Nowadays there is an exponentially growing tendency in the financial and technical industries in terms of the data they produce. There are relatively cheap devices available on the market and they provide tremendous amount of storage capacity. This tremendously grown dataset is often referenced by the name Big Data. There this an enormous amount of data in our world and it’s growing each day. This is impossible for the humans to process and understand on their own. This is where data visualization comes in handy. Visualization which extracts the essence of the observations on this huge dataset and presents it to the experts in a visual context. This is crucial because with this big amount of data the correlations and patterns can be easily missed by just looking at the raw data. There are multiple ways to visualize data. For a stationary process, a diagram can be used to represent the data and animations are for real-time changing processes. These diagrams are easy to understand if you have a lot experience with them. Unfortunately not everyone has a good amount of practice with these diagrams. For these people there is an otherway, putting the results in a different context, into an animation that makes it easier to understand the data. This thesis will investigate the most common methods to analyze data in the technical industry and related visualization and animation tasks.
This thesis is going to offer a method for developing an application in a unified method which is easily understood by both technical and financial experts. This method will rely on OMG's standard Interaction Flow Modeling Language and behavior-driven development with a framework called Cucumber.
At the end of the paper, an example will be shown for using the presented method’s last phase in order to prove it’s usefulness. For business analysis, it will be using Microsoft PowerBI and for animation a language called Processing.