At Finaps we develop primarily on the Mendix platform. And with good reason; Mendix allows us to develop and maintain complex applications much faster, in direct collaboration with the client.
But every now and then we must go beyond the standard Mendix tools and get down to authentic Java coding. Sometimes we resort to Java for something as simple as a JDBC call, but increasingly often it’s about efficient handling of large amounts of data.
Finding an optimal path through 25^25 data point combinations, quickly matching partial search-terms to the content of large databases, pattern-analysis on large datasets, machine-learning based predictive modelling, or visual navigation through networks of many thousands of entities in a swift and responsive manner; these are some of the challenges we encounter when building enterprise applications. And developing a good solution can be very time consuming.
Our R&D team utilizes its expertise in machine learning, theoretical mathematics and visualization in this challenge. And we’re confident we’ll soon be able to deliver even higher quality data-intensive applications with fantastic visual capabilities in an even shorter time.
More news as development progresses!