Big data (English: big data), also known as huge data, refers to the term to change the large or complex data sets that are not sufficiently applied in traditional data processing.
Data can also be defined as a large amount of unstructured or structured data from various sources. From an academic point of view, the emergence of big data has promoted novel research on a wide range of topics. This has also led to the development of various statistical methods of big data. There is no statistical sampling method for big data; It just observes and tracks what happens.
Therefore, big data usually contains more data than traditional software can handle in an acceptable time. Due to the recent technological progress, the convenience of releasing new data and the requirements of most governments around the world for high transparency of finger ridges, big data analysis is becoming more and more prominent in modern research.
Doug Laney, an analyst at META Group (now Gartner), pointed out in a research and related speech on 200 1 that the challenges and opportunities of data growth have three directions: quantity, speed and diversity. Gartner Nuclear and most companies in the big data industry continue to use 3V to describe big data.
Gartner revised the definition of big data in 20 12: "Big data is a huge, high-speed and/or changeable information asset, which needs new processing methods to promote stronger decision-making ability, insight and optimal processing." In addition, some organizations define the fourth V: authenticity as the fourth feature other than 3V.
Big data must be counted, compared and analyzed by computers in order to get objective results. The United States began to launch big data in 20 12, and Obama invested 200 million dollars to develop big data in the same year, emphasizing that big data will be the oil of the future. Data mining is to explore ways to analyze big data.