Article Directory
16: Customer Domain: Implementation of Customer Theme Analysis
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Goal : Master the needs analysis and realization of customer theme
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path
- step1: Requirements
- step2: Analysis
- step3: Realize
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implement
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need
Field Name field description source sum_install_num Number of installations one_make_dwb.fact_worker_order max_install_num Maximum number of installations one_make_dwb.fact_worker_order min_install_num Minimum quantity to install one_make_dwb.fact_worker_order avg_min_install_num Average number of installs one_make_dwb.fact_worker_order sum_repair_num Repair Quantity one_make_dwb.fact_worker_order max_repair_num Maximum number of repairs one_make_dwb.fact_worker_order min_repair_num Repair Minimum Quantity one_make_dwb.fact_worker_order avg_repair_num Average number of repairs one_make_dwb.fact_worker_order sum_wo_num Number of workers one_make_dwb.fact_worker_order max_sum_wo_num The maximum number of workers one_make_dwb.fact_worker_order min_sum_you_num Minimum number of workers one_make_dwb.fact_worker_order avg_wo_num Average number of dispatched workers one_make_dwb.fact_worker_order am_remould_num Inspection quantity one_make_dwb.fact_worker_order max_remould_num The maximum number of inspections one_make_dwb.fact_worker_order min_remould_num Inspection Minimum Quantity one_make_dwb.fact_worker_order avg_remould_num Average number of inspections one_make_dwb.fact_worker_order sum_alread_complete_num Number of return visits one_make_dwb.fact_worker_order max_alread_complete_num Maximum number of return visits one_make_dwb.fact_worker_order min_alread_complete_num Minimum number of return visits one_make_dwb.fact_worker_order avg_alread_complete_num Average number of return visits one_make_dwb.fact_worker_order dws_day string Date dimension - by day one_make_dws.dim_date dws_week string Date dimension - by week one_make_dws.dim_date dws_month string Date dimension - by month one_make_dws.dim_date oil_type string Gas station type one_make_dws.dim_oilstation oil_province Province of the gas station one_make_dws.dim_oilstation oil_city string City where the gas station belongs one_make_dws.dim_oilstation oil_county string Gas station area one_make_dws.dim_oilstation customer_classify customer type one_make_dws.dim_oilstation customer_province Customer's province one_make_dws.dim_oilstation -
analyze
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index
- Installs, Max Installs, Min Installs, Average Installs
- Number of Repairs, Maximum Number of Repairs, Minimum Number of Repairs, Average Number of Repairs
- The number of dispatched workers, the maximum number of dispatched workers, the minimum number of dispatched workers, and the average number of dispatched workers
- Retrofit Quantity, Maximum Retrofit Quantity, Minimum Retrofit Quantity, Average Retrofit Quantity
- Number of return visits, maximum number of return visits, minimum number of return visits, average number of return visits
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dimension
- Date dimensions: day, week, month
- Gas station dimensions: type, province, city, region
- Customer dimension: type, province
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data
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fact sheet
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fact_worker_order: work order transaction fact table
select install_num,--安装数 repair_num,--维修数 remould_num,--改造数 wo_num,--工单数 alread_complete_num,--完成数，已回访 oil_station_id, --油站id dt --日期 from fact_worker_order;
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dimension table
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dim_oilstation: oil station dimension table
select id,--油站id company_name,--公司名称 province_name,--省份名称 city_name,--城市名称 county_name,--区域名称 customer_classify_name,--客户名称 customer_province_name--客户省份 from dim_oilstation; -
dim_date: time dimension table
select date_id,--天 week_in_year_id,--周 year_month_id --月 from dim_date;
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analyze
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accomplish**
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build table
drop table if exists one_make_st.subj_customer; create table if not exists one_make_st.subj_customer( sum_install_num int comment '安装数量' ,max_install_num int comment '安装最大数量' ,min_install_num int comment '安装最小数量' ,avg_min_install_num decimal(20, 1) comment '安装平均数量' ,sum_repair_num int comment '维修数量' ,max_repair_num int comment '维修最大数量' ,min_repair_num int comment '维修最小数量' ,avg_repair_num decimal(20, 1) comment '维修平均数量' ,sum_wo_num int comment '派工数量' ,max_sum_wo_num int comment '派工最大数量' ,min_sum_wo_num int comment '派工最小数量' ,avg_sum_wo_num decimal(20, 1) comment '派工平均数量' ,sum_remould_num int comment '巡检数量' ,max_remould_num int comment '巡检最大数量' ,min_remould_num int comment '巡检最小数量' ,avg_remould_num decimal(20, 1) comment '巡检平均数量' ,sum_alread_complete_num int comment '回访数量' ,max_alread_complete_num int comment '回访最大数量' ,min_alread_complete_num int comment '回访最小数量' ,avg_alread_complete_num decimal(20, 1) comment '回访平均数量' ,dws_day string comment '日期维度-按天' ,dws_week string comment '日期维度-按周' ,dws_month string comment '日期维度-按月' ,oil_type string comment '油站维度-油站类型' ,oil_province string comment '油站维度-油站所属省' ,oil_city string comment '油站维度-油站所属市' ,oil_county string comment '油站维度-油站所属区' ,customer_classify string comment '客户维度-客户类型' ,customer_province string comment '客户维度-客户所属省' ) comment '客户主题表' partitioned by (month String, week String, day String) stored as orc location '/data/dw/st/one_make/subj_customer' ;
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Construct
insert overwrite table one_make_st.subj_customer partition(month = '202101', week='2021W1', day='20210101') select sum(fwo.install_num) sum_install_num, --安装数量 max(fwo.install_num) max_install_num, --最大安装数量 min(fwo.install_num) min_install_num, --最小安装数量 avg(fwo.install_num) avg_min_install_num, --平均安装数量 sum(fwo.repair_num) sum_repair_num, --维修数量 max((fwo.repair_num)) max_repair_num, --最大维修数量 min(fwo.repair_num) min_repair_num, --最小维修数量 avg((fwo.repair_num)) avg_repair_num, --平均维修数量 sum(fwo.wo_num) sum_wo_num, --派工数量 max(fwo.wo_num) max_sum_wo_num, --最大派工数量 min(fwo.wo_num) min_sum_wo_num, --最小派工数量 avg(fwo.wo_num) avg_wo_num, --平均派工数量 sum(fwo.remould_num) sum_remould_num, --改造数量 max(fwo.remould_num) max_remould_num, --最大改造数量 min(fwo.remould_num) min_remould_num, --最小改造数量 avg(fwo.remould_num) avg_remould_num, --平均改造数量 sum(fwo.alread_complete_num) sum_alread_complete_num, --回访数量 max(fwo.alread_complete_num) max_alread_complete_num, --最大回访数量 min(fwo.alread_complete_num) min_alread_complete_num, --最小回访数量 avg(fwo.alread_complete_num) avg_alread_complete_num, --平均回访数量 dd.date_id dws_day, --日期天 dd.week_in_year_id dws_week, --日期周 dd.year_month_id dws_month, --日期月 dimoil.company_name oil_type, --油站类型 dimoil.province_name oil_province, --油站省份 dimoil.city_name oil_city, --油站城市 dimoil.county_name oil_county, --油站区域 dimoil.customer_classify_name customer_classify, --客户类型 dimoil.customer_province_name customer_province --客户省份 --工单事务事实表 from one_make_dwb.fact_worker_order fwo --日期维度表 left join one_make_dws.dim_date dd on fwo.dt = dd.date_id --油站维度表 left join one_make_dws.dim_oilstation dimoil on fwo.oil_station_id = dimoil.id where dd.year_month_id = '202101'and dd.week_in_year_id = '2021W1' and dd.date_id = '20210101' group by dd.date_id, dd.week_in_year_id, dd.year_month_id, dimoil.company_name, dimoil.province_name, dimoil.city_name, dimoil.county_name, dimoil.customer_classify_name, dimoil.customer_province_name ; -
summary
- Master the needs analysis and implementation of customer topics
17: Material Domain: Topic Model
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Objective : Understand the design model for the material domain topic
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path
- step1: Good product write-off theme model
- step2: Defective product write-off topic model
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implement
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Good product write-off theme model
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Defective product write-off theme model
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summary
- Understanding Design Models for Material Domain Topics
18: DM layer: theme of design and operation department
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Goal : Master the design of the DM layer
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path
- step1: DM layer design
- step2: Operation department theme
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implement
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DM layer design
- Function : data mart layer, used to support the demand for various data of each department
- Source : Extract the data of the DW layer according to certain departmental classifications
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Operations Department Theme
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Requirements : Statistics of operational theme indicators in different dimensions
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accomplish
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Build database
create database if not exists one_make_dm;-
build table
drop table if exists one_make_dm.mart_operation_dept; create table if not exists one_make_dm.mart_operation_dept( wo_id string comment '工单ID' ,userids string comment '工单服务用户ID' ,callaccept_id string comment '来电受理ID' ,oil_station_id string comment '油站ID' ,os_name string comment '油站名称' ,service_total_duration decimal(20,2) comment '服务工时(小时)' ,repair_num bigint comment '维修工单数量' ,wo_num bigint comment '工单数量' ,avg_wo_num int comment '平均工单' ,sum_os_online int comment '加油机在线设备总数' ,atu_num_rate decimal(5,2) comment '客户回访满意度率' ,rtn_visit_duration decimal(20,2) comment '来电受理时长(小时)' ,dws_day string comment '日期维度-按天' ,dws_week string comment '日期维度-按周' ,dws_month string comment '日期维度-按月' ) comment '运营部数据集市表' partitioned by (month String, week String, day String) stored as orc location '/data/dw/dm/one_make/mart_operation_dept';
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Construct
insert overwrite table one_make_dm.mart_operation_dept partition(month = '202101', week='2021W1', day='20210101') select fwo.wo_id --工单id , max(fwo.userids) userids --工程师id , max(fwo.callaccept_id) callaccept_id --来电受理id , max(fwo.oil_station_id) oil_station_id --油站id , max(fos.os_name) os_name --油站名称 , max(fwo.service_total_duration) service_total_duration --服务工时 , sum(fwo.wo_num) wo_num --维修工单数量 , count(fos.os_id) sum_os_num --工单数量 , avg(fwo.wo_num) avg_wo_num --平均工单 , sum(fos.valid_os_num) sum_os_online --加油机在线设备总数 , max(fsrv.srv_atu_num / (fsrv.srv_atu_num + fsrv.srv_bad_atu_num)) atu_num_rate --客户回访满意度 , max(fcs.interval / 3600.0) rtn_visit_duration --来电受理时长 , dd.date_id dws_day --日期天 , dd.week_in_year_id dws_week --日期周 , dd.year_month_id dws_month --日期月 --工单事务事实表 from one_make_dwb.fact_worker_order fwo --油站事务事实表 left join one_make_dwb.fact_oil_station fos on fwo.oil_station_id = fos.os_id --回访事务事实表 left join one_make_dwb.fact_srv_rtn_visit fsrv on fwo.wo_id = fsrv.wrkodr_id --呼叫中心事务事实表 left join one_make_dwb.fact_call_service fcs on fwo.callaccept_id = fcs.id --日期维度表 left join one_make_dws.dim_date dd on fwo.dt = dd.date_id where dd.year_month_id = '202101'and dd.week_in_year_id = '2021W1' and dd.date_id = '20210101' group by fwo.wo_id, dd.date_id, dd.week_in_year_id, dd.year_month_id;
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summary
- Master the design of the DM layer