Our course "Data Mining Case Studies: Success Stories and Things to Avoid" presents applications of Data Mining which turned out to be very profitable for a wide range of businesses. The course begins with a compact introduction into the concepts and foundations of Data Mining. The seminar then presents a best-of-collection of successful use cases together with their practical deployment with the Data Mining software RapidMiner. These use-cases cover the optimization of marketing and customer relationship as well as the increase of sales by cross-selling and up-selling and other possibilities for optimization. It is shown how data mining can help to gain insight into your markets and deliver hints what customers expect of you and your products. Several predictive settings for forecasting sales or demands will be discussed as well as possible pitfalls and how to avoid them.

Due to a high number of practical exercises, the participants will be able to transfer the gained knowledge to own data mining problems and solve them quickly and easily. Furthermore, this course enables the participants to identify other promising application areas of Data Mining and to deepen the gained knowledge on their own.

You can register to this course online.

Details

• Course ID: 220802
• Date: September 25th - 26th, 2008
• Number of days: 2 days
• Location: Dortmund, Germany
• Target audience: users, analysts, decision makers, developers, administrators
• Previous knowledge: basic knowledge of computer programs and mathematics
• Methods: lectures, discussions, individual and group work, exercises on realistic data. Participants may introduce own work and project specific questions in order to find particular solutions together with the trainer and other participants.
• Content: this course is a compact introduction into the foundations of data mining and into the software RapidMiner. It addresses beginners and intermediate learners. Topics of this course are
  • Introduction into the basic concepts of Data Mining
  • Identifying your most profitable business units, and what characteristics make them so
  • Predicting future demand, prices, and sales
  • Identifying your most profitable customers, and what characteristics make them so
  • Indicating cross-sell and up-sell opportunities
  • Enabling Direct Marketing with cost-sensitive Data Mining
  • Optimizing sales by up- and cross-selling
  Extensive exercises on different data sets will be performed for all topics.

Prices

Value added tax (VAT) may have to be added to these base prices.