Evidence-based medicine is important to improve the prognosis of patients with chronic heart failure (CHF). To obtain informative evidence to develop effective treatment for HF, some different types of big data have been accumulated in cardiovascular research area. We have successfully enrolled 10,219 consecutive CHF patients in our Chronic Heart failure Analysis and Registry in the Tohoku District-2 (CHART-2) study. The CHART-2 study is a prospective, observational, and multicenter cohort study to elucidate the characteristics, mortality and prognostic risk of CHF patients in Japan. In this large-scale study, a server computer, which was accessible at any time through internet, was used to build a multicenter clinical research network database. To conduct the CHART-2 study, the Tohoku Heart Failure Association was established in collaboration with 24 hospitals. The database was designed so that the privacy of patients was protected by removing personal information. The collected data were cleaned up for data mining and knowledge discovery. To collect, manage, and analyze the stored data, it was necessary to secure qualified specialists including clinical research coordinators, data managers, and bio-statisticians. These specialists contributed to the design of the study protocol, written informed consent, and data analysis. To make big data from a large-scale cohort study, collaboration with specialists in various areas is important.