大数据环境下信息管理与信息系统专业就业需求的变化及人才培养模式研究

Research on Multi-level Talents Cultivation Model And Changes in Employment Requirements of Information Management and Information System Specialty in Big Data Environment

本研究基于诺兰模型分析信息管理与信息系统专业(以下简称,信管)就业市场变化及相应的人才需求,针对信息管理与信息系统专业多学科交叉融合的特点,提出现阶段大数据分析环境下信管专业多层次人才培养模式。在此基础上利用Apriori关联规则算法重点分析各层次人才课程成绩的关联性,提出大数据时代下信管专业多层次人才核心课程群建设方案,以提高信管专业人才的市场竞争能力。

This study is based on the Nolan model analysis of the information management and information system （herein referred to as the ＂credit management＂） job market changes and the corresponding talent demand, focusing on the characteristics of multidisciplinary integration of information management and information systems, to raise the stage of the emergence of big data analysis environment Information management professional multi-level personnel training model. On this basis, the Apriori association rule algorithm is used to analyze the relevance of the achievements of talents at all levels, and a multi-level talents core curriculum group construction plan for the letter management professional under the age of big data is proposed to improve the market competitiveness of the professional talents of information management.