DATA ANALYSIS, PREDICTIONS AND REPORTABILITY.
Predictive Mathematical Models that allow you to anticipate occurrences of unexpected events.
WHEN YOU KNOW WHAT IS GOING TO HAPPEN, IT IS EASIER TO MAKE DECISIONS.
DataQu adapts to your needs and gives you the necessary information so you can transform your company from being reactive to proactive.
CREATE A BETTER CUSTOMER MANAGEMENT WITH A CORRECT VISION OF THE FUTURE.
We deliver real-time predictions in a simple and easy way.
Success
Stories
At DataQu we collect and process your information and thus generate analyzes and predictions adapted to your reality.
Camanchaca
Increased efficiency with a predictive model of Salmon Caliber for the Camanchaca fishery.
DataQu was in charge of designing, implementing and calculating the caliber or size of the salmon through a predictive model, which is carried out through sampling, in order to effectively approximate the stock that will be harvested. It predicts up to 90 days before being harvested, and this has allowed them to have greater internal efficiency and thus reduce the gap between production and sale.
DataQu was in charge of designing, implementing and calculating the caliber or size of the salmon through a predictive model, which is carried out through sampling, in order to effectively approximate the stock that will be harvested. It predicts up to 90 days before being harvested, and this has allowed them to have greater internal efficiency and thus reduce the gap between production and sale.
Cementos BíoBio
Reduction of costs and errors in shipments with the intelligent concrete programmer.
DataQu was in charge of developing an intelligent programmer, which based on a Machine Learning model that learns from each client in order to predict the cycle time that relates the driver with the size of the truck, with the client and suggests the best combination to make the delivery to each client, this programmer is implemented in all regions of Chile.
DataQu was in charge of developing an intelligent programmer, which based on a Machine Learning model that learns from each client in order to predict the cycle time that relates the driver with the size of the truck, with the client and suggests the best combination to make the delivery to each client, this programmer is implemented in all regions of Chile.
Doña Inés de Collahuasi
Optimization and control of copper recovery, based on process variables and "upstream" variables. Using a methodology based on Machine Learning, DataQu developed recommendations to improve Collahuasi's operation through predictions and simulations with mathematical models that help decision-making to optimize the copper flotation or recovery process, and thus minimize losses in raw material concept.
Mutual de Seguridad
Decrease in customer churn through predictive models.
DataQu was in charge of developing a predictive model of customer churn, which based on a Machine Learning model, manages to determine up to 3 months in advance if a Mutual customer is going to leave the company. The model is able to understand which are the most important variables that trigger the action of the leak, allowing the Mutual to be able to take preventive actions in case of wanting to avoid the leak. This has allowed them to get to know their clients better and to be able to take precedence over unexpected situations.
DataQu was in charge of developing a predictive model of customer churn, which based on a Machine Learning model, manages to determine up to 3 months in advance if a Mutual customer is going to leave the company. The model is able to understand which are the most important variables that trigger the action of the leak, allowing the Mutual to be able to take preventive actions in case of wanting to avoid the leak. This has allowed them to get to know their clients better and to be able to take precedence over unexpected situations.
ACTION PROCESS
AND IMPLEMENTATION
Client's issue
Variables (Data)
- Data analysis
- Correlation
- Building first models
Predictive models
generation
Action plan
Methodology
Our clients
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