宁波市余姚市智慧工地系统工资预警管理数据

采集宁波市余姚市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：采集宁波市余姚市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%。

This dataset takes salary information within the scope of Yuyao City, Ningbo City as the research object. The original data source is collected offline via equipment and manual entry into the database. Finally, Business Intelligence (BI) tools are used to conduct classified statistics by region and job type, and a line chart is used to visualize the wage risk trend of each region and job type, with the results pushed to team leaders, enterprises, labor service companies and regulatory authorities.

(1) Data Collection: Salary information within the scope of Yuyao City, Ningbo City is collected offline through equipment and manual entry into the database as the original data source.

(2) Data Processing: First, clean the collected salary confirmation data, including records with a salary amount of 0 or null. Then perform the finest-grained aggregation of the data: by day in the time dimension, by enterprise in the project dimension, and by region in the regional dimension. Calculate the total number of salary confirmations for each construction site as X; the proportion of unconfirmed salary workers in total salary payments is calculated as (unconfirmed number)/X. The pending processing count refers to the number of collected but unprocessed records; the processed count refers to the number of records that have started processing; the completed count refers to the number of records with confirmed salary payments; the overdue unprocessed count refers to the number of records that have not been processed for more than 1 day. The following formula holds: X = pending processing count + processed count + completed count.

(3) Data Analysis: Low-risk count: The enterprise's pending processing count accounts for less than 10% of the total and the overdue unprocessed count accounts for less than 5%; Medium-risk count: The enterprise's pending processing count accounts for less than 20% of the total and the overdue unprocessed count accounts for less than 10%; High-risk count: The enterprise's pending processing count accounts for less than 30% of the total and the overdue unprocessed count accounts for less than 15%.

搜集汇总

数据集介绍

特点

该数据集记录了宁波市余姚市智慧工地系统的工资预警管理信息，包含96条数据，每月更新。数据通过设备和手动录入采集，用于监控工地工资发放情况，并通过BI工具进行风险分析和分类统计，支持班组长、企业、劳务公司和监管部门的决策。