What is the content and basic meaning of big data?

"Big data" is a hot word in the IT industry in recent years. The application of big data in various industries has gradually become popular. For example, in the two sessions of 20 14, what we hear most is big data analysis. So, what is big data? What is the concept of big data? How to understand the concept of big data? Let's have a look.

1, the definition of big data. Big data, also known as huge data, refers to the huge amount of data involved, which cannot be captured, managed, processed and arranged by human brains or even mainstream software tools in a reasonable time to help enterprises make more active business decisions.

2. Collection of big data. With the development of science and technology and the Internet, the era of big data is coming, and all walks of life will produce a large number of data fragments every day. Data measurement units have developed from bytes, KB, MB, GB and TB to PB, EB, ZB, YB and even BB, NB and DB. Data collection in the era of big data is no longer a technical problem, but how to find its internal laws in the face of so much data.

3. The characteristics of big data. There are a lot of data, many kinds of data, strong real-time requirements and great value contained in the data. There are big data in all walks of life, but a lot of information and consultation are complex, which requires us to search, process, analyze, summarize and summarize its deep-seated laws.

4. Mining and processing of big data. Big data cannot be calculated and estimated by the human brain, nor can it be processed by a single computer. It must adopt distributed computing architecture, relying on distributed processing, distributed database, cloud storage and cloud computing virtualization technology. Therefore, the mining and processing of big data must use cloud technology.

5. The application of big data. Big data can be applied to all walks of life to analyze and sort out the massive data collected by people and realize the effective use of information. Take this major as an example. For example, to find the major genes related to milk yield at the gene level of dairy cows, we can scan the whole genome of dairy cows first. Although we have obtained all the phenotypic information and genetic information, due to the huge amount of data, we need to use big data technology to analyze, compare and mine the main genes. There are many examples

6. The significance and prospect of big data. In general, big data is a huge, dynamic and sustainable data, which can be mined by using new systems, new tools and new models, thus gaining insight and new value. In the past, faced with huge data, we may be blind, so we can't understand the true nature of things, so we will draw wrong inferences in scientific work. With the advent of the era of big data, all the truth will be presented to us.