The leading analytical tool. This platform allows you to work in, an accelerated way, the creation, delivery and maintenance of high value data for your company.
The RapidMiner models results are easy to interpret and can be directly integrated into business intelligence platforms, operating systems and customer contact points.
Incorporate all types of data
Speed & optimize ALL data exploration, blending & cleansing tasks
Apply machine learning to rapidly prototype & confidently validate predective models
Easily deploy & maintain models and embed analytic results
Embed results in all types of business apps & data visualizations tools
It allows you to create advanced analysis models , using mathematical, statistical and AI operators in an fast and simple way, it is accessible to the final users and it has the possibility of automating the results through RapidMiner Server.
Collaboration and accessibility. Calculus, models execution and delivery of other process results. Easy integration of results with other platforms and, if required, parallel execution in Hadoop clusters.
It complies and executes Hadoop models, speeding up complex analytical processes and easing up their execution and control.
Detection of those customers who meet features that identify them as prospects to change to a company that provides a service/product.
Consumer buying behavior analysis. It identifies patterns such as impulse buying, anchor products, promotion effectiveness, supports the definition of best bidding strategies and promotion, and planogram planning. It is used strongly in e-commerce and direct marketing to recommend products of interest for the consumer depending on its basket and profile. It also allows the clustering of stores, customers, products and promotions.
It allows patterns identification, nonlinear trends and the understanding of the relation between causes and results, we create mathematical models that allow the generation of precise predictive.
It allows you to give specialized treatment to the entities (customers, suppliers, etc.) according to the features of each segment:
It is used to identify items that are en route to be a potential problem such as:
It allows the recognition of relationships between entities (customers, distribution points, etc.) with geographical area features, including customs, fashion and other characteristics that support analysis such as store openings, the selection of products to be sold, sale points among others.