求职招聘系统企业招聘情况总结分析数据
收藏资源简介：
通过对企业招聘岗位和行为，以及应聘者的行为分析总结，对企业招聘活跃度和效果进行总结评价，有助于企业对招聘数据和效果，及时跟进招聘情况。数据收集：通过公司招聘平台对后台数据进行提取，提取企业沟通，登入，被浏览，面试邀约等数据，将其存储在数据库中。 数据清洗和预处理：对收集到的数据进行清洗和预处理，包括去重、去噪声、标准化等。 数据分析：通过统计分析。从企业活跃度和招聘效果两方面进行总结分析，企业活跃度=企业登入次数*k1+面试邀约次数*k2+浏览简历次数*k3，招聘效果=被浏览次数*k4+应聘投递量*k5+沟通人数*k6，K为权重，采用主观赋权法，分值越高企业的活跃度和招聘效果越好。 数据可视化：将分析结果通过图表的形式呈现，便于管理层或HR部门快速了解公司招聘状况，对公司招聘进行总结。
This dataset is developed based on the analysis of enterprise recruitment positions, related behaviors and applicant behaviors, aiming to summarize and evaluate the recruitment activity level and effectiveness of enterprises, which helps enterprises timely track their recruitment status based on recruitment data and outcomes. Data Collection: Extract backend data from the company's recruitment platform, including data on enterprise communication, login, resume views, interview invitations, etc., and store the extracted data in a database. Data Cleaning and Preprocessing: Clean and preprocess the collected data, including operations such as deduplication, noise removal and standardization. Data Analysis: Conduct summary analysis from two dimensions, namely enterprise recruitment activity level and recruitment effectiveness, through statistical analysis. The specific calculation formulas are as follows: Enterprise Recruitment Activity Level = Number of Logins × k1 + Number of Interview Invitations × k2 + Number of Resume Views × k3; Recruitment Effectiveness = Number of Resume Views × k4 + Number of Application Submissions × k5 + Number of Contacted Candidates × k6. Here, k represents the weight coefficients, which are determined by the subjective weighting method. The higher the calculated score, the better the enterprise's recruitment activity and effectiveness. Data Visualization: Present the analysis results in the form of charts, so that management or HR departments can quickly grasp the company's recruitment status and conduct a comprehensive summary of the enterprise's recruitment work.
