Self-Acting Data Mining, or: Data Analysis with Autofocus

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Data mining analyses are considered complex activities that can only be performed by specialists – and are therefore expensive. Our new analysis approach Self-Acting Data Mining combines the speed of simple reporting systems with the enormous potential and forecast quality of traditional data mining.

Transform data into knowledge and business forecasts – fast and efficiently

Self-Acting Data Mining transforms large datasets into valuable knowledge with an unprecedented degree of automation. This innovative new approach radically streamlines the entire analysis process by standardizing more than 70% of the tasks used in classic data mining projects. As a result, analysis projects become dramatically faster, more planable, and more economical to complete.

 

More benefits, fewer costs

In general, data analyses are only profitable if the (expected) benefits of the insights gained amount to more than the cost of the analysis. Because Self-Acting Data Mining generates only a fraction of the costs of classic analysis projects, more analytical questions can be investigated profitably. What’s more, the additional time gained means that companies can react more quickly to current events or changed customer behavior – an increasingly important factor.
Thanks to the solution’s high degree of automation, employees  in the business units can be easily trained to tap the potential of this approach.

Flexible use

The advantages of Self-Acting Data Mining can be seen in almost every analytical question, for example, in customer value calculations and validations, customer segmentations, analysis of cross-selling and up-selling potential, customer churn analyses, in campaign management, or in fraud detection. Areas of use range from customer relationship management (CRM), through marketing and sales, controlling, and supply chain management, to production and quality assurance.

Contact us, download more information from our download area, or arrange an appointment with us. We would be most happy to hear from you.