According to the Wikipedia, big data “Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate”. In other perceptions, the “4 Vs” that characterize it (i.e., volume, velocity, variety and veracity) or the “5 Vs” (adding versatility to the previous four) are responsible for the fact that on evaluating, planning for, and executing each phase of cloud migration, including the top pros and cons, and key cost, staffing and budgeting factors to consider pre-migration. [29] In essence, big data refers to the situation that more and more aspects and artifacts of everyday life, be it personal or professional, are available in digital form, e.g., personal or company profiles, social network and blog postings, buying histories, health records, to name just a few, that increasingly more data gets dynamically produced especially on the Internet and on the Web, and that nowadays the tools and techniques are available for evaluating and analyzing all that data in various combinations. Numerous companies already foresee the enormous business effects that analytical scenarios based on big data can have, and the impacts that it will hence have on advertising, commerce, and business intelligence (BI). This paper reviews the issues, techniques, and applications of big data, with an emphasis on future BI architectures.