The course of data analyst includes two levels. Only by studying and applying these courses of data analysts can you become a top big data analyst. 1. The first level of the course: The content of data analysis course is mainly from theory-practice-case application step by step, so that students can fully grasp the basic theory of probability and statistics, skillfully use professional analysis software such as Excel, SPSS, SAS, etc., have good business understanding ability, and can use common data analysis methods to process and analyze data according to business problem indicators, and draw logical business reports. ? The second level: On the basis of the first level, the second level includes modeling analysts and big data analysts, which provides timely, effective, easy to implement and reliable data support for enterprise decision-making. Modeling analyst refers to people who specialize in data analysis and data mining in ZF, finance, telecommunications, retail, Internet, e-commerce, medicine and other industries. This course aims at the whole process of data mining, and deeply teaches the main algorithms of data mining with the case background of finance, telecommunications, e-commerce and retail. The effective combination of SAS Enterprise Miner, SPSS Moderler, SAS programming and SQL will enable students to be competent for all-round data mining application scenarios. Big data analyst, this course is aimed at big data analysis. Starting with the introduction of data analysis, JAVA language and linux operating system, the theoretical knowledge of hadoop, HDFS, MapReduce and Hbase and the ecological environment of hadoop are systematically introduced, and the installation and configuration of three Hadoop modes are demonstrated in detail. In the form of cases, this paper focuses on the clustering, classification and topic recommendation of big data analysis based on mahout project. By showing the actual big data analysis cases, students can understand the real value of big data analysis in a short time and master how to use hadoop architecture in the process of big data analysis, so that students can quickly become big data analysts who pay equal attention to theory and actual combat, thus better adapting to the employment situation with strong demand for big data analysts under the current Internet economy background. ? Second, the knowledge structure of data analysts