Multi-channel business data processing method and device, storage medium, and terminal

Abstract

The present invention discloses a method and device, storage medium, and terminal for processing multi-channel business data, which relates to the field of data processing technology, and its main purpose is to solve the problem of low processing efficiency of multi-channel business data. It mainly includes obtaining the first operation content in the business data summary table creation interface, and parsing the first configuration content corresponding to the first operation content; based on the public mapping relationship library, calling the target business dimension data matching the target business dimension and the target business indicator data matching the target business indicator under the target business dimension data from the target data table, and generating an initial delivery data summary table based on the target business dimension data and the target business indicator data; when the second operation content in the mapping relationship configuration interface is obtained, parsing the second configuration content in the second operation content; updating the initial delivery data summary table based on the second configuration content to obtain the target delivery data summary table.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and device for processing multi-channel business data, a storage medium, and a terminal. Background Art

[0002] With the development of Internet technology and big data, the business of many industries has achieved multi-platform and multi-channel development, such as the financial industry, advertising industry, insurance industry, short video industry, etc. Correspondingly, the channels that can generate business data in various industries are becoming more and more extensive. For example, in the advertising field, in order to collect information such as conversion rate, click-through rate, and return on investment of advertising, it is necessary to collect data tables from different advertising platforms and integrate the filtered data. With the diversification of business execution methods, the channels for business data collection are constantly expanding, and the composition of the collected business data tables is becoming more and more complex, making business data monitoring more and more difficult.

[0003] The existing statistics of business data are mainly through pre-set fixed program modules, calling common search functions in Excel, such as VLOOKUP, HLOOKUP, etc. to extract data from the data table, and further integrate the extracted data. Since the recording forms of various data items in the data tables of different channels are different, in the process of data extraction and integration, it is easy to have problems such as abnormal data item extraction, missed data items and repeated data items, which require manual intervention and adjustment, resulting in low data processing efficiency. Summary of the invention

[0004] In view of this, the present invention provides a method and device for processing multi-channel business data, a storage medium, and a terminal, the main purpose of which is to solve the problem of low efficiency in the existing multi-channel business data processing.

[0005] According to one aspect of the present invention, a method for processing multi-channel business data is provided, comprising:

[0006] Acquire a first operation content for configuring a data table of at least one business channel, at least one business dimension, and at least one business indicator in a business data summary table creation interface, and parse a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension, and a target business indicator;

[0007] Based on a public mapping relationship library, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data are retrieved from the target data table, and an initial delivery data summary table is generated according to the target business dimension data and the target business indicator data, wherein the public mapping relationship library includes mapping relationships between various source fields in data tables of different business dimensions and different business indicators and different business channels;

[0008] When the second operation content in the mapping relationship configuration interface is obtained, the second configuration content in the second operation content is parsed, where the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information;

[0009] The initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table.

[0010] Further, the second configuration content includes a field mapping relationship configuration table, and the initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table, including:

[0011] Receiving a field mapping relationship configuration table uploaded through a field mapping relationship configuration interface, and parsing the field mapping relationship configuration table to obtain a mapping relationship between at least one business dimension data item under a target business dimension and a user-configured field;

[0012] If the user configuration field is the target business dimension data in the initial delivery data summary table, deduplication of the target business dimension data is performed based on the mapping relationship of the user configuration field;

[0013] If the user configuration field is newly added business dimension data, the initial delivery data summary table is screened based on the mapping relationship of the user configuration field;

[0014] A target delivery data summary table is generated based on the deduplication results and / or screening results of the initial delivery data summary table.

[0015] Further, the second configuration content includes table-to-table mapping relationship configuration information, and the initial delivery data summary table is updated according to the second configuration content to obtain the target delivery data summary table, including:

[0016] Parsing the table-to-table mapping relationship configuration information to obtain a first association table and a second association table, and a correspondence between a first association field in the first association table and a second association field in the second association table;

[0017] Retrieving first associated data matching the first associated field in the initial delivery data summary table, and second associated data matching the second associated field in the initial delivery data summary table;

[0018] The first associated data and the second associated data are merged according to the business dimension, and the initial delivery data summary table is updated based on the merging result to obtain a target delivery data summary table.

[0019] Further, the step of retrieving target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data from the target data table includes:

[0020] For each of the target data tables, based on the target business dimension and the target business indicator, a plurality of source fields corresponding to the target data table are respectively identified from the public mapping relationship library, and the source fields are associated to obtain a dimension indicator joint character string of each of the target data tables;

[0021] The target business dimension data and the target business indicator data in the target data table are extracted according to the dimension indicator joint character string.

[0022] Furthermore, generating an initial delivery data summary table based on the target business dimension data and the target business indicator data includes:

[0023] Merging the target business dimension data to obtain multiple dimension data groups;

[0024] Performing statistical operations on the business indicator data under the dimensional data grouping according to the indicator statistical strategy, wherein the indicator statistical strategy includes a preset indicator calculation strategy and a real-time indicator calculation strategy corresponding to different business indicators, and the real-time indicator calculation strategy has a higher priority than the preset indicator calculation strategy;

[0025] An initial delivery data summary table is generated based on the dimensional data grouping and the statistical calculation results of the business indicator data.

[0026] Furthermore, before the first operation content of configuring the data table of at least one business channel, at least one business dimension and at least one business indicator in the acquisition business data summary table creation interface, the method further includes:

[0027] In response to a user account login instruction, retrieve a data table option sequence, a business dimension option sequence, a business indicator option sequence, and indicator calculation strategy recommendation information from a user behavior model corresponding to the user account;

[0028] According to the option sequence of the data table option sequence, the business dimension option sequence and the business indicator option sequence, the business channel data table option control, the business dimension option control and the business indicator option control are displayed in the business data summary table creation interface, and the options with ordinal numbers less than the preset ordinal threshold are configured as being checked by default;

[0029] Load the recommended information of the indicator operation strategy in the drop-down menu of the real-time indicator operation strategy configuration;

[0030] The user behavior model is constructed based on the historical operation log data of the user account.

[0031] Furthermore, after the initial delivery data summary table is updated according to the second configuration content to obtain the target delivery data summary table, the method further includes:

[0032] Sending the first configuration content and the second configuration content to an associated server, so that in the associated server, the mapping relationship weights of the public mapping relationship library are optimized in an offline learning manner through a Q-learning algorithm;

[0033] The optimized public mapping relationship library is received, and the public mapping relationship library is updated according to the optimized public mapping relationship library.

[0034] According to another aspect of the present invention, a device for processing multi-channel business data is provided, comprising:

[0035] an acquisition module, configured to acquire a first operation content for configuring a data table of at least one business channel, at least one business dimension, and at least one business indicator in a business data summary table creation interface, and parse a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension, and a target business indicator;

[0036] A calling module, configured to call, from the target data table, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data, based on a public mapping relationship library, and generate an initial delivery data summary table according to the target business dimension data and the target business indicator data, wherein the public mapping relationship library includes mapping relationships between various source fields in data tables of different business dimensions and different business indicators and different business channels;

[0037] A parsing module, configured to parse second configuration content in the second operation content when the second operation content in the mapping relationship configuration interface is acquired, wherein the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information;

[0038] An updating module is used to update the initial delivery data summary table according to the second configuration content to obtain a target delivery data summary table.

[0039] Furthermore, the update module includes:

[0040] A first parsing unit is used to receive a field mapping relationship configuration table uploaded through a field mapping relationship configuration interface, and parse the field mapping relationship configuration table to obtain a mapping relationship between at least one business dimension data item under a target business dimension and a user configuration field;

[0041] a deduplication unit, configured to, if the user configuration field is target business dimension data in the initial delivery data summary table, deduplicate the target business dimension data based on a mapping relationship of the user configuration field;

[0042] A screening unit, configured to screen the initial delivery data summary table based on a mapping relationship of the user configuration field if the user configuration field is newly added business dimension data;

[0043] The first generating unit is used to generate a target delivery data summary table according to the deduplication result and / or screening result of the initial delivery data summary table.

[0044] Furthermore, the update module further includes:

[0045] A second parsing unit, configured to parse the table-to-table mapping relationship configuration information to obtain a first association table and a second association table, and a correspondence between a first association field in the first association table and a second association field in the second association table;

[0046] A retrieving unit, configured to retrieve first associated data matching the first associated field in the initial delivery data summary table, and second associated data matching the second associated field in the initial delivery data summary table;

[0047] An updating unit is used to merge the first associated data and the second associated data according to the business dimension, and update the initial delivery data summary table based on the merging result to obtain a target delivery data summary table.

[0048] Furthermore, the calling module includes:

[0049] an identification unit, configured to identify, for each of the target data tables, a plurality of source fields corresponding to the target data table from the public mapping relationship library based on the target business dimension and the target business indicator, and perform association processing on the source fields to obtain a dimension indicator joint character string of each of the target data tables;

[0050] The extraction unit is used to extract the target business dimension data and the target business indicator data in the target data table according to the dimension indicator joint character string.

[0051] Furthermore, the calling module further includes:

[0052] A merging processing unit, used for merging the target business dimension data to obtain a plurality of dimension data groups;

[0053] A calculation unit, used to perform statistical calculations on the business indicator data under the dimensional data group according to the indicator statistical strategy, wherein the indicator statistical strategy includes a preset indicator calculation strategy and a real-time indicator calculation strategy corresponding to different business indicators, and the real-time indicator calculation strategy has a higher priority than the preset indicator calculation strategy;

[0054] The second generating unit is used to generate an initial delivery data summary table according to the dimensional data grouping and the statistical operation results of the business indicator data.

[0055] Furthermore, the device also includes:

[0056] The retrieval module is further used to retrieve the data table option sequence, the business dimension option sequence, the business indicator option sequence and the indicator operation strategy recommendation information from the user behavior model corresponding to the user account in response to the user account login instruction;

[0057] A display module is used to display the business channel data table option control, the business dimension option control and the business indicator option control in the business data summary table creation interface according to the option sequence of the data table option sequence, the business dimension option sequence and the business indicator option sequence, and configure the options with an ordinal number less than a preset ordinal number threshold as being checked by default;

[0058] A loading module, used to load the recommended information of the indicator operation strategy in the drop-down menu of the real-time indicator operation strategy configuration;

[0059] The user behavior model is constructed based on the historical operation log data of the user account.

[0060] Furthermore, the device also includes:

[0061] A first sending module, configured to send the first configuration content and the second configuration content to an associated server, so that in the associated server, mapping relationship weights are optimized for the public mapping relationship library in an offline learning manner through a Q-learning algorithm;

[0062] The receiving module is used to receive the optimized public mapping relationship library and update the public mapping relationship library according to the optimized public mapping relationship library.

[0063] According to another aspect of the present invention, a storage medium is provided, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables a processor to execute an operation corresponding to the above-mentioned method for processing multi-channel business data.

[0064] According to another aspect of the present invention, there is provided a terminal, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0065] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the above-mentioned method for processing multi-channel business data.

[0066] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages:

[0067] The present invention provides a method and device for processing multi-channel business data, a storage medium, and a terminal. In an embodiment of the present invention, a first operation content for configuring a data table, at least one business dimension, and at least one business indicator of at least one business channel in a business data summary table creation interface is obtained, and a first configuration content corresponding to the first operation content is parsed, wherein the first configuration content includes a target data table, a target business dimension, and a target business indicator; based on a public mapping relationship library, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data are retrieved from the target data table, and an initial delivery data summary table is generated based on the target business dimension data and the target business indicator data. The public mapping relationship library includes the mapping relationship between each source field in the data table of different business dimensions and different business indicators and different business channels; when the second operation content in the mapping relationship configuration interface is obtained, the second configuration content in the second operation content is parsed, and the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information; the initial delivery data summary table is updated according to the second configuration content to obtain the target delivery data summary table, which improves the convenience of creating data summary table rules and greatly reduces the creation time of the business data summary table. At the same time, it avoids the problems of missed data items and repeated data items, ensures the accuracy of data summary processing, and thus greatly improves the efficiency of data processing.

[0068] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0070] Figure 1 A flow chart of a method for processing multi-channel business data provided by an embodiment of the present invention is shown;

[0071] Figure 2 A schematic diagram of a business data summary table creation interface provided by an embodiment of the present invention is shown;

[0072] Figure 3 A flowchart of another method for processing multi-channel business data provided by an embodiment of the present invention is shown;

[0073] Figure 4 A schematic diagram of a field mapping relationship configuration interface provided by an embodiment of the present invention is shown;

[0074] Figure 5 A schematic diagram of a field mapping relationship configuration provided by an embodiment of the present invention is shown;

[0075] Figure 6 A schematic diagram of a table-to-table mapping relationship configuration interface provided by an embodiment of the present invention is shown;

[0076] Figure 7 A block diagram showing the composition of a multi-channel business data processing device provided by an embodiment of the present invention;

[0077] Figure 8 A schematic diagram of the structure of a terminal provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0078] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0079] The existing statistics of business data are mainly based on pre-set fixed program modules, calling common search functions in Excel, such as VLOOKUP, HLOOKUP, etc., to extract data from the data table, and further integrate the extracted data. Since the recording forms of various data items in different channel data tables are different, in the process of data extraction and integration, data item extraction anomalies, data item omissions and data item duplication are prone to occur, which requires manual intervention and adjustment, resulting in low data processing efficiency. The embodiment of the present invention provides a method for processing multi-channel business data, such as Figure 1 As shown, the method includes:

[0080] 101. Obtain first operation content for configuring a data table of at least one business channel, at least one business dimension, and at least one business indicator in a business data summary table creation interface, and parse first configuration content corresponding to the first operation content.

[0081] In an embodiment of the present invention, a visual interface for creating a business data summary table is provided. Figure 2 As shown. Through this business data summary table creation interface, users can drag, drop, and drag the data tables of multiple business channels that need to be summarized, as well as the specific business dimensions and business indicators in the table, to configure the source and specific content of the statistical data in the business data summary table. Among them, the number of selected data tables, business dimensions, and business indicators is not limited to one, that is, multiple data tables can be selected at the same time, and multiple business indicators under multiple business dimensions in the data table can be configured to be extracted. The first operation content is the operation performed by the user in the business data summary table creation interface. By parsing the display control operated in the first operation content, the first configuration content configured by the user can be determined, wherein the first configuration content includes the target data table, the target business dimension, and the target business indicator. Among them, the business dimensions include but are not limited to: date, delivery account, plan type, channel id, channel name, media type, interaction type, ad slot name, etc. Business indicators include but are not limited to: click volume, click-through rate, number of interactions, number of shares, number of product attentions, total number of shopping carts, number of live broadcast views, etc.

[0082] It should be noted that the embodiment of the present invention only takes the business scenario of the advertising delivery channel as an example to illustrate the business data aggregation of multiple business channels. This application is also applicable to other business scenarios that require the processing of multi-channel business data, such as commodity sales, insurance, smart cities, and short video delivery, etc. The embodiment of the present invention does not make specific limitations. By displaying a visual interface to the user, the user can conveniently select the data table, business dimension, and business indicator of the target business channel that needs to be counted by dragging and dropping, effectively improving the intuitiveness and convenience of creating a business data summary table.

[0083] 102. Based on a public mapping relationship library, retrieve target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data from the target data table, and generate an initial delivery data summary table based on the target business dimension data and the target business indicator data.

[0084] In an embodiment of the present invention, the data table selected by the user through the visual interface can be a data table manually imported by the user, an sftp (SSH File Transfer Protocol) upload model table, and an advertiser business channel table. Among them, the fields used to describe business dimensions and business indicators in the advertiser business channel table are field ids generated according to channel rules, and there is a mapping relationship with the business dimension fields and business indicator field ids of the public consensus. However, the fields used to describe business dimensions and business indicators in the sftp upload model table and the data table manually imported by the user are mostly user-defined fields. In order to identify the fields corresponding to the target business dimensions and target business indicators in any data table, a public mapping relationship library is pre-constructed, including the mapping relationship between different business dimensions and different business indicators and each source field in the data table of different business channels. That is, each business dimension is used as the key in the key-value pair, and the source field corresponding to the business dimension in the data table of different advertising business channels is used as the value to construct a business dimension key-value pair; each business indicator is used as the key in the key-value pair, and the source field corresponding to the business indicator in the data table of different advertising business channels is used as the value to construct a business indicator key-value pair. Then, the target business dimension data and the target business indicator data are integrated, and the integration results are written into the master data table to obtain the initial delivery data summary table. The master data table can be a newly created blank data table or a target data table with the highest coverage of the target business dimension.

[0085] It should be noted that by pre-building a public mapping relationship library, the fields expressing the same meaning in the data tables of different business channels are associated and mapped with the corresponding business dimensions and business indicators, so that the target business dimensions and target business indicators selected by the user are applicable to the data tables of all advertising business channels, and the data of the corresponding target business dimensions and target business indicators can be accurately extracted from any data table, avoiding repeated extraction and missed extraction of data.

[0086] 103. When the second operation content in the mapping relationship configuration interface is obtained, parse the second configuration content in the second operation content.

[0087] In an embodiment of the present invention, a mapping relationship configuration interface is also provided. Through this interface, the user can further configure the mapping relationship (field mapping) between the fields in the business data summary table to further flexibly and fine-grainedly configure the business indicators or business dimensions in the business data summary table; the mapping relationship between specified fields in two or more specified data tables can also be configured. The second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information. The second operation content can be a drag-and-drop operation on the display control in the page, or it can be a data table download and upload operation based on the current interface. Accordingly, the second configuration content can be the parsing result of the display control, or it can be the parsing result of the uploaded data table. If the user does not configure in the mapping relationship configuration interface, that is, the second operation content is not obtained, the initial delivery data summary table will be used as the target delivery data summary table.

[0088] It should be noted that the short cycle of advertising determines that the update frequency of business channels, business dimensions and business indicators of advertising is very high, which also leads to more variables in the statistical needs of business data, such as the addition of advertising business channels, new requirements for data statistical dimensions, etc. If the operation and maintenance personnel are relied on to update the business data summary table creation interface, it will take a long time, and for individual temporary needs, updating the interface will also cause unnecessary waste of resources. By providing a mapping relationship configuration interface, users can configure the mapping relationship between fields according to real-time data statistical needs, greatly reducing the time for updating the mapping relationship between fields.

[0089] 104. Update the initial delivery data summary table according to the second configuration content to obtain a target delivery data summary table.

[0090] In an embodiment of the present invention, the field mapping relationship configuration table is a configuration table generated based on the target business dimension to meet the user's field mapping relationship customization requirements. The user can download the initial field mapping relationship configuration table from the field mapping relationship configuration interface, and then configure the mapping relationship between the fields in the table, and complete the configuration of the field mapping relationship configuration table through the interface to upload the updated data in the initial delivery data summary table. The field mapping relationship that the user can configure includes adding a differentiated field column, that is, configuring different mapping fields for different data items under a certain business dimension in the newly added column to achieve fine-grained business dimension data processing. The table-to-table mapping relationship configuration information includes the mapping relationship between one or more business dimensions in two or more data tables selected by the user. When the user selects two data tables through the table-to-table mapping relationship configuration interface, and selects two business dimensions in each data table, the mapping relationship between the first business dimension in the first data table and the first business dimension in the second data table, and the mapping relationship between the second business dimension in the first data table and the second business dimension in the second data table are constructed, and the initial delivery data summary table is integrated according to the above two mapping relationships.

[0091] It should be noted that updating the initial delivery data summary table through the second configuration content is a process of flexibly adjusting the statistical data items of the delivery data summary table according to the mapping relationship between user-defined fields, which can further improve the flexibility of business data processing to meet more user needs and does not require code adjustments by operation and maintenance personnel, greatly reducing the response time to different user needs while ensuring the accuracy of data processing, thereby effectively improving the efficiency of data processing.

[0092] In an embodiment of the present invention, for further explanation and limitation, as Figure 3 As shown, the step updates the initial delivery data summary table according to the second configuration content to obtain the target delivery data summary table, including:

[0093] 201. Receive a field mapping relationship configuration table uploaded through a field mapping relationship configuration interface, and parse the field mapping relationship configuration table to obtain a mapping relationship between at least one business dimension data item under a target business dimension and a user configuration field.

[0094] 202. If the user configuration field is target business dimension data in the initial delivery data summary table, deduplicate the target business dimension data based on the mapping relationship of the user configuration field.

[0095] 203. If the user configuration field is newly added business dimension data, the initial delivery data summary table is screened based on the mapping relationship of the user configuration field.

[0096] 204. Generate a target delivery data summary table according to the deduplication result and / or screening result of the initial delivery data summary table.

[0097] In the embodiment of the present invention, the field mapping relationship configuration interface is as follows Figure 4 As shown, the field mapping relationship configuration table can be downloaded and uploaded through this interface. When the second configuration content includes field mapping relationship, the field mapping relationship configuration table uploaded by the user is parsed, such as Figure 5 As shown. If the user-configured field exists in the target business dimension data, a mapping relationship between two dimension data items in the target business dimension data is constructed, and the two can be deduplicated. For example, "Oriental Times" under the business dimension "Promotion Name" and "id123456" under the business dimension "Promotion ID" are both target business dimension data. The user configures "Oriental Times" as the user-configured field of "id123456" in the table, and a mapping relationship is established between "Oriental Times" and "id123456", indicating that "Oriental Times" is equal to "id123456". The business indicator data corresponding to the two are the same content, and can be deduplicated, and only one of them can be retained. If the user-configured field is a newly added business dimension data, that is, the user adds a business dimension column to the table, this column can be used to implement fine-grained configuration of different business dimension data items, that is, different business dimension data items correspond to different other business dimensions. For example, if the target business dimension is "date", the data items under this dimension include January 1 to January 30. The user enters the user configuration field "id67890" in the new column corresponding to the row of January 1, and enters the user configuration field "id68909" in the new column corresponding to the row of January 2. By entering different user configuration fields in different rows in the new column, different data items under a certain business dimension correspond to different data contents in this column. In addition, the lower-order data items of the current business dimension data item can also be entered in this new column. For example, if the business dimension data item is "fruit" and the user configuration field is "durian", the mapping relationship of the user configuration field is the field mapping relationship between fruit and durian. When retrieving data, only the "durian" data under the "fruit" data item is retrieved through the field mapping relationship to achieve fine-grained business dimensions, thereby meeting the user's fine-grained requirements.

[0098] In one embodiment of the present invention, for further explanation and limitation, the step of updating the initial delivery data summary table according to the second configuration content to obtain the target delivery data summary table includes:

[0099] Parsing the table-to-table mapping relationship configuration information to obtain a first association table and a second association table, and a correspondence between a first association field in the first association table and a second association field in the second association table;

[0100] Retrieving first associated data matching the first associated field in the initial delivery data summary table, and second associated data matching the second associated field in the initial delivery data summary table;

[0101] The first associated data and the second associated data are merged according to the business dimension, and the initial delivery data summary table is updated based on the merging result to obtain a target delivery data summary table.

[0102] In the embodiment of the present invention, the second configuration content includes table-to-table mapping relationship configuration information, that is, the user Figure 6 The table-to-table mapping relationship configuration interface shown configures the mapping relationship between one or more business dimensions in two data tables, one of which is the first association table and the other is the second association table. There can be multiple first association fields and second association fields, but the number of the two fields is equal, and the corresponding mapping relationship is established in sequence according to the order of the configuration interface. For example, the user configures two data tables, the first association table and the second association table, and sequentially configures three association fields under the first association table and the second association table, respectively. Then, a mapping relationship between the first association field of the first order and the second association field of the first order is constructed, and a mapping relationship between the first association field of the second order and the second association field of the second order is constructed. By analogy, the corresponding relationship between all the first association segments in the first association table and all the second association fields in the second association table is completed. The above field mapping relationship is only established between the first association table and the second association table. After the mapping relationship is established, the first association data corresponding to the existing first association field and the second association data corresponding to the second association field are merged based on this mapping relationship to achieve deduplication of data in the current initial delivery data summary table. If the second configuration content obtained through parsing includes both a field mapping relationship configuration table and a table-to-table mapping relationship, the initial delivery data summary table is updated according to the field mapping relationship configuration table and the table-to-table mapping relationship.

[0103] It should be noted that in some cases, the mapping relationship between fields is not universally applicable to all data tables, but is a corresponding relationship specified based on user experience or business needs. For example, the target data tables include 5, but only the sales of goods in data table A is equal to the number of clicks on goods in data table B, while in other data tables, this mapping relationship does not hold. By setting the table-to-table mapping relationship configuration interface, users can configure the mapping relationship between specified fields in the specified data table through this interface, which greatly improves the flexibility of multi-channel business data processing and improves the quality of user experience.

[0104] In one embodiment of the present invention, for further explanation and limitation, the step of retrieving target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data from the target data table includes:

[0105] For each of the target data tables, based on the target business dimension and the target business indicator, a plurality of source fields corresponding to the target data table are respectively identified from the public mapping relationship library, and the source fields are associated to obtain a dimension indicator joint character string of each of the target data tables;

[0106] The target business dimension data and the target business indicator data in the target data table are extracted according to the dimension indicator joint character string.

[0107] In an embodiment of the present invention, according to the mapping relationship between each source field in the data table of different business dimensions and different business indicators and different business channels in the public mapping relationship library, the source fields corresponding to different target business dimensions in different target data tables and the source fields corresponding to different target business indicators in different target data tables are matched. For any target data table, the source fields corresponding to the target business dimensions and target business indicators are associated as a string, that is, a dimension indicator joint string, and data is extracted from the target data table based on this dimension indicator joint string. The above mapping relationship can be specifically implemented using a hash function. By associating the field groups corresponding to different business dimensions and different business indicators into one field, the mapping relationship between multiple fields in the mapping table is converted into a key-value pair mapping, so that each piece of data is mapped to its own object by the key composed of the value of the selected field, and the time complexity of a single data is converted from On to O1. When adding fields later, some of the previously existing data is obtained by local comparison instead of all re-matching to reduce the amount of data to be calculated. In addition, the converted key-value pair mapping can be stored in other servers to reduce the memory space occupied by the current server and reduce the storage pressure of the current server.

[0108] In one embodiment of the present invention, for further explanation and limitation, the step of generating an initial delivery data summary table based on the target business dimension data and the target business indicator data includes:

[0109] Merging the target business dimension data to obtain multiple dimension data groups;

[0110] Perform statistical operations on the business indicator data under the dimension data grouping according to the indicator statistical strategy;

[0111] An initial delivery data summary table is generated based on the dimensional data grouping and the statistical calculation results of the business indicator data.

[0112] In an embodiment of the present invention, the target business dimension data may be a large dimension concept, for example, "daily necessities", but the target business dimension data retrieved in different target data tables may be "paper products" or "daily chemicals", which all belong to "daily necessities". Therefore, it is necessary to group the target business dimension data, and merge the dimension data in a group, and group multiple dimension data. After the dimension data is grouped, since different dimension data groups also correspond to business indicator data, and the statistical rules corresponding to different business indicator data are also different, it is necessary to perform statistical operations on the business indicator data under the dimension data grouping according to the indicator statistical strategy. Among them, the indicator statistical strategy includes preset indicator operation strategies and real-time indicator operation strategies corresponding to different business indicators. Among them, the preset indicator operation strategy is configured according to the historical statistical experience of the business indicator, for example, summing up all clicks, calculating the instantaneous maximum value of web page clicks, taking the average value of satisfaction, etc. The real-time indicator calculation strategy is a statistical calculation formula configured by the user through the interactive interface. It is customized for different business indicators according to the actual needs of the user. When a real-time indicator calculation strategy exists, the corresponding indicator data is processed according to the real-time indicator calculation strategy, that is, the real-time indicator calculation strategy has a higher priority than the preset indicator calculation strategy.

[0113] It should be noted that by grouping and deduplicating dimension data, data duplication caused by different field names but the same meaning of dimension data is avoided, thus improving the accuracy of data processing. The indicator operation strategy improves the flexibility of indicator data processing and effectively improves the quality of user experience by combining preset strategies with user real-time configuration strategies.

[0114] In one embodiment of the present invention, for further explanation and limitation, before the step of obtaining the first operation content of configuring at least one business channel data table, at least one business dimension and at least one business indicator in the business data summary table creation interface, the method further includes:

[0115] In response to a user account login instruction, retrieve a data table option sequence, a business dimension option sequence, a business indicator option sequence, and indicator calculation strategy recommendation information from a user behavior model corresponding to the user account;

[0116] According to the option sequence of the data table option sequence, the business dimension option sequence and the business indicator option sequence, the business channel data table option control, the business dimension option control and the business indicator option control are displayed in the business data summary table creation interface, and the options with ordinal numbers less than the preset ordinal threshold are configured as being checked by default;

[0117] Display business channel data table option controls, business dimension option controls, and business indicator option controls;

[0118] Load the indicator calculation strategy recommendation information in the drop-down menu of the real-time indicator calculation strategy configuration.

[0119] In an embodiment of the present invention, the option contents and the arrangement order between the options in the business data summary table creation interface are personalized according to different user accounts, and are checked by default according to the preset sequence threshold. Among them, the preset sequence threshold can be customized according to application requirements. For example, if the preset sequence threshold is 3, the top options in the data table option sequence, business dimension option sequence and business indicator option sequence are checked by default. When different user accounts log in, they will be displayed according to the data table option sequence, business dimension option sequence and business indicator option sequence corresponding to this user account. For example, the data table of user account 001 is sorted into channels B, A, C, and D, and the data table of user account 002 is sorted into channels A, B, D, and C. The user account data table option sequence, business dimension option sequence, business indicator option sequence and indicator operation strategy recommendation information are extracted from the user behavior model. The business data summary table creation interface also supports real-time indicator operation strategy configuration. When the user configures the real-time indicator operation strategy, the indicator operation strategy recommendation information is displayed in the drop-down menu of the configuration option for the user to quickly select.

[0120] It should be noted that the user behavior model is constructed based on the historical operation log data of the user account. In the process of the user configuring the options, the user's dragging and field mapping configuration operations are log tracked and recorded, including key information such as the time of the user operation, the name of the dragged field, and the correspondence between the source field and the target business dimension or indicator. Then, based on machine learning or analysis algorithms, the user's historical operation log data is identified to learn the characteristics of the user's field mapping relationship matching and option dragging. And based on these characteristics, a user behavior model for the corresponding user account is constructed. By pre-building a user behavior model, it is possible to accurately match the user's option usage frequency and indicator calculation strategy configuration habits, thereby effectively improving the efficiency and accuracy of user operations.

[0121] In one embodiment of the present invention, for further explanation and limitation, after the step of updating the initial delivery data summary table according to the second configuration content to obtain the target delivery data summary table, the method further includes:

[0122] Sending the first configuration content and the second configuration content to an associated server, so that in the associated server, the mapping relationship weights of the public mapping relationship library are optimized in an offline learning manner through a Q-learning algorithm;

[0123] The optimized public mapping relationship library is received, and the public mapping relationship library is updated according to the optimized public mapping relationship library.

[0124] In an embodiment of the present invention, in the process of optimizing learning, a pre-built public mapping relationship library is used as a basic model. After each storage of user configuration information is completed, a value weight model is generated through the Q-learning algorithm based on the association relationship of each data, the mapping relationship between each field, and the frequency of use of each option. The value weights between different mapping relationships are updated and optimized through iterative learning to achieve the update of the mapping relationship in the public mapping relationship library. The above process is implemented in an associated server, which is a server that has data interaction with the current execution server but does not participate in the data processing process. In the associated server, offline learning can be performed without affecting the resource consumption of the current server, thereby reducing the server pressure when the client code is running.

[0125] The present invention provides a method for processing multi-channel business data. In an embodiment of the present invention, a first operation content for configuring a data table, at least one business dimension and at least one business indicator of at least one business channel in a business data summary table creation interface is obtained, and a first configuration content corresponding to the first operation content is parsed, wherein the first configuration content includes a target data table, a target business dimension and a target business indicator; based on a public mapping relationship library, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data are retrieved from the target data table, and an initial delivery data summary table is generated based on the target business dimension data and the target business indicator data, and the public mapping relationship library is used to obtain the target business dimension data matching the target business dimension data and the target business indicator data. The system library includes mapping relationships between source fields in data tables of different business dimensions and different business indicators and different business channels; when the second operation content in the mapping relationship configuration interface is obtained, the second configuration content in the second operation content is parsed, and the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information; the initial delivery data summary table is updated according to the second configuration content to obtain the target delivery data summary table, which improves the convenience of creating data summary table rules and greatly reduces the creation time of the business data summary table. At the same time, it avoids the problems of missed selection of data items and duplication of data items, ensures the accuracy of data summary processing, and thus greatly improves the efficiency of data processing.

[0126] Furthermore, as a response to the above Figure 1 The embodiment of the present invention provides a multi-channel business data processing device, such as Figure 7 As shown, the device comprises:

[0127] The acquisition module 31 is used to acquire a first operation content for configuring a data table of at least one business channel, at least one business dimension and at least one business indicator in the business data summary table creation interface, and parse a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension and a target business indicator;

[0128] A retrieval module 32 is used to retrieve target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data from the target data table based on a public mapping relationship library, and generate an initial delivery data summary table according to the target business dimension data and the target business indicator data, wherein the public mapping relationship library includes mapping relationships between various source fields in data tables of different business dimensions and different business indicators and different business channels;

[0129] The parsing module 33 is used to parse the second configuration content in the second operation content when the second operation content in the mapping relationship configuration interface is obtained, wherein the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information;

[0130] The updating module 34 is used to update the initial delivery data summary table according to the second configuration content to obtain a target delivery data summary table.

[0131] Furthermore, the updating module 34 includes:

[0132] A first parsing unit is used to receive a field mapping relationship configuration table uploaded through a field mapping relationship configuration interface, and parse the field mapping relationship configuration table to obtain a mapping relationship between at least one business dimension data item under a target business dimension and a user configuration field;

[0133] a deduplication unit, configured to, if the user configuration field is target business dimension data in the initial delivery data summary table, deduplicate the target business dimension data based on a mapping relationship of the user configuration field;

[0134] A screening unit, configured to screen the initial delivery data summary table based on a mapping relationship of the user configuration field if the user configuration field is newly added business dimension data;

[0135] The first generating unit is used to generate a target delivery data summary table according to the deduplication result and / or screening result of the initial delivery data summary table.

[0136] Furthermore, the updating module 34 further includes:

[0137] A second parsing unit, configured to parse the table-to-table mapping relationship configuration information to obtain a first association table and a second association table, and a correspondence between a first association field in the first association table and a second association field in the second association table;

[0138] A retrieving unit, configured to retrieve first associated data matching the first associated field in the initial delivery data summary table, and second associated data matching the second associated field in the initial delivery data summary table;

[0139] An updating unit is used to merge the first associated data and the second associated data according to the business dimension, and update the initial delivery data summary table based on the merging result to obtain a target delivery data summary table.

[0140] Furthermore, the calling module 32 includes:

[0141] an identification unit, configured to identify, for each of the target data tables, a plurality of source fields corresponding to the target data table from the public mapping relationship library based on the target business dimension and the target business indicator, and perform association processing on the source fields to obtain a dimension indicator joint character string of each of the target data tables;

[0142] The extraction unit is used to extract the target business dimension data and the target business indicator data in the target data table according to the dimension indicator joint character string.

[0143] Furthermore, the calling module 32 further includes:

[0144] A merging processing unit, used for merging the target business dimension data to obtain a plurality of dimension data groups;

[0145] A calculation unit, used to perform statistical calculations on the business indicator data under the dimensional data group according to the indicator statistical strategy, wherein the indicator statistical strategy includes a preset indicator calculation strategy and a real-time indicator calculation strategy corresponding to different business indicators, and the real-time indicator calculation strategy has a higher priority than the preset indicator calculation strategy;

[0146] The second generating unit is used to generate an initial delivery data summary table according to the dimensional data grouping and the statistical operation results of the business indicator data.

[0147] Furthermore, the device also includes:

[0148] The retrieving module 32 is further used to retrieve the data table option sequence, the business dimension option sequence, the business indicator option sequence and the indicator operation strategy recommendation information from the user behavior model corresponding to the user account in response to the user account login instruction;

[0149] A display module is used to display the business channel data table option control, the business dimension option control and the business indicator option control in the business data summary table creation interface according to the option sequence of the data table option sequence, the business dimension option sequence and the business indicator option sequence, and configure the options with an ordinal number less than a preset ordinal number threshold as being checked by default;

[0150] A loading module, used to load the recommended information of the indicator operation strategy in the drop-down menu of the real-time indicator operation strategy configuration;

[0151] The user behavior model is constructed based on the historical operation log data of the user account.

[0152] Furthermore, the device also includes:

[0153] A second sending module is used to send the first configuration content and the second configuration content to an associated server, so that in the associated server, the mapping relationship weights of the public mapping relationship library are optimized in an offline learning manner through a Q-learning algorithm;

[0154] The receiving module is used to receive the optimized public mapping relationship library and update the public mapping relationship library according to the optimized public mapping relationship library.

[0155] The present invention provides a multi-channel business data processing device. The embodiment of the present invention obtains a first operation content for configuring a data table, at least one business dimension and at least one business indicator of at least one business channel in a business data summary table creation interface, and parses a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension and a target business indicator; based on a public mapping relationship library, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data are retrieved from the target data table, and an initial delivery data summary table is generated based on the target business dimension data and the target business indicator data, wherein the public mapping relationship library is used to obtain target business dimension data matching the target business dimension and the target business indicator data matching the target business indicator under the target business dimension data; the public mapping relationship library is used to obtain the target business dimension data matching the target business dimension data and the target business indicator data, and the target business dimension data matching the target business indicator data matching the target business indicator data matching the target business indicator data matching the target business dimension ... The system library includes mapping relationships between source fields in data tables of different business dimensions and different business indicators and different business channels; when the second operation content in the mapping relationship configuration interface is obtained, the second configuration content in the second operation content is parsed, and the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information; the initial delivery data summary table is updated according to the second configuration content to obtain the target delivery data summary table, which improves the convenience of creating data summary table rules and greatly reduces the creation time of the business data summary table. At the same time, it avoids the problems of missed selection of data items and duplication of data items, ensures the accuracy of data summary processing, and thus greatly improves the efficiency of data processing.

[0156] According to an embodiment of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction, and the computer executable instruction can execute the method for processing multi-channel business data in any of the above method embodiments.

[0157] Figure 8 A schematic diagram of the structure of a terminal provided according to an embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the terminal.

[0158] like Figure 8 As shown, the terminal may include: a processor (processor) 402 , a communication interface (Communications Interface) 404 , a memory (memory) 406 , and a communication bus 408 .

[0159] The processor 402 , the communication interface 404 , and the memory 406 communicate with each other via a communication bus 408 .

[0160] The communication interface 404 is used for network communication with other devices such as a client or other servers.

[0161] The processor 402 is used to execute the program 410, and specifically can execute the relevant steps in the embodiment of the method for processing multi-channel business data.

[0162] Specifically, the program 410 may include program codes, which include computer operation instructions.

[0163] The processor 402 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiment of the present invention. The one or more processors included in the terminal may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0164] The memory 406 is used to store the program 410. The memory 406 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0165] The program 410 may be specifically configured to enable the processor 402 to perform the following operations:

[0166] Acquire a first operation content for configuring a data table of at least one business channel, at least one business dimension, and at least one business indicator in a business data summary table creation interface, and parse a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension, and a target business indicator;

[0167] Based on a public mapping relationship library, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data are retrieved from the target data table, and an initial delivery data summary table is generated according to the target business dimension data and the target business indicator data, wherein the public mapping relationship library includes mapping relationships between various source fields in data tables of different business dimensions and different business indicators and different business channels;

[0168] When the second operation content in the mapping relationship configuration interface is obtained, the second configuration content in the second operation content is parsed, where the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information;

[0169] The initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table.

[0170] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0171] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for processing multi-channel business data, characterized in that: include: Acquire a first operation content for configuring a data table of at least one business channel, at least one business dimension, and at least one business indicator in a business data summary table creation interface, and parse a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension, and a target business indicator; Based on a public mapping relationship library, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data are retrieved from the target data table, and an initial delivery data summary table is generated according to the target business dimension data and the target business indicator data, wherein the public mapping relationship library includes mapping relationships between various source fields in data tables of different business dimensions and different business indicators and different business channels; When the second operation content in the mapping relationship configuration interface is obtained, the second configuration content in the second operation content is parsed, where the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information; The initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table; The second configuration content includes a field mapping relationship configuration table, and the initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table, including: Receiving a field mapping relationship configuration table uploaded through a field mapping relationship configuration interface, and parsing the field mapping relationship configuration table to obtain a mapping relationship between at least one business dimension data item under a target business dimension and a user-configured field; If the user configuration field is the target business dimension data in the initial delivery data summary table, deduplication of the target business dimension data is performed based on the mapping relationship of the user configuration field; If the user configuration field is newly added business dimension data, the initial delivery data summary table is screened based on the mapping relationship of the user configuration field; Generate a target delivery data summary table based on the deduplication result and / or screening result of the initial delivery data summary table; The second configuration content includes table-to-table mapping relationship configuration information, and the initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table, including: Parsing the table-to-table mapping relationship configuration information to obtain a first association table and a second association table, and a correspondence between a first association field in the first association table and a second association field in the second association table; Retrieving first associated data matching the first associated field in the initial delivery data summary table, and second associated data matching the second associated field in the initial delivery data summary table; The first associated data and the second associated data are merged according to the business dimension, and the initial delivery data summary table is updated based on the merging result to obtain a target delivery data summary table.

2. The method according to claim 1, characterized in that The step of retrieving target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data from the target data table includes: For each of the target data tables, based on the target business dimension and the target business indicator, a plurality of source fields corresponding to the target data table are respectively identified from the public mapping relationship library, and the source fields are associated to obtain a dimension indicator joint character string of each of the target data tables; The target business dimension data and the target business indicator data in the target data table are extracted according to the dimension indicator joint character string.

3. The method according to claim 2, characterized in that The generating of the initial delivery data summary table according to the target business dimension data and the target business indicator data includes: Merging the target business dimension data to obtain multiple dimension data groups; Performing statistical operations on the business indicator data under the dimensional data grouping according to the indicator statistical strategy, wherein the indicator statistical strategy includes a preset indicator calculation strategy and a real-time indicator calculation strategy corresponding to different business indicators, and the real-time indicator calculation strategy has a higher priority than the preset indicator calculation strategy; An initial delivery data summary table is generated based on the dimensional data grouping and the statistical calculation results of the business indicator data.

4. The method according to claim 1, characterized in that: Before the first operation content of configuring the data table of at least one business channel, at least one business dimension and at least one business indicator in the acquisition business data summary table creation interface, the method further includes: In response to a user account login instruction, retrieve a data table option sequence, a business dimension option sequence, a business indicator option sequence, and indicator calculation strategy recommendation information from a user behavior model corresponding to the user account; According to the option sequence of the data table option sequence, the business dimension option sequence and the business indicator option sequence, the business channel data table option control, the business dimension option control and the business indicator option control are displayed in the business data summary table creation interface, and the options with ordinal numbers less than the preset ordinal threshold are configured as being checked by default; Load the recommended information of the indicator operation strategy in the drop-down menu of the real-time indicator operation strategy configuration; The user behavior model is constructed based on the historical operation log data of the user account.

5. The method according to claim 1, characterized in that After the initial delivery data summary table is updated according to the second configuration content to obtain the target delivery data summary table, the method further includes: Sending the first configuration content and the second configuration content to an associated server, so that in the associated server, the mapping relationship weights of the public mapping relationship library are optimized in an offline learning manner through a Q-learning algorithm; The optimized public mapping relationship library is received, and the public mapping relationship library is updated according to the optimized public mapping relationship library.

6. A multi-channel business data processing device, characterized in that: include: an acquisition module, configured to acquire a first operation content for configuring a data table of at least one business channel, at least one business dimension, and at least one business indicator in a business data summary table creation interface, and parse a first configuration content corresponding to the first operation content, wherein the first configuration content includes a target data table, a target business dimension, and a target business indicator; A calling module, configured to call, from the target data table, target business dimension data matching the target business dimension and target business indicator data matching the target business indicator under the target business dimension data, based on a public mapping relationship library, and generate an initial delivery data summary table according to the target business dimension data and the target business indicator data, wherein the public mapping relationship library includes mapping relationships between various source fields in data tables of different business dimensions and different business indicators and different business channels; A parsing module, configured to parse second configuration content in the second operation content when the second operation content in the mapping relationship configuration interface is acquired, wherein the second configuration content includes a field mapping relationship configuration table and / or table-to-table mapping relationship configuration information; The second configuration content includes a field mapping relationship configuration table, and the initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table, including: Receiving a field mapping relationship configuration table uploaded through a field mapping relationship configuration interface, and parsing the field mapping relationship configuration table to obtain a mapping relationship between at least one business dimension data item under a target business dimension and a user-configured field; If the user configuration field is the target business dimension data in the initial delivery data summary table, deduplication of the target business dimension data is performed based on the mapping relationship of the user configuration field; If the user configuration field is newly added business dimension data, the initial delivery data summary table is screened based on the mapping relationship of the user configuration field; Generate a target delivery data summary table based on the deduplication result and / or screening result of the initial delivery data summary table; The second configuration content includes table-to-table mapping relationship configuration information, and the initial delivery data summary table is updated according to the second configuration content to obtain a target delivery data summary table, including: Parsing the table-to-table mapping relationship configuration information to obtain a first association table and a second association table, and a correspondence between a first association field in the first association table and a second association field in the second association table; Retrieving first associated data matching the first associated field in the initial delivery data summary table, and second associated data matching the second associated field in the initial delivery data summary table; The first associated data and the second associated data are merged according to the business dimension, and the initial delivery data summary table is updated based on the merged result to obtain a target delivery data summary table; An updating module is used to update the initial delivery data summary table according to the second configuration content to obtain a target delivery data summary table.

7. A storage medium storing at least one executable instruction, wherein the executable instruction enables a processor to execute an operation corresponding to the method for processing multi-channel business data according to any one of claims 1 to 5.

8. A terminal, comprising: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform an operation corresponding to the method for processing multi-channel business data according to any one of claims 1-5.

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