development, our software engineer performed deep R&D to find out how the software would interact with the CRMs. As a result, they came up with an efficient solution for structuring data.
Our developers started with rebuilding the system architecture from scratch to ensure performance requirements were met. They chose a technology stack that supported big data development: the Spark framework to gather and process data, and ensure consistency and efficiency. Our specialists established data processing and ensured the data output is in required form almost immediately after the request.
During development, one of our software engineers acted as a tech lead. They took responsibility for evaluating new feature development; estimating the required time and effort; consulting the client’s team, and third-party specialists on any questions regarding the system’s work; and helping to identify bugs and find solutions.
We supported the client with specialists, changing the team size depending on the task complexity and required development speed. When achieving business goals required more specialists than the client had, we involved new team members to augment the existing team and ensure the project stayed on schedule.
Scala
Spark
Kafka
Play 2
JavaScript
Angular
