Big data, or huge data, refers to information that is so large in size that it cannot be captured, managed, processed, and organized in a reasonable amount of time by current mainstream software tools for the purpose of helping companies make more positive business decisions. (In Victor Mayer Sch?nberg and Kenneth Cukier's "The Age of Big Data", Big Data refers to the use of all data without using shortcuts such as randomized analysis (sampling).) The 4V characteristics of Big Data: Volume (large volume), Velocity (high speed), Variety (variety), veracity (authenticity). Big Data requires special technologies, including massively parallel processing (MPP) databases, data mining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.

The four "Vs" of big data, or characterized by four dimensions: First, the volume of data is huge. From the terabyte level, jumped to the petabyte level; second, a variety of data types. Second, there are many types of data, such as web logs, videos, pictures, geolocation information, and so on, as mentioned earlier. Third, the source of data, which directly leads to the accuracy and authenticity of the analysis results. If the data source is complete and true, the final analysis results and decisions will be more accurate. Fourth, fast processing speed, the law of 1 second. This last point is also fundamentally different from traditional data mining technology. The industry has summarized it as the 4 "V"

In a way, Big Data is the cutting edge of data analytics. Simply put, the ability to quickly derive valuable information from a wide variety of data types is big data technology. Understanding this is crucial, and it's what gives the technology the potential to move into so many businesses.

Search the various encyclopedias and it's all there. To put it bluntly, the amount of data is enormous. It really has been a hot issue in recent years.