杭州市拱墅区智慧工地系统工资预警管理数据

采集杭州市拱墅区范围内工资信息线下通过设备和手动录入的方式采集数据到数据库作为原始数据源。最后通过BI工具，按区域工种进行分类统计，利用折线图体现每个地区工种的工资风险走势情况。推送给班组长、企业、劳务公司、监管部门。（1）数据采集：采集杭州市拱墅区范围内工资信息线下通过设备和手动录入的方式采集数据到数据库作为原始数据源。（2）数据处理：首先对采集的工资确认数据进行清洗，包括工资金额为0的或者为null的。然后对数据在时间维度按日，项目维度按企业，区域维度按区域，进行最细级别粒度的聚合。计算得到各工地的工资确认总数量为X，未确认工资人数/X=未确认人数在总工资发放中的占比， 待处理数为已经采集且并未介入处理数， 已处理数为已经开始处理的数量，已完成数为已经确认工资发放的数量，超时未处理数为超时未处理数指超过1天未处理数，X=待处理数+已处理数+已完成数。（3）数据分析: 低危风险数=企业待处理数低于总比10%且超时未处理数低于5%，中危风险数=企业待处理数低于总比20%且超时未处理数低于10%，高危风险数=企业待处理数低于总比30%且超时未处理数低于15%。The original data source is established by offline collecting wage information within Gongshu District, Hangzhou via equipment and manual entry, which is then stored in a database. Subsequently, classification and statistics are conducted by region and occupation using Business Intelligence (BI) tools, and line charts are utilized to visualize the wage risk trends of occupations in each region. The analysis results are delivered to team leaders, enterprises, labor service companies, and regulatory authorities. (1) Data Collection: Wage information within the scope of Gongshu District, Hangzhou is collected offline via equipment and manual entry, and stored in the database as the original data source. (2) Data Processing: First, clean the collected wage confirmation data, including records with a wage amount equal to 0 or null. Then, aggregate the data at the finest granularity: by day in the time dimension, by enterprise in the project dimension, and by region in the regional dimension. Calculate the total number of confirmed wages for each construction site as X; the proportion of unconfirmed wage recipients in total wage payments is equal to (number of unconfirmed wage recipients)/X. Define the following metrics: - Pending processing count: Collected data that has not yet undergone processing - Processed count: Data that has started the processing procedure - Completed count: Data with confirmed wage payments - Overdue unprocessed count: Data that has not been processed for more than 1 day Where X = pending processing count + processed count + completed count. (3) Data Analysis: Define risk levels as follows: - Low-risk count: Enterprises where the pending processing count accounts for less than 10% of total X and the overdue unprocessed count accounts for less than 5% of total X - Medium-risk count: Enterprises where the pending processing count accounts for less than 20% of total X and the overdue unprocessed count accounts for less than 10% of total X - High-risk count: Enterprises where the pending processing count accounts for less than 30% of total X and the overdue unprocessed count accounts for less than 15% of total X

搜集汇总

数据集介绍

特点

杭州市拱墅区智慧工地系统工资预警管理数据集包含33条记录，每月更新，主要用于监控建筑行业工资发放情况，通过BI工具分析工资风险走势，支持班组长、企业、劳务公司和监管部门的决策。