Business Data Analytics team runner-up in the Datathon organized by Grupo Cajamar
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Business Data Analytics team runner-up in the Datathon organized by Grupo Cajamar
Datathon
Business Data Analytics team runner-up in the Datathon organized by Grupo Cajamar
This is the V. edition of a competition in which more than 20 universities nationwide participate
2021·06·01
On May 1st the jury of the Datathon organized by the Cajamar Group announced its decision. A team of second year students of the Degree in Business Data Analytics of Mondragon Unibertsitatea were runners-up in the challenge related to data visualization. This is the V. edition of a competition in which more than 20 universities participate nationwide and where the vast majority of participants are master's and doctoral students.
We have been with the team (Nagore Bermeosolo, Elene Astondoa and Unai Torrecilla) and these are their evaluations after knowing the results.
Why did you decide to participate in this competition? What motivated you to do it?
We thought it was very interesting to compete with people from outside the university and with very different profiles in order to have a first contact with the outside world. In addition, we thought it could help us to develop our personal brand, and to start specializing in a more specific area of data analytics.
What was the contest about? How was it organized? What phases were there?
The objective was to analyze the impact that COVID-19 has had on the Spanish agri-food market through data, in a visual and easily interpretable way. The competition had two elimination phases to reach the national top 3. The first phase was an inter-university competition, and in the national phase the winners from each of the universities competed. Once this was over, the three finalist teams made a presentation to defend their projects.
What did you build and what does your solution to the competition consist of?
Our product is an interactive and multiplatform visual application, which allows the user to draw different conclusions in a guided way. It has different pages, which allow to analyze the impact of COVID globally and in more detail. It allows zooming in on these qualitative and quantitative impacts by autonomous community and by product. In addition, it studies the eating habits of the population during and after the pandemic.
Our product is an interactive and multiplatform visual application, which allows the user to draw different conclusions in a guided way. It has different pages, which allow to analyze the impact of COVID globally and in more detail. It allows zooming in on these qualitative and quantitative impacts by autonomous community and by product. In addition, it studies the eating habits of the population during and after the pandemic.
What have you learned in this process, and what do you take away from it?
We have had the opportunity to deepen aspects such as user experience, creativity, business orientation and develop our research capabilities to solve problems that we had not faced before. Finally, we have increased our expertise in creating interactive applications in Shiny.
We have had the opportunity to deepen aspects such as user experience, creativity, business orientation and develop our research capabilities to solve problems that we had not faced before. Finally, we have increased our expertise in creating interactive applications in Shiny.
Would you encourage other students to participate in this type of activity? Why?
We certainly encourage all those students who wish to expand their knowledge on aspects of data analysis that are of interest to them, as it is a very good opportunity to do so. Even so, it is worth mentioning that behind these works there is a great implicit effort, which may not be perceptible to the naked eye.
We certainly encourage all those students who wish to expand their knowledge on aspects of data analysis that are of interest to them, as it is a very good opportunity to do so. Even so, it is worth mentioning that behind these works there is a great implicit effort, which may not be perceptible to the naked eye.