While common statistical methods focus on extracting information from a small amount of data, data mining (more precise: knowledge discovery in databases) works with big data. Datamining methods get rid of the traditional distribution assumptions. Working without these assumptions helps to apply these methods because there is no need of typical aspects of statistical analysis, like residual diagnostics.
The traditional use cases for data mining are marketing (market segmentation, market basket analysis) and financial applications (credit-scoring, fraud detection). But with the increasing amount of data the number of potential applications is constantly rising. Today datamining is used in industry (automotive, pharmaceutical) and for many (web-)services (recommendations, personal advertising).
To utilize these methods in your company, Statcon supports you right from the start with a definition of possible use cases in your field of application. The following steps will be data-management and selection, a final implementation of the chosen datamining methods and the integration into your business process. Years of experience put our consultants in the situation to give fast and precise advice concerning the methods and software to use.Our consultants are not only used to the application of common methods of KDD, like
- Prediction models (CART, Ensembles, Support Vector Machines, Neuronal Networks, ...)
- Association Rules (Apriori, Eclat)
- Clustering (Hierarchical , partitional and density based clustering)
At the same time being the largest European reseller for statistics software we have an excellent overview over the newest progresses in datamining tools. This allows us to recommend the most convenient software for your needs.
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