The amount of data generated in a company has grown exponentially, as well as the possibilities of obtaining value from such data: as we have discussed in other posts, it is possible to use them in different ways to make better decisions, obtained from models and algorithms. However, a company's path to become "data-driven" is not easy.
A move that many companies have recently made is the creation of a Data Analytics department, separating its team from the already traditional IT structure. This department becomes responsible for managing the company's data, creating ways to visualize it more efficiently and developing models for optimization, forecasting, etc.
However, more than creating mathematical models and algorithms, this department must build the applications that will embed them, allowing end-users to execute them and make decisions. This process is as crucial as the development of models itself, because if the application is not functional and intuitive, users will not be able to extract value and gains will not be obtained.
Departments face several difficulties when building such applications. Among them, we can mention the difficulty of programming graphical interfaces in traditional languages (Java, C++, Python, among others), as well as the time required for their development.
To facilitate this step in the case of mathematical model optimization applications, Cassotis developed Quandec, a platform that allows the creation of complete and intuitive graphic interfaces quickly, in addition to the use of several analysis functionalities. Quandec is a framework for the development of applications that will allow end-users to visualize the results through different graphic elements (tables, charts, graphs, diagrams, etc.) and edit parameters. By using a simple syntax, the time to develop such an interface is accelerated to generally less than two days.
In addition, Quandec allows the use of a set of already included features, regardless of the model or problem to be solved, avoiding the need for new developments for each application, such as:
Other advantages that a Data Analytics department can benefit from by using Quandec are the standardization of its applications, which facilitates user learning and maintenance by developers, and the flexibility to use different optimization solvers or even create their own solving method via Java.
Without a doubt, selecting the best tools is essential for an Analytics department to be effective in the company and, with all its benefits, it is clear that adopting Quandec can make the difference in this success!
Author: Cassiano Lima - Senior Consultant at Cassotis Consulting
Co-author: Emmanuel Marchal - Managing Partner at Cassotis
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