绍兴市越城区智慧工地系统合同预警管理数据

采集绍兴市越城区范围内合同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合同风险走势情况。推送给班组长、企业、劳务公司、监管部门。（1）数据采集：采集绍兴市越城区范围内合同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：首先对采集的合同确认数据进行清洗，包括合同为0的或者为null的。然后对数据在时间维度按年，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。计算各工地的合同确认总数量，已签署数为已经确认合同的数量，待签署数为未确认合同数量， 离职申请中数为已签署合同申请离职中数量，已离职数为已签署合同离职数量，超时未处理数量指合同发起后七天未完成的数量，超时未处理比例=超时未处理数量/总数量，超时未离职数量指提出离职七天未完成数量，超时未离职比例=超时未离职数/已离职数。 （3）数据分析: 低风险数=0%<超时未处理比例<5%、0%<超时未离职比例<5%，中风险数=5%<超时未处理比例<10%、5%<超时未离职比例<10%，高风险数=超时未处理比例>10%、超时未离职比例>10%。

Contract information within Yuecheng District, Shaoxing City was collected into the database via offline device input and manual entry as the original data source. Subsequently, classified statistics were conducted by region and job type using Business Intelligence (BI) tools. A line chart was employed to visualize the contract risk trends of each region and job type, and the results were pushed to team leaders, enterprises, labor service companies and regulatory authorities.

(1) Data Collection: Contract information within Yuecheng District, Shaoxing City was collected into the database via offline device input and manual entry as the original data source.

(2) Data Processing: First, the collected contract confirmation data was cleaned, excluding entries with contract values of 0 or null. Then, the data was aggregated at the finest granularity: by year in the time dimension, by enterprise in the project dimension, and by region in the regional dimension. The following indicators were calculated for each construction site: total number of confirmed contracts; number of signed contracts (i.e., confirmed contracts); number of unsigned contracts (i.e., unconfirmed contracts); number of contracts in ongoing leave application status (i.e., signed contracts with pending leave applications); number of resigned contracts (i.e., signed contracts with completed resignation procedures); number of overtime unprocessed contracts (i.e., contracts that have not been completed within 7 days after initiation); overtime unprocessed ratio = number of overtime unprocessed contracts / total number of contracts; number of overtime unresigned cases (i.e., leave applications that have not been completed within 7 days after submission); overtime unresigned ratio = number of overtime unresigned cases / number of resigned contracts.

(3) Data Analysis: Low-risk count refers to cases where 0% < overtime unprocessed ratio < 5% and 0% < overtime unresigned ratio < 5%; Medium-risk count refers to cases where 5% < overtime unprocessed ratio < 10% and 5% < overtime unresigned ratio < 10%; High-risk count refers to cases where overtime unprocessed ratio > 10% and overtime unresigned ratio > 10%.

搜集汇总

数据集介绍

特点

绍兴市越城区智慧工地系统合同预警管理数据集包含130条记录，每月更新，涵盖项目合同的数量、签署状态、风险等级等信息。数据通过线下采集和手动录入，经过清洗和分类统计后，利用BI工具进行风险分析，推送给相关企业和监管部门。