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Data Mining

 

In the statistics field, the trees are often likely to hide the forest. However, there are mathematical and numerical tools that assist the analyst in spotting systematic patterns in the midst of billions of data bits. These tools and methodologies, known as “data mining”, churn out information and patterns concealed in large volume of data. INVAP has successfully broken into this field and currently offers data mining products and services to prospective customers.

In the domestic market, INVAP has recently completed an ambitious data mining project with a private commercial-transactions company. The developed system was able to crack a large database loaded with information that was both complex, apparently unintelligible and thus useless.

INVAP carried out the development of data mining tools suitable for the different output stages of the project, meant to transform the database in a useful policy tool. These stages were basically the following:

  • Customization of the data base to allow data mining operations
  • Design of indexes and variables’ categories
  • Development of rules and patterns
  • Introduction of cause/effect networks
  • Data segmentation
  • Descriptive model of behavioral patterns
  • Predictive model of behavioral patterns
  • Design of responses to be implemented by the system

Throughout these stages, the design team followed the following methodology:

  • Definition of valid operative modules
  • Statement of the requirements of each module
  • Analysis of each module
  • Execution of automatic solutions, using proprietary software tools in the areas of data mining, object programming and user interfaces.
  • Joint analysis of the results and final recommendations and updates.