Previously, we are concerned about the transaction system and business system data generated by the data warehouse to analyze and display, in fact, the terminal, especially individuals, a variety of water operations, such as the list of purchases, Internet browsing history, photos, microblogging and so on, but do not pay attention to, and the era of big data, more attention to the large amount of data, the expectation that analyze these data to find value, so big data! In fact, before the system, terminal, personal and so on are in the generation, just did not take advantage of it, and now want to analyze these data to find value from it.

When the volume of data, the complexity of data, data processing tasks require more than the traditional data storage and computing capabilities, called "big data (phenomenon)". Visible, computer science and technology is from the perspective of storage and computing power to understand "big data" - big data is not only "data stock" problem, but also involves the "data increment". It is also about "incremental data", complexity, and processing requirements (e.g., real-time analytics).

Big Data, also known as Big Data, refers to massive, high-growth, and diverse information assets that require new processing paradigms to enable greater decision-making, insight, and process optimization. The concept of "Big Data" was first introduced by Viktor Mayer Sch?nberg and Kenneth Kukier in their book "The Age of Big Data", which refers to the use of all data for analyzing and processing without taking the shortcut of random analysis (sampling). Big Data is characterized by 4Vs, namely Volume, Velocity, Variety, and Value.