宁波市镇海区智慧工地系统考勤预警管理数据

采集宁波市镇海区范围内考勤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考勤风险走势情况。推送给班组长、企业、劳务公司、监管部门。（1）数据采集：采集宁波市镇海区范围内考勤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：首先对采集的考勤数据进行清洗，包括考勤数量为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。计算得到各工地的考勤确认总数量为X，未确认考勤人数/X=未确认人数在总考勤数中的占比， 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考勤的数量，超时未处理数为超时未处理数指超过1天未处理数，缺勤考勤人数/X=缺勤考勤人数在总考勤数中的占比，补卡考勤人数/X=补卡考勤人数在总考勤数中的占比。（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%。

Raw data was collected as attendance information within Zhenhai District, Ningbo City, via offline equipment and manual entry, stored in a database as the original data source. Subsequently, classification statistics were conducted by region and job type using BI tools, with line charts used to visualize the attendance risk trends for each region and job type. The analysis results are pushed to team leaders, enterprises, labor service companies, and regulatory authorities.

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

(2) Data Processing: First, clean the collected attendance data, including removing records with zero or null attendance counts. Then, perform 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 following indicators:
- Total confirmed attendance count for each construction site: X
- Proportion of unconfirmed attendance personnel in total attendance: (Unconfirmed attendance personnel / X)
- Pending processing count: number of collected records that have not yet undergone processing
- Processed count: number of records that have started processing
- Completed count: number of confirmed attendance records
- Overdue unprocessed count: number of records that have not been processed for more than 1 day
- Proportion of absent attendance personnel in total attendance: (Absent attendance personnel / X)
- Proportion of reissued card attendance personnel in total attendance: (Reissued card attendance personnel / X)

(3) Data Analysis: Risk levels are defined as follows:
- Low-risk count: Enterprises where the pending processing count accounts for less than 10% of the total, and the overdue unprocessed count accounts for less than 5% of the total
- Medium-risk count: Enterprises where the pending processing count accounts for less than 20% of the total, and the overdue unprocessed count accounts for less than 10% of the total
- High-risk count: Enterprises where the pending processing count accounts for less than 30% of the total, and the overdue unprocessed count accounts for less than 15% of the total

搜集汇总

数据集介绍

特点

宁波市镇海区智慧工地系统考勤预警管理数据集包含109条记录，每月更新，涵盖项目名称、考勤信息、风险等级等字段。数据通过设备和手动录入采集，经过清洗和聚合处理，用于分析工地考勤风险，并推送给相关管理人员。