宁波市慈溪市智慧工地系统考勤预警数据
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采集宁波市慈溪市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：采集宁波市慈溪市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%。
First, the original data source is established by collecting attendance information within the scope of Cixi City, Ningbo City via offline device recording and manual entry, and storing the data in a database. Then, BI tools are used to conduct classified statistics by region and job type, and line charts are adopted to visualize the attendance risk trends of each region and job type. The analysis results will be pushed to team leaders, enterprises, labor service companies and regulatory authorities. (1) Data Collection: Collect attendance information within the scope of Cixi City, Ningbo City via offline device recording and manual entry, and store the collected data in the database as the original data source. (2) Data Processing: First, clean the collected attendance data, including removing records with 0 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 total number of confirmed attendances for each construction site as X; the proportion of unconfirmed attendance personnel in the total attendance count is (unconfirmed attendance personnel)/X; the number of pending processing refers to the number of collected attendance records that have not yet been processed; the number of processed records refers to the number of attendance records that have started to be processed; the number of completed records refers to the number of attendance records that have been confirmed; the number of overdue unprocessed records refers to the number of records that have not been processed for more than 1 day. In addition, calculate the proportion of absent attendance personnel in the total attendance count as (absent attendance personnel)/X, and the proportion of reissue attendance personnel in the total attendance count as (reissue attendance personnel)/X. (3) Data Analysis: Low-risk count is defined as enterprises where the pending processing count is lower than 10% of the total and the overdue unprocessed count is lower than 5%; medium-risk count is defined as enterprises where the pending processing count is lower than 20% of the total and the overdue unprocessed count is lower than 10%; high-risk count is defined as enterprises where the pending processing count is lower than 30% of the total and the overdue unprocessed count is lower than 15%.
