WO2018202176A1 - 多维度数据对账方法及系统 - Google Patents

多维度数据对账方法及系统 Download PDF

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WO2018202176A1
WO2018202176A1 PCT/CN2018/085730 CN2018085730W WO2018202176A1 WO 2018202176 A1 WO2018202176 A1 WO 2018202176A1 CN 2018085730 W CN2018085730 W CN 2018085730W WO 2018202176 A1 WO2018202176 A1 WO 2018202176A1
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data
reconciliation
dimensional
monitoring party
public platform
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French (fr)
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曾芳
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Ping An Technology Shenzhen Co Ltd
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Ping An Technology Shenzhen Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/12—Accounting

Definitions

  • the present application relates to the field of data management technologies, and in particular, to a multi-dimensional data reconciliation method and system.
  • the purpose of the present application is to provide a multi-dimensional data reconciliation method and system to solve the problem that multi-dimensional data reconciliation is difficult and time-consuming.
  • the present application provides a multi-dimensional data reconciliation method, the method comprising the steps of:
  • At least one data provider sends the first data to a public platform
  • the public platform records the first data
  • the data extractor extracts data from the public platform, and the extracted data is second data;
  • the monitoring party reconciles whether the second data is the same as the first data.
  • the present application also provides a multi-dimensional data reconciliation system, the system comprising:
  • At least one data provider for transmitting the first data to a public platform
  • the public platform is configured to receive and record the first data
  • a data extracting party configured to extract data from the public platform, and the extracted data is second data
  • the monitoring party is configured to reconcile whether the second data is the same as the first data.
  • the multi-dimensional data reconciliation method and system of the present application the first data is sent to the public platform by at least one data provider, the common platform records the first data, and the data extractor extracts data from the common platform The extracted data is the second data.
  • the monitoring party reconciles the second data with the first data, the reconciliation is successful.
  • the multi-dimensional data reconciliation method of the present application can ensure the correctness and integrity of the synchronous data, ensure that the abnormal data can be processed in time, and ensure that the erroneous data does not enter other processes and cause errors.
  • FIG. 1 is a flowchart of a multi-dimensional data reconciliation method according to a first embodiment of the present application
  • FIG. 2 is a flowchart of a multi-dimensional data reconciliation method according to a second embodiment of the present application.
  • FIG. 3 is a flowchart of a multi-dimensional data reconciliation method according to a third embodiment of the present application.
  • FIG. 4 is a schematic block diagram of a multi-dimensional data reconciliation system according to a fourth embodiment of the present application.
  • the first embodiment of the present application provides a multi-dimensional data reconciliation method, and the method includes the following steps:
  • the at least one data provider sends the first data to the public platform.
  • the professional company that pushes data in this embodiment is referred to as a data provider.
  • Each professional company is responsible for different products, salesmen and work content. Different professional companies regularly push multi-dimensional data to the public platform.
  • Multiple data providers periodically push data to the public platform and record multi-dimensional reconciliation data in the common platform reconciliation table.
  • the push data includes key indicators such as data volume, total premium, and total commission value.
  • the data provider uses a synchronization tool to send the data to the public platform.
  • the data transmitted by the data provider is referred to as first data.
  • the synchronization tool may adopt an Extract-Transform-Load (ETL), or may be a cross-database synchronization tool TJS or the like.
  • ETL Extract-Transform-Load
  • the data provider can push the data according to the time period, or push the data from time to time.
  • the public platform records the first data.
  • the public platform saves the first data to the database.
  • the Oracle database is used.
  • various databases such as PostgreSQL and MySQL may also be used.
  • the data extractor extracts data from the public platform, and the extracted data is second data.
  • a professional company that extracts data is referred to as a data extractor.
  • the data extractor extracts the data from the data recorded by the common platform, and the extracted data is referred to as the second data. It can be understood by those skilled in the art that the second data may or may not be the first data.
  • the monitoring party reconciles whether the second data is the same as the first data. If so, the flow ends, and if not, the process proceeds to S150.
  • the monitoring party compares whether the second data is the same as the first data according to the specific frequency, and specifically compares whether all the indicators in the second data and all the indicators in the first data are identical, and if they are the same, If the reconciliation is correct, other processes, such as a commission calculation process, may be performed. If not, the process proceeds to S150.
  • the email is sent to the development and operation and maintenance, and the problem is searched in advance to avoid affecting the subsequent process.
  • Life Insurance D synchronizes the performance data N of professional companies A and B from the public platform to the eight life insurance institutions, and records the reconciliation data of each institution, such as the amount of data, on the public platform. Key indicators such as total premiums and total commission values.
  • the first data is sent to the public platform by the at least one data provider, the common platform records the first data, and the data extractor extracts data from the common platform, and the extracted data
  • the data is the second data, and when the monitoring party reconciles the second data with the first data, the reconciliation is successful.
  • the second embodiment of the present application proposes a multi-dimensional data reconciliation method.
  • the steps of the multi-dimensional data reconciliation method are similar to those of the first embodiment, the main difference being that S240-S250 is added on the basis of the first embodiment.
  • the method specifically includes the following steps:
  • the at least one data provider sends the first data to the public platform.
  • the professional company that pushes data in this embodiment is referred to as a data provider.
  • Each professional company is responsible for different products, salesmen and work content. Different professional companies regularly push multi-dimensional data to the public platform.
  • Multiple data providers periodically push data to the public platform and record multi-dimensional reconciliation data in the common platform reconciliation table.
  • the push data includes key indicators such as data volume, total premium, and total commission value.
  • the data provider uses a synchronization tool to send the data to the public platform.
  • the data transmitted by the data provider is referred to as first data.
  • the synchronization tool may adopt an Extract-Transform-Load (ETL), or may be a cross-database synchronization tool TJS or the like.
  • ETL Extract-Transform-Load
  • the data provider can push the data according to the time period, or push the data from time to time.
  • the public platform records the first data.
  • the public platform saves the first data to the database.
  • the Oracle database is used.
  • various databases such as PostgreSQL and MySQL may also be used.
  • the data extractor extracts data from the public platform, and the extracted data is second data.
  • a professional company that extracts data is referred to as a data extractor.
  • the data extractor extracts the data from the data recorded by the common platform, and the extracted data is referred to as the second data. It can be understood by those skilled in the art that the second data may or may not be the first data.
  • the data extractor synchronizes the second data to at least one branch.
  • life insurance regularly synchronizes the performance data of each professional company from the public platform to the eight life insurance institutions, and records the reconciliation data of each institution on the public platform, such as data volume and total premium. Key information such as total commission value.
  • the public platform also has key indicators for professional companies to push data to the public platform, and key indicators for life insurance to synchronize from the public platform to the data.
  • the monitoring party acquires the first data and the second data from the public platform.
  • the monitoring party reconciles whether the second data is the same as the first data. If so, the flow ends, and if not, the process proceeds to S270.
  • the monitoring party compares whether the second data is the same as the first data according to the specific frequency, and specifically compares whether all the indicators in the second data and all the indicators in the first data are identical, and if they are the same, If the reconciliation is correct, other processes, such as a commission calculation process, may be performed. If not, the process proceeds to S270.
  • the email is sent to the development and operation and maintenance, and the problem is searched in advance to avoid affecting the subsequent process.
  • the multi-dimensional data reconciliation method of the present application has at least the following three meanings: 1. ensuring the correctness and integrity of the synchronous data; 2. ensuring that abnormal data can be processed in time; 3. ensuring that erroneous data does not enter other processes. Causes an error.
  • the third embodiment of the present application proposes a multi-dimensional data reconciliation method.
  • the steps of the multi-dimensional data reconciliation method are similar to those of the first embodiment, the main difference being that S250 in the second embodiment specifically includes S350-S360.
  • the method specifically includes the following steps:
  • the at least one data provider sends the first data to the public platform.
  • the professional company that pushes data in this embodiment is referred to as a data provider.
  • Each professional company is responsible for different products, salesmen and work content. Different professional companies regularly push multi-dimensional data to the public platform.
  • Multiple data providers periodically push data to the public platform and record multi-dimensional reconciliation data in the common platform reconciliation table.
  • the push data includes key indicators such as data volume, total premium, and total commission value.
  • the data provider uses a synchronization tool to send the data to the public platform.
  • the data transmitted by the data provider is referred to as first data.
  • the synchronization tool may adopt an Extract-Transform-Load (ETL), or may be a cross-database synchronization tool TJS or the like.
  • ETL Extract-Transform-Load
  • the data provider can push the data according to the time period, or push the data from time to time.
  • the public platform records the first data.
  • the public platform saves the first data to the database.
  • the Oracle database is used.
  • various databases such as PostgreSQL and MySQL may also be used.
  • the data extractor extracts data from the public platform, and the extracted data is second data.
  • a professional company that extracts data is referred to as a data extractor.
  • the data extractor extracts the data from the data recorded by the common platform, and the extracted data is referred to as the second data. It can be understood by those skilled in the art that the second data may or may not be the first data.
  • the data extractor synchronizes the second data to at least one branch.
  • life insurance regularly synchronizes the performance data of each professional company from the public platform to the eight life insurance institutions, and records the reconciliation data of each institution on the public platform, such as data volume and total premium. Key information such as total commission value.
  • the public platform also has key indicators for professional companies to push data to the public platform, and key indicators for life insurance to synchronize from the public platform to the data.
  • the monitoring party acquires the first data and the second data from the common platform according to the specific frequency.
  • the monitoring party acquires the first data and the second data from the common platform according to a specific frequency
  • the specific frequency may refer to a cycle frequency, a time range, a number of times, and the like.
  • the cycle frequency can be: day, month, and the like. That is, the monitoring party views the first data and the second data separately or simultaneously in units of days or months.
  • the time range may be a time range of a fixed cycle frequency, for example, within a time range of 10:00 to 10:00 every day, the first data and the second data are separately or simultaneously viewed.
  • the number of times refers to each time the data provider sends the data, and the data extractor extracts the data once as one.
  • the data provider and the data sender complete the data transmission and extraction actions once, and the monitoring party views the first data and the second data.
  • the monitoring party reconciles whether the second data is the same as the first data. If so, the flow ends, and if not, the process proceeds to S380.
  • the monitoring party compares whether the second data is the same as the first data according to the specific frequency, and specifically compares whether all the indicators in the second data and all the indicators in the first data are identical, and if they are the same, If the reconciliation is correct, other processes, such as a commission calculation process, may be performed. If not, the process proceeds to S380.
  • the email is sent to the development and operation and maintenance, and the problem is searched in advance to avoid affecting the subsequent process.
  • the multi-dimensional data reconciliation method of the embodiment by setting a specific frequency, and the monitoring party acquires the first data and the second data from the common platform according to the specific frequency, and then performs subsequent reconciliation of the second data and the first data, It can guarantee the correctness and integrity of the synchronized data, ensure that abnormal data can be processed in time, and ensure that the wrong data does not enter other processes and cause errors.
  • the fourth embodiment of the present application proposes a multi-dimensional data reconciliation system.
  • the multi-dimensional data reconciliation system includes at least one data provider 410, a public platform 420, a data extractor 430, and a monitoring party 440. among them,
  • At least one data provider 410 for transmitting the first data to the public platform.
  • the professional company that pushes data in this embodiment is referred to as a data provider 410.
  • Each professional company is responsible for different products, salesmen and work content. Different professional companies regularly push multi-dimensional data to the public platform.
  • the plurality of data providers 410 periodically push the data to the public platform 420, and record the multi-dimensional reconciliation data in the common platform 420 reconciliation table, and the push data includes key indicators such as the amount of data, the total premium, and the total commission value.
  • the data provider uses a synchronization tool to send the data to the public platform.
  • the data transmitted by the data provider 410 is referred to as first data.
  • the synchronization tool may adopt an Extract-Transform-Load (ETL), or may be a cross-database synchronization tool TJS or the like.
  • ETL Extract-Transform-Load
  • the data provider 410 may push the data in a time period or push the data from time to time.
  • the public platform 420 records the first data.
  • the public platform 420 saves the first data to the database.
  • the Oracle database is used.
  • various databases such as PostgreSQL and MySQL may also be used.
  • the data extracting party 430 is configured to extract data from the common platform 420, and the extracted data is second data.
  • a professional company that extracts data is referred to as a data extractor 430.
  • the data extracting party 430 extracts data from the public platform 420, and the extracted data is referred to as the second data. It can be understood by those skilled in the art that the second data may or may not be the first data.
  • the monitoring party 440 is configured to reconcile whether the second data is the same as the first data.
  • the monitoring party 440 compares whether the second data is the same as the first data according to the specific frequency, and specifically compares whether all the indicators in the second data and all the indicators in the first data are identical. If they are the same, then If the reconciliation is correct, you can perform other processes, such as the commission calculation process.
  • the system reports an error.
  • the email is sent to the development and operation and maintenance, and the problem is searched in advance to avoid affecting the subsequent process.
  • the data extracting party 430 is further configured to synchronize the second data to at least one branching mechanism.
  • the life insurance regularly synchronizes the performance data of each professional company from the public platform 420 to the eight life insurance institution libraries, and records the reconciliation data of each institution, such as the amount of data, on the public platform 420. Key information such as total premiums and total commission values.
  • the public platform 420 has both key indicators for professional companies to push data to the public platform, and key indicators for life insurance to synchronize from the public platform to the data.
  • the monitoring party 440 is further configured to acquire the first data and the second data from the common platform 420.
  • the monitoring party 440 is specifically configured to set a specific frequency, and acquire the first data and the second data from the common platform 420 according to the specific frequency, where the specific frequency includes a periodic frequency, a time range, and a number of times.
  • the monitoring party 440 acquires the first data and the second data from the common platform 420 according to a specific frequency, which may refer to a periodic frequency, a time range, a number of times, and the like.
  • the cycle frequency can be: day, month, and the like. That is, the monitoring party 440 views the first data and the second data separately or simultaneously in units of days or months.
  • the time range may be a time range of a fixed cycle frequency, for example, within a time range of 10:00 to 10:00 every day, the first data and the second data are separately or simultaneously viewed.
  • the number of times refers to the data sent by the data provider once and the data extractor extracts the data once per time.
  • the monitor 440 views the first data and the second data every time the data provider 410 and the data sender 430 complete the data transmission and extraction operations.
  • Life Insurance D synchronizes the performance data N of professional companies A and B from the public platform to the eight life insurance institutions, and records the reconciliation data of each institution, such as the amount of data, on the public platform. Key indicators such as total premiums and total commission values.
  • the multi-dimensional data reconciliation system of the present application transmits the first data to the public platform 420 via at least one data provider 410, the common platform 420 recording the first data, and the data extractor 430 from the common platform 420
  • the data is extracted, and the extracted data is the second data.
  • the monitoring party 440 reconciles the second data with the first data, the reconciliation is successful.
  • the multi-dimensional data reconciliation system of the present application the correctness and integrity of the synchronous data can be ensured, the abnormal data can be processed in time, and the erroneous data can be prevented from entering other processes and causing errors.
  • the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and can also be implemented by hardware, but in many cases, the former is A better implementation.
  • the technical solution of the present application which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
  • the optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present application.

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Abstract

本申请公开了一种多维度数据对账方法及系统，该方法包括：至少一个数据提供方将第一数据发送至公共平台；公共平台记录所述第一数据；数据提取方从所述公共平台中提取数据，提取的数据为第二数据；当监控方对账第二数据与第一数据相同时，则对账成功。通过本申请的多维度数据对账方法及系统，可以保证同步数据的正确性和完整性、保证出现异常数据能够及时处理、以及保证错误的数据不会进入其他流程而导致错误。

Description

多维度数据对账方法及系统
本申请要求于2017年5月5日提交中国专利局，申请号为2017103128068、发明名称为“多维度数据对账方法及系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及数据管理技术领域，尤其涉及多维度数据对账方法及系统。
背景技术
当前，由于保险行业的综合开拓业务量巨大，业务员及综拓专员佣金计算过程中依赖大量的其它专业公司的业绩数据，主要来自产险、健康险和养老险。现有的系统每日从专业公司同步业绩数据，因数据量庞大，难以核对同步程序异常或者数据异常造成的数据遗漏。如果人工核对，则难度较大，耗时长。
发明内容
有鉴于此，本申请的目的在于提供一种多维度数据对账方法及系统，以解决多维度数据对账难道大、耗时长的问题。
为实现上述目的，本申请提供一种多维度数据对账方法，该方法包括步骤：
至少一个数据提供方将第一数据发送至公共平台；
所述公共平台记录所述第一数据；
数据提取方从所述公共平台中提取数据，提取的数据为第二数据；
监控方对账所述第二数据是否与所述第一数据相同。
为实现上述目的，本申请还提出一种多维度数据对账系统，所述系统包括：
至少一个数据提供方，用于将第一数据发送至公共平台；
所述公共平台，用于接收并记录所述第一数据；
数据提取方，用于从所述公共平台中提取数据，提取的数据为第二数据；
监控方，用于对账所述第二数据是否与所述第一数据相同。
本申请提出的多维度数据对账方法及系统，通过至少一个数据提供方将第一数据发送至公共平台，所述公共平台记录所述第一数据，数据提取方从所述公共平台中提取数据，提取的数据为第二数据，当监控方对账第二数据与第一数据相同时，则对账成功。本申请的多维度数据对账方法，可以保证同步数据的正确性和完整性、保证出现异常数据能够及时处理、以及保证错误的数据不会进入其他流程而导致错误。
附图说明
图1为本申请第一实施例提出的一种多维度数据对账方法的流程图；
图2为本申请第二实施例提出的一种多维度数据对账方法的流程图；
图3为本申请第三实施例提出的一种多维度数据对账方法的流程图；
图4为本申请第四实施例提出的一种多维度数据对账系统的模块示意图；
本申请目的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
具体实施方式
为了使本申请所要解决的技术问题、技术方案及有益效果更加清楚、明白，以下结合附图和实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
第一实施例
如图1所示，本申请第一实施例提出一种多维度数据对账方法，该方法包括以下步骤：
S110，至少一个数据提供方将第一数据发送至公共平台。
具体地，本实施例中将推送数据的专业公司称为数据提供方。各专业公司分管不同的产品、业务员和工作内容，不同的专业公司定期向公共平台推送多维度数据。
多个数据提供方定期将数据推送至公共平台，并在公共平台对账表中记录多维度对账数据，推送数据包括：数据量、总计保费、总计佣金值等关键指标。数据提供方采用同步工具将数据发送给公共平台。
在本实施例中，将数据提供方发送的数据称之为第一数据。
在本实施例中，同步工具可以采用数据仓库技术(Extract-Transform-Load，ETL)，也可以是跨数据库同步工具TJS等。
进一步地，数据提供方可以按照时间周期推送数据，也可以不定时地推送数据。
S120，所述公共平台记录所述第一数据。
具体地，公共平台将第一数据保存至数据库中，在本实施例中，采用Oracle数据库，在其他实施例中，也可以采用PostgreSQL、MySQL等类型各种数据库。
S130，数据提取方从所述公共平台中提取数据，提取的数据为第二数据。
具体地，将提取数据的专业公司称为数据提取方。数据提取方从公共平台记录的数据中提取数据，将提取的数据称为第二数据，本领域技术人员可以理解的是，第二数据可以是第一数据，也可以不是第一数据。
S140，监控方对账所述第二数据是否与所述第一数据相同。若是，则流程结束，若否，则进入S150。
具体地，监控方按照特定频率比较比对第二数据是否与第一数据相同，具 体比对的是第二数据中的所有指标和第一数据中的所有指标是否完全相同，若相同，则说明对账无误，则可以进行其他流程，例如佣金计算流程等，若不相同，则进入S150。
S150，系统报错。
具体地，说明出现错误，邮件发送给开发及运维，提前进行问题查找，避免影响后续的流程。
下面以进行综拓佣金对账为例进行具体说明：
(1)专业公司A和B在1月1日采用ETL、TJS等其中一种方式将业绩数据M推送至公共平台C，数据包括数据量、总计保费、总计佣金值等关键指标。
(2)寿险D在1月2日从公共平台将专业公司A和B的业绩数据N按机构同步至8个寿险机构库，并在公共平台记录下每个机构的对账数据，如数据量、总计保费、总计佣金值等关键指标。
(3)监控方检测到专业公司A和B、寿险D完成一次数据的发送和提取动作，则对业绩数据M和业绩数据N进行对账，如果任一指标不一致，则无法进行综拓佣金的计算，并提示用户上报问题，如果所有指标均一致，则进行综拓佣金的计算。
本申请的多维度数据对账方法，通过至少一个数据提供方将第一数据发送至公共平台，所述公共平台记录所述第一数据，数据提取方从所述公共平台中提取数据，提取的数据为第二数据，当监控方对账第二数据与第一数据相同时，则对账成功。通过本申请的多维度数据对账方法，可以保证同步数据的正确性和完整性、保证出现异常数据能够及时处理、以及保证错误的数据不会进入其他流程而导致错误。
第二实施例
如图2所示，本申请第二实施例提出一种多维度数据对账方法。在第二实 施例中，所述多维度数据对账方法的步骤与第一实施例的步骤相类似，主要区别在于在第一实施例的基础上增加了S240-S250。该方法具体包括以下步骤：
S210，至少一个数据提供方将第一数据发送至公共平台。
具体地，本实施例中将推送数据的专业公司称为数据提供方。各专业公司分管不同的产品、业务员和工作内容，不同的专业公司定期向公共平台推送多维度数据。
多个数据提供方定期将数据推送至公共平台，并在公共平台对账表中记录多维度对账数据，推送数据包括：数据量、总计保费、总计佣金值等关键指标。数据提供方采用同步工具将数据发送给公共平台。
在本实施例中，将数据提供方发送的数据称之为第一数据。
在本实施例中，同步工具可以采用数据仓库技术(Extract-Transform-Load，ETL)，也可以是跨数据库同步工具TJS等。
进一步地，数据提供方可以按照时间周期推送数据，也可以不定时地推送数据。
S220，所述公共平台记录所述第一数据。
具体地，公共平台将第一数据保存至数据库中，在本实施例中，采用Oracle数据库，在其他实施例中，也可以采用PostgreSQL、MySQL等类型各种数据库。
S230，数据提取方从所述公共平台中提取数据，提取的数据为第二数据。
具体地，将提取数据的专业公司称为数据提取方。数据提取方从公共平台记录的数据中提取数据，将提取的数据称为第二数据，本领域技术人员可以理解的是，第二数据可以是第一数据，也可以不是第一数据。
S240，所述数据提取方将所述第二数据同步至至少一个分支机构。
具体地，以保险行业为例，寿险定时从公共平台将各专业公司业绩数据按机构同步至8个寿险机构库，并在公共平台记录下每个机构的对账数据，如数 据量、总计保费、总计佣金值等关键信息。此时，公共平台同时有专业公司推送到公共平台数据的关键指标，和寿险从公共平台同步到数据的关键指标。
S250，所述监控方从所述公共平台中获取所述第一数据和所述第二数据。
S260，监控方对账所述第二数据是否与所述第一数据相同。若是，则流程结束，若否，则进入S270。
具体地，监控方按照特定频率比较比对第二数据是否与第一数据相同，具体比对的是第二数据中的所有指标和第一数据中的所有指标是否完全相同，若相同，则说明对账无误，则可以进行其他流程，例如佣金计算流程等，若不相同，则进入S270。
S270，系统报错。
具体地，说明出现错误，邮件发送给开发及运维，提前进行问题查找，避免影响后续的流程。
本申请的多维度数据对账方法，至少具有以下三点意义：1、保证同步数据的正确性和完整性；2、保证出现异常数据能够及时处理；3、保证错误的数据不会进入其他流程而导致错误。
第三实施例
如图3所示，本申请第三实施例提出一种多维度数据对账方法。在第三实施例中，所述多维度数据对账方法的步骤与第一实施例的步骤相类似，主要区别在于在第二实施例中的S250具体包括S350-S360。该方法具体包括以下步骤：
S310，至少一个数据提供方将第一数据发送至公共平台。
具体地，本实施例中将推送数据的专业公司称为数据提供方。各专业公司分管不同的产品、业务员和工作内容，不同的专业公司定期向公共平台推送多维度数据。
多个数据提供方定期将数据推送至公共平台，并在公共平台对账表中记录多维度对账数据，推送数据包括：数据量、总计保费、总计佣金值等关键指标。数据提供方采用同步工具将数据发送给公共平台。
在本实施例中，将数据提供方发送的数据称之为第一数据。
在本实施例中，同步工具可以采用数据仓库技术(Extract-Transform-Load，ETL)，也可以是跨数据库同步工具TJS等。
进一步地，数据提供方可以按照时间周期推送数据，也可以不定时地推送数据。
S320，所述公共平台记录所述第一数据。
具体地，公共平台将第一数据保存至数据库中，在本实施例中，采用Oracle数据库，在其他实施例中，也可以采用PostgreSQL、MySQL等类型各种数据库。
S330，数据提取方从所述公共平台中提取数据，提取的数据为第二数据。
具体地，将提取数据的专业公司称为数据提取方。数据提取方从公共平台记录的数据中提取数据，将提取的数据称为第二数据，本领域技术人员可以理解的是，第二数据可以是第一数据，也可以不是第一数据。
S340，所述数据提取方将所述第二数据同步至至少一个分支机构。
具体地，以保险行业为例，寿险定时从公共平台将各专业公司业绩数据按机构同步至8个寿险机构库，并在公共平台记录下每个机构的对账数据，如数据量、总计保费、总计佣金值等关键信息。此时，公共平台同时有专业公司推送到公共平台数据的关键指标，和寿险从公共平台同步到数据的关键指标。
S350，设置特定频率，所述特定频率包括周期频率、时间范围和次数；
S360，监控方按照所述特定频率从所述公共平台中获取所述第一数据和所述第二数据。
具体地，监控方按照特定频率从公共平台获取第一数据和第二数据，该特 定频率可以是指周期频率、时间范围、次数等。
周期频率可以是：日、月等。即，监控方以日或者月为单位，分别或者同时查看第一数据和第二数据。
时间范围可以是固定周期频率的时间范围，例如：每天10:00至次日10:00的时间范围内，分别或者同时查看第一数据和第二数据。
次数是指数据提供方每发送一次数据、以及数据提取方每提取一次数据作为1次。数据提供方和数据发送方每完成1次数据发送和提取动作，则监控方查看第一数据和第二数据。
S370，监控方对账所述第二数据是否与所述第一数据相同。若是，则流程结束，若否，则进入S380。
具体地，监控方按照特定频率比较比对第二数据是否与第一数据相同，具体比对的是第二数据中的所有指标和第一数据中的所有指标是否完全相同，若相同，则说明对账无误，则可以进行其他流程，例如佣金计算流程等，若不相同，则进入S380。
S380，系统报错。
具体地，说明出现错误，邮件发送给开发及运维，提前进行问题查找，避免影响后续的流程。
本实施例的多维度数据对账方法，通过设置特定频率，且监控方按照该特定频率从公共平台中获取第一数据和第二数据，进而进行后续的对账第二数据与第一数据，可以保证同步数据的正确性和完整性、保证出现异常数据能够及时处理、以及保证错误的数据不会进入其他流程而导致错误。
第四实施例，
如图4所示，本申请第四实施例提出一种多维度数据对账系统。
在本实施例中，多维度数据对账系统包括至少一个数据提供方410、公共平台420、数据提取方430、及监控方440。其中，
至少一个数据提供方410，用于将第一数据发送至公共平台。
具体地，本实施例中将推送数据的专业公司称为数据提供方410。各专业公司分管不同的产品、业务员和工作内容，不同的专业公司定期向公共平台推送多维度数据。
多个数据提供方410定期将数据推送至公共平台420，并在公共平台420对账表中记录多维度对账数据，推送数据包括：数据量、总计保费、总计佣金值等关键指标。数据提供方采用同步工具将数据发送给公共平台。
在本实施例中，将数据提供方410发送的数据称之为第一数据。
在本实施例中，同步工具可以采用数据仓库技术(Extract-Transform-Load，ETL)，也可以是跨数据库同步工具TJS等。
进一步地，数据提供方410可以按照时间周期推送数据，也可以不定时地推送数据。
公共平台420，记录所述第一数据。
具体地，公共平台420将第一数据保存至数据库中，在本实施例中，采用Oracle数据库，在其他实施例中，也可以采用PostgreSQL、MySQL等类型各种数据库。
数据提取方430，用于从所述公共平台420中提取数据，提取的数据为第二数据。
具体地，将提取数据的专业公司称为数据提取方430。数据提取方430从公共平台420中提取数据，将提取的数据称为第二数据，本领域技术人员可以理解的是，第二数据可以是第一数据，也可以不是第一数据。
监控方440，用于对账所述第二数据是否与所述第一数据相同。
具体地，监控方440按照特定频率比较比对第二数据是否与第一数据相同，具体比对的是第二数据中的所有指标和第一数据中的所有指标是否完全相同，若相同，则说明对账无误，则可以进行其他流程，例如佣金计算流程等。
当监控方440对账第二数据与第一数据不相同时，则进行系统报错。
具体地，说明出现错误，邮件发送给开发及运维，提前进行问题查找，避免影响后续的流程。
进一步地，所述数据提取方430，还用于将所述第二数据同步至至少一个分支机构。
具体地，以保险行业为例，寿险定时从公共平台420将各专业公司业绩数据按机构同步至8个寿险机构库，并在公共平台420记录下每个机构的对账数据，如数据量、总计保费、总计佣金值等关键信息。此时，公共平台420同时有专业公司推送到公共平台数据的关键指标，和寿险从公共平台同步到数据的关键指标。
相应地，所述监控方440，还用于从所述公共平台420中获取所述第一数据和所述第二数据。
监控方440具体用于设置特定频率、以及按照所述特定频率从所述公共平台420中获取所述第一数据和所述第二数据，所述特定频率包括周期频率、时间范围和次数
具体地，监控方440按照特定频率从公共平台420获取第一数据和第二数据，该特定频率可以是指周期频率、时间范围、次数等。
周期频率可以是：日、月等。即，监控方440以日或者月为单位，分别或者同时查看第一数据和第二数据。
时间范围可以是固定周期频率的时间范围，例如：每天10:00至次日10:00的时间范围内，分别或者同时查看第一数据和第二数据。
次数是指数据提供方每发送一次数据、以及数据提取方每提取一次数据作 为1次。数据提供方410和数据发送方430每完成1次数据发送和提取动作，则监控方440查看第一数据和第二数据。
下面以进行综拓佣金对账为例进行具体说明：
(1)专业公司A和B在1月1日采用ETL、TJS等其中一种方式将业绩数据M推送至公共平台C，数据包括数据量、总计保费、总计佣金值等关键指标。
(2)寿险D在1月2日从公共平台将专业公司A和B的业绩数据N按机构同步至8个寿险机构库，并在公共平台记录下每个机构的对账数据，如数据量、总计保费、总计佣金值等关键指标。
(3)监控方检测到专业公司A和B、寿险D完成一次数据的发送和提取动作，则对业绩数据M和业绩数据N进行对账，如果任一指标不一致，则无法进行综拓佣金的计算，并提示用户上报问题，如果所有指标均一致，则进行综拓佣金的计算。
本申请的多维度数据对账系统，通过至少一个数据提供方410将第一数据发送至公共平台420，所述公共平台420记录所述第一数据，数据提取方430从所述公共平台420中提取数据，提取的数据为第二数据，当监控方440对账第二数据与第一数据相同时，则对账成功。通过本申请的多维度数据对账系统，可以保证同步数据的正确性和完整性、保证出现异常数据能够及时处理、以及保证错误的数据不会进入其他流程而导致错误。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下， 由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件来实现，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本申请各个实施例所述的方法。
以上参照附图说明了本申请的优选实施例，并非因此局限本申请的权利范围。上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。另外，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。
本领域技术人员不脱离本申请的范围和实质，可以有多种变型方案实现本申请，比如作为一个实施例的特征可用于另一实施例而得到又一实施例。凡在运用本申请的技术构思之内所作的任何修改、等同替换和改进，均应在本申请的权利范围之内。

Claims (20)

  1. 一种多维度数据对账方法，其特征在于，该方法包括步骤：
    至少一个数据提供方将第一数据发送至公共平台；
    所述公共平台记录所述第一数据；
    数据提取方从所述公共平台中提取数据，提取的数据为第二数据；
    监控方对账所述第二数据是否与所述第一数据相同。
  2. 根据权利要求1所述的多维度数据对账方法，其特征在于，在数据提取方从所述公共平台中提取数据之后，所述方法还包括：
    所述数据提取方将所述第二数据同步至至少一个分支机构。
  3. 根据权利要求1所述的多维度数据对账方法，其特征在于，所述方法还包括：
    所述监控方从所述公共平台中获取所述第一数据和所述第二数据。
  4. 根据权利要求2所述的多维度数据对账方法，其特征在于，所述方法还包括：
    所述监控方从所述公共平台中获取所述第一数据和所述第二数据。
  5. 根据权利要求3或4所述的多维度数据对账方法，其特征在于，所述监控方从所述公共平台中获取所述第一数据和所述第二数据，包括：
    设置特定频率，所述特定频率包括周期频率、时间范围和次数；
    所述监控方按照所述特定频率从所述公共平台中获取所述第一数据和所述第二数据。
  6. 根据权利要求1所述的多维度数据对账方法，其特征在于，所述方法还包括：
    当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  7. 根据权利要求2所述的多维度数据对账方法，其特征在于，所述方法还包括：
    当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  8. 根据权利要求3所述的多维度数据对账方法，其特征在于，所述方法还包括：
    当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  9. 根据权利要求4所述的多维度数据对账方法，其特征在于，所述方法还包括：
    当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  10. 根据权利要求5所述的多维度数据对账方法，其特征在于，所述方法还包括：
    当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  11. 一种多维度数据对账系统，其特征在于，所述系统包括：
    至少一个数据提供方，用于将第一数据发送至公共平台；
    所述公共平台，用于接收并记录所述第一数据；
    数据提取方，用于从所述公共平台中提取数据，提取的数据为第二数据；
    监控方，用于对账所述第二数据是否与所述第一数据相同。
  12. 根据权利要求11所述的多维度数据对账系统，其特征在于，所述数据提取方，还用于将所述第二数据同步至至少一个分支机构。
  13. 根据权利要求11所述的多维度数据对账系统，其特征在于，所述监控 方，还用于从所述公共平台中获取所述第一数据和所述第二数据。
  14. 根据权利要求12所述的多维度数据对账系统，其特征在于，所述监控方，还用于从所述公共平台中获取所述第一数据和所述第二数据。
  15. 根据权利要求13或14所述的多维度数据对账系统，其特征在于，所述监控方，具体用于：设置特定频率、以及按照所述特定频率从所述公共平台中获取所述第一数据和所述第二数据，所述特定频率包括周期频率、时间范围和次数。
  16. 根据权利要求11所述的多维度数据对账系统，其特征在于，当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  17. 根据权利要求12所述的多维度数据对账系统，其特征在于，当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  18. 根据权利要求13所述的多维度数据对账系统，其特征在于，当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  19. 根据权利要求14所述的多维度数据对账系统，其特征在于，当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
  20. 根据权利要求15所述的多维度数据对账系统，其特征在于，当所述监控方对账所述第二数据与所述第一数据不相同时，则进行系统报错。
PCT/CN2018/085730 2017-05-05 2018-05-04 多维度数据对账方法及系统 Ceased WO2018202176A1 (zh)

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