Data warehousing role in telecommunications continues to increase in importance. Supporting business decision making through reports and analysis Data Warehouse empowers management to act based on real numbers from the business environment they operate in. Data mining processes play an important role in analytical processes, either for the purpose of decision making support or marketing campaign support. In the field of marketing, especially given the environment full of various information and offers, personalized approach becomes a must. Here data warehousing and data mining offers the technology required to implement personalized marketing approach, allowing for the better understanding of the customer’s needs and preferences. Data mining can be implemented through different tools offering intelligent automata or various algorithms. This thesis presents a complete end to end approach to data mining aimed at a telecommunications environment. It starts with the presentation of various algorithms, ways to compare models, details important from the telecommunication standpoint, then moves on to the business background, mining process implementation in a workstation consisting of database, interfaces, self developed neural network and open source tool Weka. Workstation delivered in the scope of this thesis presents an approach to data mining in telecommunications marketing campaign environment with the goals of cost down and improved business model understanding. This workstation is then tested on multiple test data sets in order to compare several algorithms both from their mining capability and from the practical aspects of their implementation. Final conclusion from the tests is that no single algorithm is the best for all situations, but an analyst is required to interact with the process, at least occasionally in order to perform verification.