Data Analytics & AI

Observing data and indicators we can visualize which processes are not obtaining the expected results and why this is happening, besides providing trends based on comparative.

The key is to take the best decisions and to be prepared for the future.

Know what values will be obtained in the future based on past data and obtain automatic recommendations of what decisions to make in our business processes. When will a machine fail in my factory?, What prices of a product do I offer to a specific group of customers to guarantee more sales?, etc.

Through the analysis of data and images, we can obtain patterns and predict different stages and evolution of pathologies, obtain market flows and tendencies or exploit the facial recognition with security purposes.

A complicated issue in analytics is to exploit in an agile and effective manner large data amounts of heterogeneous origin.

The term Big Data is commonly associated with the 3Vs that define the properties: Volume, Velocity and Variety. Volume refers to the large amount of data which it will be able to deal, Velocity to the speed of data processing and Variety to the different types of data. We add to this equation the fourth V of Value that stands for knowledge that can be obtained from the stored data.

By applying machine learning techniques, machines can throw predictive models by learning from data and incorporating business intelligence into prescriptive analytics. Thanks to the data analysis we solve problems by the technique of generalizing behaviours to concrete situations.

The data and compilation analysis is essential to adapt the strategy to the behaviours of the client and the competitors.

Dynamic pricing techniques to calculate the most efficient price according to market trends, competitor’s prices, time of the year or the maturity of the product will boost sales.

An analysis of the user behaviour will make possible to identify weaknesses in our online point of sale in order to apply improvements through user experience.