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Big Data has recently been used for many purposes like medicine, marketing and sports. It has helped improve management decisions. However, for almost each case a unique data warehouse should be built to benefit from the merits of data mining and Big Data. Hence, each time we start from scratch to form and build a Big Data Warehouse. In this study, we propose a Big Data Warehouse and a model for universities to be used for information management, to be more specific gossip management. The overall model is a decision support system that may help university administraitons when they are making decisions and also provide them with information or gossips being circulated among students and staff. In the model, unsupervised machine learning algorithms have been employed. A prototype of the proposed system has also been presented in the study. User generated data has been collected from students in order to learn gossips and students’ problems related to school, classes, staff and instructors. The findings and results of the pilot study suggest that social media messages among students may give important clues for the happenings at school and this information may be used for management purposes.The model may be developed and implemented by not only universities but also some other organisations.

<div><p>Data mining technology is one of the new technologies that have become increasingly popular. Data mining enables to form forecasts and models regarding future by making use of past data. It can be costly, risky and time consuming for enterprises to gain knowledge. Firms gain important competitive advantage by data mining methods. This study analyzes on the readiness to implement and the extent of utilization of data mining technologies in the Financial Information Systems (FIS) in Borsa Istanbul and also researches the level of understanding of, perceptions of and readiness to implement data mining technologies within the Borsa Istanbul.  Analysis was undertaken using SPSS. Manufacturing and financial enterprises are the universal of this study. Primary data were obtained by using survey method and questionnaire technique and findings of the study were evaulated. Technological, organisational and human resources issues had a significant role in the decision to, or not to utilize data mining technology. The ability to use data mining technology was found to be increased the performance of the Financial Information System.<strong></strong></p></div>