Big Data and Predictive Analytics in Business Decision Making
DOI:
https://doi.org/10.62943/rig.v3n2.2024.103Keywords:
Big Data, Predictive Analytics, Inventory Management, Gradient Boosting, Sales PredictionAbstract
This study examined the implementation of Big Data and Predictive Analytics at "Or Importaciones", a retail company in La Maná, Ecuador, that was facing challenges in inventory management and sales prediction. The objective was to evaluate the impact of a Predictive Analytics model on the accuracy of sales forecasts and inventory optimization. A mixed methodology was used, combining quantitative analysis of historical data with a predictive model based on Gradient Boosting. The study, conducted between January and May 2024, used Python and Google Colab for data analysis. The results showed a significant improvement in sales prediction accuracy, with the model achieving an R² of 0.92. It was concluded that the integration of these technologies can provide a significant competitive advantage even for small businesses, improving decision making in sales and inventory.
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