摘要
对水利水电行业企业而言,人员种类多样化,管理、技术等人力资源薪酬多元化,企业应构建基于Hadoop和Kafka的数据湖平台,整合内外部薪酬数据;利用机器学习算法优化多样化的薪酬决策模型;采用云原生微服务架构和服务网格技术,提高系统安全性和互操作性等。通过上述技术驱动路径与策略,可显著提升水利水电工程建设企业薪酬管理的精准化、自动化和制度化水平。
For enterprises in the water conservancy and hydropower industry,which have diverse personnel types and varied human re-sources compensation such as management and technology,it is recommended to build a data lake platform based on Hadoop and Kafka to integrate internal and external salary data.Machine learning algorithms can be utilized to optimize diverse salary decision-making models,while cloud-native microservices architecture and service mesh technology can enhance system security and interoperability.Through the a-bove technology-driven path and strategies,the precision,automation,and institutionalization of salary management in water conservancy and hydropower engineering construction enterprises can be significantly improved.
作者
周晶晶
肖阳
Zhou Jingjing;Xiao Yang(Power China Vibroflotation Construction Engineering Co.,Ltd.,Beijing,100000;Hubei Institute of Water Resources Survey and Design Co.,Ltd.,Wuhan,Hubei,430070)
出处
《市场周刊》
2024年第23期187-190,共4页
Market Weekly
关键词
大数据
人力资源管理
薪酬模型
数据隐私保护
big data
human resource management
salary model
data privacy protection