Introduction2. Big Data, Data Mining and Predictive Analytics Applications For the development of Big Data, Data Mining and Predictive Analytics applications, different methodologies and techniques have been generated in various fields aimed at the control and post-analysis of information-data. Such methodologies and techniques allow for better use of information data to solve a specific problem. Some fields in which Big Data has developed, both in the public and private sectors, are healthcare and science, economics, business and management. Taking these into account, we can define and classify the following applications:Figure1. Applications of Big Data, Data Mining and Predictive Analytics 2.1 Marketing and Sales Application Data warehousing, data mining and customer relationship management (CRM) tools have improved companies' ability to create and build relationships with customers. For sales managers, data mining can evaluate sales performance by product type, distribution channels and geographic regions. Combined with other variables, such as demographics or purchasing behavior, this data can also be used to predict which products are likely to perform well in certain markets (Hair, 2007). For retailers, Big Data comes from many sources: point of sale, radio frequency identification (RFID) devices, online clickstream patterns, etc. With the help of predictive analytics models, this data becomes useful for various decisions in inventory control, store layout, merchandise assortment, and so on (Hair, 2007).For advertisers, Data Mining it can turn into a valuable tool with the new emerging media of the Internet, blogs, podcasts, and search ads (as opposed to traditional media, such as television, radio, or newspapers). The increase...... middle of the paper ......re Fawcett, 2013).2.4 Service Operations Analytics ApplicationsBig Data, predictive analytics and data mining have other important applications that do not incorporate a direct impact on managerial strategy in a company; however, they represent a significant tool in society. These include the effective use of Big Data in astronomy (e.g., the Sloan Digital Sky Survey of telescopic information), in politics (e.g., a political campaign focusing on people who are most likely to support a candidate based on social networks or web searches) (Murdoch and Detsky, 2013) and education, where Data Mining offers educational institutions additional approaches to improve student graduation rates, student success and learning outcomes, through prediction, cluster analysis, association and classification using information-data computer tools (Beikzadeh, Phon-Amnuaisuk and Delavari, 2008).