Speaking of big data, I think everyone has only heard of the concept, but there is no standard thing about what it is specifically and how to define it, because in our impression, many companies are called big data companies, and the business form is There are hundreds of them, but they are not easy to understand, so I suggest that we should understand big data literally. In "The Era of Big Data" written by Victor Mayer-Schoenberg and Kenneth Cukier, they mentioned 4 aspects of big data. Characteristics:
The first is that the quantity is relatively large. Only the data volume reaches the PB level or above can it be called big data. (Recommended learning: Python video tutorial)
1PB is equal to 1024TB, 1TB is equal to 1024G, then 1PB is equal to 1024*1024 G of data.
The second one is great value.
If you have more than 1PB of online data of all 20-35 young people in the country, then it will naturally have commercial value. For example, by analyzing this data, we will know the hobbies of these people. , and then guide the development direction of products, etc.
If we have the data of millions of patients across the country, we can predict the occurrence of diseases based on analysis of these data. These are the values of big data.
The third one is diversity.
If there is only a single data, then the data has no value. For example, if there is only a single personal data, or a single user submits data, these data cannot be called big data, so it is called big data. It also needs to be diverse.
For example, among current Internet users, everyone has different characteristics such as age, education, hobbies, personality, etc. This is the diversity of big data. Of course, if it is expanded to the whole country, then the diversity of data The data will be more diverse, and there will be a variety of data diversity in every region and every time period.
The fourth one is fast.
The logical processing speed of data through algorithms is very fast. The 1 second rule can quickly obtain high-value information from various types of data. This is also the same as traditional data mining technology. Essentially different.
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