数据挖掘，是提升教师数据智慧过程中最重要的阶段。数据决策的确需要依靠统

数据挖掘，是提升教师数据智慧过程中最重要的阶段。数据决策的确需要依靠统计学、数据挖掘的方法等，这些作为数据分析的方法，成为学校数据团队的技术工具。学校管理人员和教师应该理解数据挖掘和学习分析的方法在实践中是如何展开的，并以此确立学习者中心问题。教师进行数据挖掘依托于对于大数据核心技术的掌握。“大数据的核心技术包括大规模并行处理数据库、分布式文件系统、分布式数据库、云计算平台、互联网和可扩展的存储系统”。教师通过挖掘学校中的数据，发现学生学习过程或者教师教学过程中普遍存在的问题，这是依据数据进行教学决策的前提。

Data mining is the most important stage in the process of improving teachers' data intelligence. Data decision-making does need to rely on statistics, data mining methods, etc. as data analysis methods, these have become the technical tools of the school data team. School administrators and teachers should understand how the methods of data mining and learning analysis are carried out in practice, so as to establish learner centered problems. Teachers' data mining relies on mastering the core technology of big data. "The core technologies of big data include large-scale parallel processing database, distributed file system, distributed database, cloud computing platform, Internet and scalable storage system". Teachers find the common problems in students' learning process or teachers' teaching process by mining the data in the school, which is the premise of teaching decision-making based on the data.

Data mining is the most important stage in the process of improving teachers' data wisdom. Data decision-making really needs to rely on statistics and data mining methods, etc. As data analysis methods, these become technical tools of school data teams. School administrators and teachers should understand how the methods of data mining and learning analysis are developed in practice, so as to establish the learner-centered problem. Teachers' data mining depends on mastering the core technologies of big data. "The core technologies of big data include large-scale parallel processing database, distributed file system, distributed database, cloud computing platform, Internet and scalable storage system". Teachers discover common problems in students' learning process or teachers' teaching process by mining data in schools, which is the premise of making teaching decisions based on data.