Design of models for the selection of the suitable platform in the area of data analysis

This paper deals with the design of models that form the basis for Decision Support System (DSS) supporting suitable solutions of data analysis. DSS will be in the form of web application in order to bring the most practical solution. The design of these algorithms is only one of the five stages of the research in field of data analysis. That means, the other stages will be described in this article only marginally - mapping the currents situation in this IT field, identification of parameters entering into the designed models, implementation of web application and verification of DSS using case studies. For each of these areas, a separate paper will be published later. Models presented in this article are ranked from the simplest to the most complex, in each case, the algorithm is demonstrated on a model example. DSS itself, which is the output of all research should facilitate decision of organizations about selecting a suitable analytical environment, application or platform. In other words, if the company has some amount of data and does not know what to do next. The only one thing the organization knows is the fact that data are a source of knowledge and time precious.

[1]  Ramjeevan Singh Thakur,et al.  An Efficient Approach for Supervised Learning Algorithms Using Different Data Mining Tools for Spam Categorization , 2014, 2014 Fourth International Conference on Communication Systems and Network Technologies.

[2]  Mete Ömerali.  Feasibility evaluation of Business Intelligence tools as measurement systems: an industrial case study , 2012 .

[3]  Marguerite Summers,et al.  Evaluation of fourteen desktop data mining tools , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[4]  Bas Geerdink,et al.  A reference architecture for big data solutions introducing a model to perform predictive analytics using big data technology , 2013, 8th International Conference for Internet Technology and Secured Transactions (ICITST-2013).

[5]  Adela Tušanová,et al.  A Methodology for Decision Support for Implementation of Cloud Computing IT Services , 2014 .

[6]  Ping-Tsai Chung,et al.  On data integration and data mining for developing business intelligence , 2013, 2013 IEEE Long Island Systems, Applications and Technology Conference (LISAT).

[7]  Dean Abbott,et al.  An evaluation of high-end data mining tools for fraud detection , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[8]  Younes Oulad Sayad,et al.  From Big Data to Big Projects: A Step-by-Step Roadmap , 2014, 2014 International Conference on Future Internet of Things and Cloud.