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2. BUSINESS INTELLIGENCE IN MODERN DECISION MAKING Systems of business intelligence combine operational data with analytical tools in order to give the descriptive meaning to that data and to give to the manager competitive information. The term Business Intelligence has replaced the terms systems for decision making, executive information systems and management information systems. The concept of Business Intelligence has been defined as: Systems of business intelligence combine techniques of collecting data, data warehousing and knowledge management with the help of analytical tools, in order to present the complex internal and competitive information to decision makers. (Negash, 2004). Mission of application of business intelligence is to give support to strategic and operational planning. Its most often use is in management of performances inside company, optimization of relationships with users and creation of reports for management. With the help of techniques and methods of business intelligence, the data has been transferred to useful information, and with the help of analyses of skilled analytics, that useful information has been transferred to knowledge. Business intelligence has been used to understand the possibilities inside the company. The possibilities are modern tendencies, future market positioning and technologies. There are also the steps and behavior of competitive organizations analyzed. Business 21 Intelligence provides that complex data transfer to useful information that is presented as characteristic knowledge for decision makers. The goal is to improve the timeline and data quality during decision making. Business intelligence is the system made of technical and organizational elements that give its users useful information for analysis to make effective decision making and support to management, in order to improve the organizational performances (Isik et al. 2013). Business intelligence continues to be the priority in many organizations and possibilities that provide are useful and interesting to management of companies. Companies fight to use and make logical large amounts of data that generated externally and internally. Business intelligence has become key component to many companies, as well as the topic of research of many academic institutions. Possibilities of business intelligence are critical functions that help organizations to improve performances and adapt to changes. Data mining (Suknovi, Delibai, 2010) is the scientific discipline that has the goal to reveal in data certain rules, models and rules based on decision can be made. Data mining are methods, techniques and algorithms from different fields such as statistics, mathematics, data bases and it has been provided for processing of large amounts of data. Rules and patterns that achieved in this way have been in use later for business decision making, generating new ideas and generally influence to competitiveness of systems. Data mining is the technology that puts together traditional methods for data analysis with sophisticated algorithms that process the large amounts of data and open possibilities for research and analysis of new types of data. In the paper there will be presented the model of business intelligence applied into real problems of modern decision making. The goal of the presented model is the description and the pointing to importance and benefits of concept of business intelligence, its methods and techniques that has in customer relationship management. The goal of the model is the application of business intelligence for creation the headlines for management of companies, in order to increase the efficiency and effectiveness of process of decision making 3. MODEL OF APPLICATION OF BUSINESS INTELLIGENCE BY THE USE OF MODERN SOFTWARE ARCHITECTURE In the paper there is the model of application of business intelligence on real business problem of modern decision making by the use of modern software architecture. Software "Orange" presents very popular data mining tool that serves as help to managers in decision making process. Orange, as very convenient and user-friendly software, has numerous data mining options for data processing, such as creation of model, testing, data visualization, application of model, etc. One of the most important technologies of data mining is CRISP-DM methodology. This methodology consists of following phases: 1. Business understanding 2. Data understanding 3. Data transformation 4. Modeling 5. Evaluation 6. Deployment of model Orange has options for each of this phase of CRISP-DM methodology. In the paper it has been described the example of business problem if the buyers with certain attributes are convenient or not for marketing and CRM activities of companies. It has been shown the preparation of data in order to create the successful model of classification of buyers if they are CRM convenient or not. There is the validation of the project solution, as well as its application in practice. Say Regenerate D. Sed 2000 CD M Figure 1: Desktop of Software Orange with Beginning Step of Data Input