"Information is the oil of the 21st century, and analytics is the combustion engine."
— Peter Sondergaard (Gartner IT Symposium/Xpo, October 2011).
The intelligent collection, cleaning, processing and visualization of data is an indispensable process for the efficient, precise, productive and sharp self-criticism of any project.
This project seeks to make supply chains in the grocery sector more efficient, secure and customizable, addressing problems of logistics, shrinkage reduction and segmentation at the local, regional or national level of consumption.
This project started as a personal initiative during my university career at Tecnológico de Monterrey (ITESM), who has agreements with several companies to facilitate students the development of projects attacking the specific problems they have (in this case Iconn Group of 7-Eleven). this collaboration happened in two subjects under different approaches, in both I managed to reach the regional and national phases.
Important
Pending approval and modifications to be treated as Open Source, as intended.
- Facilitating export with gganimate.
- Native ggplot2-shiny dashboards.
- Local UX/UI.
Note
The src/tests reference folder is derived from the tensor-house repository, which is licensed under the Apache License 2.0. Copyright [2017] [Ilya Katsov].
Feel free to reach out if you have any questions or feedback.
- Email: victorbenitogr@gmail.com
- The subject must start with: [OpenNutritionData]