What is big data? What are its characteristics?

1. Big Data (Big Data), also known as huge data, refers to the massive, high growth rate and diversity that require new processing models to have stronger decision-making power, insight and process optimization capabilities. information assets.

2. Features: Compared with traditional data warehouse applications, big data analysis has the characteristics of large data volume and complex query analysis.

2. The concept of "big data" was first proposed by Victor Meyer Schonberger and Kenneth Cukier in the "Big Data Era", which refers to the use of random analysis methods (sampling surveys) ), but uses all data for analysis and processing. Big data has 4V characteristics, namely Volume, Velocity, Variety, and Value.

3. Gartner, a research institute for “big data”, has given a definition. “Big data” requires new processing models to have stronger decision-making power, insight discovery and process optimization capabilities. massive, high-growth and diversified information assets. The strategic significance of big data technology lies not in mastering huge data information, but in professional processing of these meaningful data. In other words, if big data is compared to an industry, then the key to making this industry profitable is to improve the "processing capabilities" of data and achieve the "value-added" of data through "processing".

4. From a technical point of view, the relationship between big data and cloud computing is as inseparable as the two sides of the same coin. Big data cannot be processed by a single computer and must use a distributed architecture. Its characteristic lies in distributed data mining of massive data, but it must rely on distributed processing, distributed database and cloud storage, and virtualization technology of cloud computing.

5. With the advent of the cloud era, big data (Big data) has also attracted more and more attention. The analyst team of "Zhu Yuntai" believes that big data (Big data) is usually used to describe the large amount of unstructured data and semi-structured data created by a company. This data will cost a lot of money when downloaded to a relational database for analysis. Too much time and money. Big data analytics is often associated with cloud computing because real-time analysis of large data sets requires frameworks like MapReduce to distribute work to tens, hundreds, or even thousands of computers.