Modern data mining and big data analysis environment. The multifunctional interface facilitates process and group work management. This flexible solution allows any already collected data to be used and predictive analyses to be easily integrated with the organization's business processes. A wide range of prediction algorithms, including data science and machine learning, is available to solve complex problems. Built-in Python integration further enhances the range of possibilities.
Standard Data Mining
The IBM SPSS Modeler analytical engine provides advanced modeling techniques based on statistical procedures and artificial intelligence. It offers graphical visualization of results and integration with other analytical environments and databases.
Analyses in the hands of users
The solution facilitates cooperation between users and safe storage of analytical procedures and resources. It creates the possibility for business users to launch scoring and other analytical processes.
Easy management of analytical processes
Built-in functionalities allow for extensive management of analytical processes - from creating a structure, through granting privileges and blocking edits, group work, to process control.
Saves time on process handling
Modern automation of processes includes not only predictive model learning, but also complex types of automatic triggers, execution status notifications or recording of the history of launches.
The architecture of the solution allows for flexible adaptation to the requirements of the organization and integration of predictive analyses with business processes and internal systems.
Real time solution
Distribution and implementation of results, evaluations or recommendations recorded in databases can be carried out in real time through operating systems.