1. Different types. Credit information is shared by peers. Big data judges massive data and user information from multiple dimensions such as security, wealth and compliance, and then establishes a credit report.
2. Advantages and disadvantages. The problems faced by the credit model are incomplete data, no initiative in uploading data, untimely update and high entry threshold, but the data is accurate, reliable and authoritative. The big data model has a wide range of data sources, which makes up for the lack of credit information, but the data types are diversified, and there may be interference information, which affects the accuracy of judgment. In addition, big data obtained through some channels also faces legal risks, and personal privacy protection is difficult to control.
Big data includes structured, semi-structured and unstructured data, and unstructured data is increasingly becoming the main part of data. According to IDC's investigation report, 80% of the data in an enterprise is unstructured data, and these data increase exponentially by 60% every year. Big data is just a representation or feature of the development of the Internet at this stage. There is no need to myth it or keep it in awe. Under the background of technological innovation represented by cloud computing, these data, which seemed to be difficult to collect and use, began to be used easily. Through continuous innovation in all walks of life, big data will gradually create more value for mankind.
Secondly, in order to understand big data systematically, we must decompose it comprehensively and carefully, starting from three levels:
The first level is theory, which is the only way of cognition and the baseline that is widely recognized and spread. Here, we can understand the overall description and characterization of big data by the industry from the definition of its characteristics; From the discussion of the value of big data, deeply analyze the preciousness of big data; Insight into the development trend of big data; This paper examines the long-term game between people and data from the special and important perspective of big data privacy.
The second level is technology, which is the means to reflect the value of big data and the cornerstone of progress. From the development of cloud computing, distributed processing technology, storage technology and sensing technology, this paper expounds the whole process of big data from collection, processing and storage to the formation of results.
The third level is practice, and practice is the ultimate value embodiment of big data. Here, we describe the beautiful scenes that big data has shown and the blueprint that will be realized from four aspects: Internet big data, government big data, enterprise big data and personal big data.