National Big Data for Education mainly aggregates all kinds of education data generated from various regions.

Education is an ultra-complex system that involves teaching, management, teaching and research, services and many other operations. Unlike the financial system, which has a clear, standardized, and consistent business process, the education business in different regions and schools, while having a certain ****, is also very different, and the differences in business directly lead to a more diverse source of education data and more complex data collection.

Education big data arises from a variety of educational practices, including both teaching activities, management activities, scientific research activities, and campus life in campus environments, as well as learning activities in informal environments such as families, communities, museums, libraries, etc.; and both online and offline educational and teaching activities.

The core data sources of big data in education are "people" and "things" -- "people" include The "people" include students, teachers, administrators and parents, and the "things" include information systems, campus websites, servers, multimedia equipment and other educational equipment. Based on the different sources and scope, education big data can be divided into individual education big data, curriculum education big data, class education big data, school education big data, regional education big data, national education big data and so on six kinds.

There are multiple ways to categorize education data:

From the viewpoint of the business source of data generation, it includes teaching data, management data, scientific research data, and service data. From the viewpoint of the technical scene of data generation, it includes the types of perceptual data, business data and Internet data. In terms of the degree of data structuring, it includes structured data, semi-structured data and unstructured data. Structured data is suitable to be stored in two-dimensional tables.

From the point of view of data generation, it includes process data and result data. Process data are data collected during the course of an activity that are difficult to quantify (e.g., classroom interactions, online assignments, web searches, etc.); outcome data are often expressed as some kind of quantifiable result (e.g., grades, grades, quantities, etc.).

The data collected by the state are mainly managerial, structured and result-oriented, focusing on the overall status of education development at the macro level. By the era of big data, the comprehensive collection and in-depth mining and analysis of education data have become increasingly important. The center of gravity of education data collection will shift to unstructured, process data.