Data processing method and device, equipment and storage medium

Abstract

The application relates to a data processing method, device and equipment and a storage medium. The method comprises the following steps: determining a target board data type; acquiring a target standard business data table corresponding to the target board data type and a full-amount standard table; the full-amount standard table comprises a first full-amount target object standard table or a second full-amount target object standard table; the first full-amount target object standard table comprises full-amount standard identifiers of first target objects, and the second full-amount target object standard table comprises full-amount standard identifiers of second target objects; target field information corresponding to the full-amount standard identifiers of the first target objects or the full-amount standard identifiers of the second target objects in the full-amount standard table is extracted from the target standard business data table; and the target field information is processed to obtain target board data corresponding to the full-amount standard identifiers of the first target objects or the full-amount standard identifiers of the second target objects. Therefore, investment data can be efficiently and accurately monitored and managed.

Description

Technical Field

[0001] This application relates to the field of big data processing, and in particular to a data processing method, apparatus, device and storage medium. Background Technology

[0002] In existing technologies, business operations typically involve a large number of business data tables. For example, in investment promotion, there are numerous business data tables originating from multiple stages or scenarios. This can lead to duplicate or erroneous information, such as revenue details for the same project, resulting in inaccurate data in the business data tables. Furthermore, frequent project name changes, often done manually, can cause data gaps for the same project. Additionally, current monitoring of investment promotion operations involves monitoring these scattered business data tables, leading to low monitoring efficiency. Summary of the Invention

[0003] In view of the above-mentioned technical problems, this application proposes a data processing method, apparatus, device and storage medium.

[0004] According to one aspect of this application, a data processing method is provided, the method comprising:

[0005] Determine the data type for the target Kanban board;

[0006] Obtain the target standard business data table and the full standard table corresponding to the target dashboard data type; the full standard table includes a first full target object standard table or a second full target object standard table; the first full target object standard table includes the full standard identifier of the first target object, and the second target object standard table includes the full standard identifier of the second target object;

[0007] Extract the target field information corresponding to the full standard identifier of the first target object or the target field information corresponding to the full standard identifier of the second target object from the corresponding target standard business data table.

[0008] The target field information is processed by a preset operation to obtain the target dashboard data corresponding to the full standard identifier of the first target object or the target dashboard data corresponding to the full standard identifier of the second target object.

[0009] According to another aspect of this application, a data processing apparatus is provided, comprising:

[0010] The target Kanban data type determination module is used to determine the data type of the target Kanban.

[0011] The target standard business data table and full standard table acquisition module is used to acquire the target standard business data table and full standard table corresponding to the target dashboard data type; the full standard table includes a first full target object standard table or a second full target object standard table; the first full target object standard table includes the full standard identifier of the first target object, and the second target object standard table includes the full standard identifier of the second target object;

[0012] The target field information extraction module is used to extract the target field information corresponding to the full standard identifier of the first target object or the target field information corresponding to the full standard identifier of the second target object from the corresponding target standard business data table.

[0013] The target dashboard data acquisition module is used to perform preset calculations on the target field information to obtain target dashboard data corresponding to the full standard identifier of the first target object or the target dashboard data corresponding to the full standard identifier of the second target object.

[0014] According to another aspect of this application, a data processing apparatus is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the above-described method.

[0015] According to another aspect of this application, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions, when executed by a processor, implement the above-described method.

[0016] By setting the data types of the target dashboard and implementing unified data processing based on standard business data tables and full standard tables, multi-dimensional target dashboard data can be obtained, enabling efficient and unified monitoring of the data. Based on this unified monitoring, the rationality of investment promotion business issuance can be guaranteed, adding a guarantee for the stable development of investment promotion business; and the monitored target dashboard data can be used as a guide to make efficient adjustments to investment promotion strategies, further ensuring the effective progress of investment promotion business.

[0017] Furthermore, the full standard table used for data processing contains only standard identifiers, and the standard business data table also contains only standard identifiers, saving storage resources; and by associating various standard business data tables based on this standard table, unified data processing can be performed, which can simplify the data processing flow, save computing resources, and thus make data processing more efficient and the response to business more timely.

[0018] Furthermore, since all fields in the standard business data table are standardized, and the full standard table contains the full standard identifiers of both the first and second target objects, the comprehensiveness of the acquired first and second target objects can be guaranteed. This ensures that the data obtained from the target standard business data table is also comprehensive, and the target dashboard data obtained based on comprehensive data processing will be more accurate. Moreover, this standardized and unified data processing method has strong adaptability to business expansion and data additions, exhibiting good universality and scalability.

[0019] Other features and aspects of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0020] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this application together with the specification and serve to explain the principles of this application.

[0021] Figure 1 This diagram illustrates an application system provided according to an embodiment of the present application.

[0022] Figure 2 A schematic diagram of a data processing platform according to an embodiment of this application is shown.

[0023] Figure 3 A flowchart illustrating a method for standardizing business data tables in the business data table set according to an embodiment of this application to obtain a standard business data table set.

[0024] Figure 4 A flowchart illustrating a data processing method according to an embodiment of this application is shown.

[0025] Figure 5 A flowchart illustrating a method for determining the target Kanban data type according to an embodiment of this application is shown.

[0026] Figure 6 This diagram illustrates the overall project dashboard data corresponding to the full standard identifier of a first target object according to an embodiment of this application.

[0027] Figure 7 This diagram illustrates the project progress dashboard data corresponding to the full standard identifier of a first target object according to an embodiment of this application.

[0028] Figure 8 A flowchart illustrating a data processing method according to an embodiment of this application is shown.

[0029] Figure 9This diagram illustrates target dashboard data, including warning information, corresponding to the full standard identifier of a first target object according to an embodiment of this application.

[0030] Figure 10 A flowchart illustrating a method for generating a first full target object standard table and a second full target object standard table according to an embodiment of this application is shown.

[0031] Figure 11 A block diagram of a data processing apparatus according to an embodiment of this application is shown.

[0032] Figure 12 This is a block diagram illustrating a data processing apparatus 1200 according to an exemplary embodiment. Detailed Implementation

[0033] Various exemplary embodiments, features, and aspects of this application will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0034] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0035] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, methods, means, components, and circuits well-known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0036] Please see Figure 1 , Figure 1 This diagram illustrates an application system according to an embodiment of this application. The application system can be used in the data processing method of this application. Figure 1 As shown, the application system may include at least server 01 and terminal 02.

[0037] In this embodiment of the application, the server 01 may include an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0038] In this embodiment, the terminal 02 may include physical devices such as smartphones, desktop computers, tablets, laptops, smart speakers, digital assistants, augmented reality (AR) / virtual reality (VR) devices, and smart wearable devices. The physical device may also include software running on it, such as applications. The operating system running on the terminal 02 in this embodiment may include, but is not limited to, Android, iOS, Linux, and Windows.

[0039] In the embodiments described in this specification, the terminal 02 and the server 01 can be directly or indirectly connected through wired or wireless communication, and this application does not limit this connection.

[0040] The terminal 02 can be used to provide user-facing data processing. Users can view dashboards of target data on the terminal 02, thereby enabling monitoring of project progress and customer progress. The terminal 02 can provide user-facing data processing in ways including, but not limited to, application-based methods and web-based methods.

[0041] It should be noted that, in this embodiment of the application, the data processing is preferably implemented in server 01. This is to reduce the data processing pressure on the terminal and improve the device performance of the user-facing terminal.

[0042] In a specific embodiment, when server 02 is a distributed system, this distributed system can be a blockchain system. When the distributed system is a blockchain system, it can be formed by multiple nodes (any form of computing device connected to the network, such as servers or user terminals). These nodes form a peer-to-peer (P2P) network. The P2P protocol is an application layer protocol running on top of the Transmission Control Protocol (TCP). In a distributed system, any machine, such as a server or terminal, can join and become a node. A node includes a hardware layer, a middleware layer, an operating system layer, and an application layer. Specifically, the functions of each node in the blockchain system may include:

[0043] 1) Routing: A basic function of nodes used to support communication between nodes.

[0044] In addition to routing capabilities, nodes can also have the following functions:

[0045] 2) Applications are deployed in the blockchain to implement specific business needs. They record data related to the implementation of functions to form record data, carry digital signatures in the record data to indicate the source of the task data, and send the record data to other nodes in the blockchain system. When other nodes successfully verify the source and integrity of the record data, they add the record data to a temporary block.

[0046] Figure 2 This diagram illustrates a data processing platform according to an embodiment of this application. The data processing method of this application can be performed based on this data processing platform. The data processing platform may include a data standardization device, a data processing model, and a data display device. The data standardization device can be used to standardize a received set of business data tables, converting the business data tables in the set into standard business data tables. These standard business data tables can form a set of standard business data tables. The business data tables can originate from various business scenarios, such as project business data tables, business opportunity business data tables, etc. Each business data table can be in Excel format or other formats. The standard business data table can be a table in a database, for example, a two-dimensional table in a database. In other words, the standardization process may include converting business data tables into tables in a database. Compared to business data tables in Excel format or other formats, converting them into a unified standard business data table in a database facilitates the data processing model in retrieving and processing data from the database, thus realizing the toolification of standard business data tables. The database can be a database associated with the data processing model; this associated database can exist within the data processing model or independently of it.

[0047] In one example, converting a business data table into a standard business data table can be done using the Power Pivot tool. Power Pivot is highly compatible and suitable for scenarios with numerous sources of business data, and it can also quickly analyze large datasets.

[0048] The aforementioned standardization process can also include standardizing the identifiers of the first and second target objects in the business data table, as well as standardizing the format and data type of other fields in the business data table. For example, in investment promotion and sales, the first target object can refer to a project, and its identifier can be the project name; the second target object can refer to a customer, and its identifier can be the customer name. In this case, it can refer to the standardization of the project name and customer name, as well as the standardization of the format and data type of other fields in the business data table.

[0049] In this embodiment of the specification, as an example, the data processing model may include a data processing mechanism and a full set of standard tables. The full set of standard tables may include a first full set of target object standard tables and a second full set of target object standard tables. The first full set of target object standard tables may include full set of standard identifiers for a first target object, and the second target object standard table may include full set of standard identifiers for a second target object. Here, "full set" can refer to the entire set; for example, the full set of standard identifiers for the first target object may refer to the entire set of standard identifiers for the first target object, such as the standard identifiers for all projects; the full set of standard identifiers for the second target object may refer to the entire set of standard identifiers for the second target object, such as the standard identifiers for all customers.

[0050] The aforementioned data processing mechanism can refer to the data processing mechanism corresponding to each target dashboard data type. This mechanism may include a target standard business data table, target fields, target field processing strategies, target dashboard data display strategies, and a corresponding full standard table for each target dashboard data type. Specifically, the target standard business data table can be at least one standard business data table from a set of standard business data tables; the target field can be at least one field from the target standard business data table; and the corresponding full standard table can be either a first full target object standard table or a second full target object standard table. The target field processing strategy and the target dashboard data display strategy can be pre-set based on the target dashboard data type, and this application does not impose any limitations on them.

[0051] In one example, taking project investment promotion as an example, the target dashboard data types can include project revenue / opportunity progress, quarterly project allocation monitoring, and order progress for each customer. The first full target object standard table can be the full project standard table, and the second full target object standard table can be the full customer standard table. The correspondence between target dashboard data types and data processing mechanisms is shown in Table 1 below:

[0052] Table 1

[0053]

[0054] Table 1 is merely an example and does not limit this application. Target dashboard data types can also include project trackability status, potential revenue risks, project opportunity order progress, revenue from projects not listed in the opportunity table, and changes in each customer's purchasing preferences. Target dashboard data types can be set according to actual business monitoring and management needs, allowing users to efficiently access target dashboard data from different management perspectives. For example, the target standard business data table corresponding to project trackability status can include a standard project inventory data table. Based on preset target fields and target field processing strategies, it can quickly compare project revenue, remaining inventory, etc., providing sales guidance for the sales team and improving sales efficiency. Similarly, the target standard business data table corresponding to potential revenue risks can include a standard opportunity data table and a standard revenue data table. By linking these two tables, the project's online status can be monitored, such as project revenue reserves and whether the title sponsorship has been sold, and whether there are risks to the project's estimated revenue. The project opportunity order progress monitoring system can be used to track the order progress of each customer under each project. It can also generate alerts based on this progress, such as if the order progress is lower than the project completion rate or the order amount is lower than the opportunity amount. After verification, an alert can be sent to the relevant monitoring user, who can be a direct sales representative. The revenue from orders not listed in the opportunity table can be quickly retrieved. Because it is linked to both the standard opportunity data table and the standard revenue data table, it allows for granular revenue monitoring. Changes in each customer's purchasing preferences can be monitored to see how their latest purchasing preferences compare to historical preferences. By monitoring each customer's opportunities and revenue, and given a defined customer budget, the conversion rate can be determined. Combined with monitoring of each project, changes in customer purchasing preferences can be analyzed, providing guidance for project recruitment.

[0055] Optionally, a data processing mechanism can be omitted, and the target standard business data table, target fields, target field processing strategies, target dashboard data display strategies, and full standard tables corresponding to the target dashboard data type can be directly set. This application does not impose any restrictions on this.

[0056] In the embodiments described in this specification, the target dashboard data display strategy can also be a curve, bar chart, etc., and this application does not limit it in this way.

[0057] It should be noted that target dashboard data types can be added, reduced, or modified. This means that the target dashboard data types can be adjusted according to changes in actual needs. Users can flexibly set the target dashboard data they need to monitor, thus enabling the efficient and flexible creation of new target dashboard data based on business requirements or new data needs. For the adjusted target dashboard data types, the corresponding data processing mechanism can be set based on practical experience.

[0058] The aforementioned data display device can be used to display various target dashboard data, showcasing the target dashboard data in a unified data display dashboard to form a unified monitoring panel. This enables unified monitoring and management of various business data, thereby ensuring the accuracy of investment forecasting. The data display dashboard can be divided into one or more dashboards. In one example, it can be divided into three dashboards: an overall project dashboard, a project progress dashboard, and a customer progress dashboard. This application does not limit this. For example, the overall project dashboard may include project revenue / opportunity progress, project trackability, and potential revenue risks; the project progress dashboard may include quarterly project allocation monitoring, project opportunity order placement progress, and revenue from orders not placed in the opportunity table; the customer progress dashboard may include each customer's order placement progress and changes in each customer's purchasing preferences, etc.

[0059] In the embodiments of this specification, the data display device can receive target dashboard data and target dashboard data display strategy corresponding to the target dashboard data sent by the data processing model, and thus display the corresponding target dashboard data according to the target dashboard data display strategy.

[0060] Before introducing the data processing method of this application, we will first exemplarily introduce the various business data tables in the business data table set of this application. The following examples all use investment promotion business data, where the first target object is equivalent to the project, and the second target object is equivalent to the customer. The business data table set may include a project data table, which can be used to manage project information, such as investment promotion project information. It may include basic project information, project sales information, etc. Basic project information may include project category, commercial level, etc. Project category can refer to a classification based on project content, such as variety shows, TV dramas, news, sports, etc. Commercial level can refer to the level of the project category, such as the level of viewership corresponding to the project category. For example, a TV drama with over 100 million views per episode is S+ level, 70 million to 100 million views per episode is S level, 30 million to 70 million views per episode is A level, and less than 30 million views per episode is B level. A corresponding level can be set according to the project category; this application does not limit this. Project sales information may include project revenue targets, estimated revenue, etc. The project data table can also include nearly a hundred other fields; this application does not limit this, and the fields in the project data table can be set according to actual business needs. As an example, the project data table can be shown in Table 2. Unless otherwise specified, all units in the following tables are in ten thousands.

[0061] Table 2

[0062]

[0063] In the embodiments of this specification, the business data table set may include a business opportunity data table, which can be used to manage business opportunity information. The business opportunity data table may include basic project information, basic customer information, customer sales information, etc. Basic customer information may include the customer's abbreviation, industry, department, or center. Customer sales information may include cooperation details, cooperation amount, business opportunity status, etc. The business opportunity data table may also include nearly a hundred other fields; this application does not limit this, and the fields in the business opportunity data table can be set according to actual needs. Among them, the business opportunity status may include "Following up," "Basic confirmation of cooperation intention" (which can be abbreviated as WIP), "Order locked," "Order placed," "Expired," etc. As an example, the business opportunity data table for 2019 can be shown in Table 3.

[0064] Table 3

[0065]

[0066] Among them, "following up" can refer to business opportunities with a success rate of more than 30% but less than 60%, such as having progressed to the stage of negotiating prices and resource packages with the client; "WIP" can refer to business opportunities with a success rate of more than 60% but less than 90%, such as having no objection to the price and being in the final confirmation stage of the resource package; "locked in" can refer to business opportunities with a success rate of 90%, such as having the client formally confirmed the cooperation.

[0067] In the embodiments described in this specification, the business data table set may include a revenue data table, which can be used to manage investment attraction revenue information. The revenue data table may include basic project information, basic customer information, revenue information, etc. Revenue information may include cooperation details, cooperation amount, business opportunity status, etc. The revenue data table may also include other fields; this application does not limit this, and the fields in the revenue data table can be set according to actual needs. As an example, the revenue data table may be as shown in Table 4:

[0068] Table 4

[0069]

[0070] In the embodiments of this specification, the business data table set may include a project inventory data table, which can be used to manage project inventory information. The project inventory data table may include sold seat information, unsold seat information, etc., and this application does not limit this; the fields in the inventory data table can be set according to actual needs. Both sold and unsold seat information may include seat identity information, seat quantity, and seat price. The seat information may be seat information for project sponsorship, such as naming rights information for project sponsorship. Seat identity information may include total naming rights, co-naming rights, etc.; the seat quantity may be the number of naming rights a project wants to attract; and the seat price may refer to the funds required for the naming rights sponsorship. As an example, the project inventory data table may be as shown in Table 5:

[0071] Table 5

[0072]

[0073] In the embodiments described in this specification, the business data table set may include a customer interview data table, which can be used to record customer purchasing needs, i.e., to predict the projects that customers will purchase and the number of projects they will be involved in. This application does not limit the fields in this customer interview data table.

[0074] In this embodiment of the specification, based on the aforementioned business data tables, all project names can be counted to obtain a complete set of project names, and deduplication can be performed to ensure the uniqueness of each project name; and a standard name for each project can be determined, i.e., a standard identifier for each first target object can be determined. This yields a project intermediate table (i.e., a first complete target object standard table). As an example, the project intermediate table can be shown in Table 6:

[0075] Table 6

[0076]

[0077] Table 6 is merely an example; it could also include only the serial number and project standard name; or it could include other fields, which could be fields for other dimensions required for monitoring. This application does not limit this, as long as the intermediate project table includes the standard identifiers of all projects, that is, as long as the first full-scale target object standard table includes the full set of standard identifiers of the first target object. This ensures that the standard identifiers of the first target object are included in the complete set, thus allowing association with other standard business data tables based on the full set of standard identifiers of the first target object, achieving a pivot effect for each standard business data table in the data processing model. In one example, the standardization of project names can include the following:

[0078] Number standardization: When project names include data, Arabic numerals can be used, such as XXXX2;

[0079] Year standardization: Use Arabic numerals and place them at the beginning of the project name, such as 2018 Project XXX; unless the project name itself includes the year, follow the original project name, such as Project XXX 2019;

[0080] Standardize projects with the same IP across different channels: place the channel name before the project name, such as TV series "The King's Avatar", anime "The King's Avatar", etc.

[0081] Project prefix standardization: Integrated projects must retain the original project name, for example: Project AAA-Advertising Products, where Project AAA is the original project name; Large network projects retain their channel names, where a large network project could refer to a project on a local website of XX company; otherwise, channel information is not retained, for example, for News-XXX, after standardization it can be XXX.

[0082] Standardize English usage: Use capital letters for abbreviations, such as 2019CNY; capitalize the first letter of English words, such as 2019Live Music.

[0083] Standardize redundant symbols and notes: Redundant symbols and notes should be removed from project names.

[0084] The above are standardized examples of project standard names, that is, standardized examples of standard identifiers of the first target object, and this application does not limit them.

[0085] Based on the same acquisition method used for the intermediate tables of the above projects, customers in the customer list, customers with investment revenue, and customers with business opportunities can be integrated into one table to obtain the intermediate customer table, as shown in Table 7:

[0086] Table 7

[0087]

[0088] Table 7 is merely an example; it could also include only the serial number and customer standard name, or other fields such as those required for monitoring. This application does not limit this, as long as the customer intermediate table includes the standard identifiers of all projects, that is, as long as the second full-scale target object standard table includes all standard identifiers of the second target object. This ensures that the complete set of standard identifiers of the second target object is included, allowing the association of other standard business data tables based on the full set of standard identifiers of the second target object, thus achieving a pivotal effect for each standard business data table in the data processing model. In other words, the embodiments in this specification use the first and second full-scale target object standard tables to associate each standard business data table with the data processing model, providing a foundation for data processing.

[0089] The following describes the data processing method. It should be noted that the diagram below shows one possible sequence of steps, and it is not strictly necessary to follow this order. Some steps can be executed in parallel without interdependence.

[0090] In the embodiments described in this specification, the business data tables in the business data table set can be standardized to obtain a standard business data table set, such as... Figure 2 As shown. For example, a business data table set can be obtained, which may include one or more business data tables; and the business data tables in the business data table set can be standardized to obtain a standard business data table set; wherein, the standard business data table set includes one or more standard business data tables, and the standard business data tables may include the standard identifier of a first target object and / or the standard identifier of a second target object, that is, the standard business data table may include the standard identifier of the first target object, or the standard business data table may include the standard identifier of the second target object, or the standard business data table may include the standard identifier of the first target object and the standard identifier of the second target object.

[0091] In one example, such as Figure 3 As shown, Figure 3This document illustrates a method flowchart for standardizing business data tables in a business data table set according to an embodiment of this application to obtain a standard business data table set. Standardizing the business data tables may include:

[0092] S301, Obtain the first target object identifier mapping table and the second target object identifier mapping table.

[0093] In the embodiments of this specification, the first target object identifier mapping table may include the correspondence between the standard identifier of the first target object and at least one non-standard identifier of the first target object; the second target object identifier mapping table may include the correspondence between the standard identifier of the second target object and at least one non-standard identifier of the second target object.

[0094] In one possible implementation, the first target object identifier mapping table and the second target object identifier mapping table can be pre-set offline. For example, identifier information corresponding to each first target object can be obtained from a business data set. One identifier can be selected from the identifier information corresponding to each first target object as the standard identifier for that first target object, or a standard identifier can be set for each first target object. Identifier information other than the standard identifier in the identifier information corresponding to each first target object can be used as non-standard identifiers for that first target object. Thus, a mapping relationship between the standard identifier and the non-standard identifier of each first target object can be established as the first target object identifier mapping relationship. Based on this first target object identifier mapping relationship, the first target object identifier mapping table can be generated. The second target object identifier mapping table can be generated in the same way.

[0095] S303, extract the identification information of the first target object and the identification information of the second target object from the business data table set;

[0096] S305, obtain the standard identifier of the first target object corresponding to the identifier information of the first target object from the first target object identifier mapping table; and obtain the standard identifier of the second target object corresponding to the identifier information of the second target object from the second target object identifier mapping table;

[0097] S307, if the identification information of the first target object does not match the standard identification of the corresponding first target object, the identification information of the first target object is replaced with the standard identification of the corresponding first target object; and if the identification information of the second target object does not match the standard identification of the corresponding second target object, the identification information of the second target object is replaced with the standard identification of the corresponding second target object; thus obtaining the standard business data table set.

[0098] In this embodiment, if the identification information of the first target object does not match the standard identification of the corresponding first target object, it indicates that the identification information of the first target object is a non-standard identification; if the identification information of the second target object does not match the standard identification of the corresponding second target object, it indicates that the identification information of the second target object is a non-standard identification. S403-S407 above replaces the non-standard identification of the first target object in the business data table with the standard identification of the first target object, and replaces the non-standard identification of the second target object in the business data table with the standard identification of the second target object, thereby obtaining the corresponding standard business data table. The identification information of the first target object included in the standard business data table consists entirely of the standard identification of the first target object, and the identification information of the second target object consists entirely of the standard identification of the second target object. Thus, the standard business data tables can be combined into a standard business data table set.

[0099] Optionally, standardization of business data tables may also include standardizing the format and data type of fields other than the identification information fields, and may also include preprocessing such as data cleaning. Specifically, the format and data type of fields in each business data table may be standardized according to their standard formats and data types.

[0100] like Figure 2 As shown, the obtained standard business data table can be sent to the data processing model for data processing in order to display the target dashboard data. Figure 4 A flowchart illustrating a data processing method according to an embodiment of this application is shown. Figure 4 As shown, the data processing method may include:

[0101] S401, Determine the target Kanban data type.

[0102] In the embodiments of this specification, as shown in Table 1, there are corresponding data processing mechanisms for different Kanban data types. Therefore, the target Kanban data type can be determined from the Kanban data types first. In one example, a preset Kanban data type can be obtained and determined as the target Kanban data type. For example, if there are 8 preset Kanban data types, all 8 Kanban data types can be used as the target Kanban data type. Alternatively, the target Kanban data type can be determined based on a request-triggered method, for example... Figure 5 As shown, this can be achieved through the following steps:

[0103] S501 receives data requests from the target dashboard.

[0104] In the embodiments of this specification, in order to enable users to flexibly select and view target dashboard data, users can select at least one dashboard data type as the target dashboard data type from the dashboard data types. Based on the target dashboard data type selected by the user, a target dashboard data request is generated, and the data processing model can receive the target dashboard data request.

[0105] S503, Obtain the data type of the dashboard in the target dashboard data request;

[0106] S505, the data type of the Kanban data request is determined as the target Kanban data type.

[0107] In the embodiments described in this specification, the data type of the Kanban selected by the user can be determined as the target Kanban data type.

[0108] S403, obtain the target standard business data table and the full standard table corresponding to the target dashboard data type; the full standard table includes a first full target object standard table or a second full target object standard table; the first full target object standard table includes the full standard identifier of the first target object, and the second target object standard table includes the full standard identifier of the second target object.

[0109] In the embodiments of this specification, the target standard business data table and the full standard table corresponding to the target dashboard data type can be obtained. In one example, based on Table 2, the target standard business data table corresponding to the target dashboard data type and the full standard table corresponding to the target dashboard data type can be obtained from the set of standard business data tables.

[0110] S405, extract from the target standard business data table the target field information corresponding to the full standard identifier of the first target object or the target field information corresponding to the full standard identifier of the second target object from the full standard table.

[0111] In the embodiments of this specification, information from all fields corresponding to the full standard identifier of the first target object in the full standard table can be extracted from the corresponding target standard business data table as target field information; or, information from all fields corresponding to the full standard identifier of the second target object in the full standard table can be extracted as target field information.

[0112] In one example, as shown in Table 1, the data processing mechanism corresponding to the target dashboard data type can be obtained. This data processing mechanism includes the target field corresponding to the target dashboard data type. Based on this target field, target field information can be extracted from the corresponding target standard business data table from the target standard table. This includes the target field information from the target field corresponding to the full standard identifier of the first target object and the target field information from the target field corresponding to the full standard identifier of the second target object.

[0113] S407, perform preset calculation processing on the target field information to obtain target dashboard data corresponding to the full standard identifier of the first target object or target dashboard data corresponding to the full standard identifier of the second target object.

[0114] In the embodiments of this specification, the target field information can be processed based on a pre-set target field processing strategy. For example, as shown in Table 1, the target field processing strategy corresponding to the target field can be obtained, and the target field information can be processed based on the corresponding target field processing strategy to obtain the target dashboard data corresponding to the full standard identifier of the first target object and the target dashboard data corresponding to the full standard identifier of the second target object. In one example, the target dashboard data corresponding to the full standard identifier of the first target object can be as follows: Figure 6 and Figure 7 As shown, Figure 6 It can provide overall project dashboard data. Figure 7 This can be used for project progress dashboard data. The fields in the target dashboard data can also have dropdown selection functionality for easy filtering by users. Furthermore, there are other dimension-based filter options on the left, such as resources and platforms, allowing users to filter and view only the target dashboard data under that dimension.

[0115] like Figure 6 As shown, taking "Project XX 3" as an example, the target dashboard data corresponding to the full standard identifier of the first target object is the dashboard data for project revenue / opportunity progress. The information of the target field "Locked Orders + Orders Placed" corresponding to "Project XX 3" can be extracted from the standard opportunity data table. The information of this target field "Locked Orders + Orders Placed" is then added together to obtain... Figure 6 The information for "locked orders + placed orders" corresponding to "Project XX 3" is 4314, which means that we get the sum of the information for "locked orders + placed orders" corresponding to "Project XX 3".

[0116] Optionally, new fields can be generated in the target dashboard data based on the information from each target field, such as opportunity amount, which is calculated as "Following Up" + "WIP" + "Locked Orders + Orders Placed". "Total Revenue" can be obtained from the standard revenue data table. Figure 7 The generation method and Figure 6 The generation method is similar; it can be executed according to the target field processing strategy in the pre-set data processing mechanism.

[0117] Additionally, the target dashboard data can include user interaction areas, such as allowing users to filter the data according to other dimensions, like viewing project revenue / business opportunity progress on a specific platform. This application does not impose any limitations on this. It should be noted that null values ​​in the target dashboard data can refer to the absence of data or a value of zero.

[0118] By setting the data types of the target dashboard and implementing unified data processing based on standard business data tables and full standard tables, multi-dimensional target dashboard data can be obtained, enabling efficient and unified monitoring of the data. Based on this unified monitoring, the rationality of investment promotion business issuance can be guaranteed, adding a guarantee for the stable development of investment promotion business; and the monitored target dashboard data can be used as a guide to make efficient adjustments to investment promotion strategies, further ensuring the effective progress of investment promotion business.

[0119] Furthermore, the full standard table used for data processing contains only standard identifiers, and the standard business data table also contains only standard identifiers, saving storage resources; and by associating various standard business data tables based on this standard table, unified data processing can be performed, which can simplify the data processing flow, save computing resources, and thus make data processing more efficient and the response to business more timely.

[0120] Furthermore, since all fields in the standard business data table are standardized, and the full standard table contains the full standard identifiers of both the first and second target objects, the comprehensiveness of the acquired first and second target objects can be guaranteed. This ensures that the data obtained from the target standard business data table is also comprehensive, and the target dashboard data obtained based on comprehensive data processing will be more accurate. Moreover, this standardized and unified data processing method has strong adaptability to business expansion and data additions, exhibiting good universality and scalability.

[0121] In one possible implementation, Figure 8 A flowchart illustrating a data processing method according to an embodiment of this application is shown. Figure 8 As shown, after obtaining the target dashboard data corresponding to the full standard identifiers of the first target object or the full standard identifiers of the second target object, the data processing method may further include:

[0122] S801, analyze the target dashboard data to generate early warning information and data prediction information; or, analyze the target dashboard data to generate the early warning information; or, analyze the target dashboard data to generate the data prediction information.

[0123] In the embodiments of this specification, the target dashboard data can be further analyzed to generate early warning information and data prediction information; or, the target dashboard data can be analyzed to generate the early warning information; or, the target dashboard data can be analyzed to generate the data prediction information, thereby achieving efficient and accurate prediction and early warning of investment promotion business.

[0124] Optionally, the early warning information or data prediction information can be displayed in conjunction with the target dashboard data, such as... Figure 9 As shown, for example, the target dashboard data type is the order progress of each customer. The alert information here could refer to the current progress, i.e., the health of the customer's revenue. Different shades of color can be used to represent different current progress indicators. In one example, an estimated percentage below 30% could be represented by a dark color, an estimated percentage greater than or equal to 30% but less than 50% by a medium color, and an estimated percentage greater than or equal to 50% by a light color. This provides a clear understanding of the target dashboard data. In another example, red, yellow, and green lights can be used to represent the current progress. For instance, an estimated percentage below 30% could be represented by red, an estimated percentage greater than or equal to 30% but less than 50% by yellow, and an estimated percentage greater than or equal to 50% by green. The estimated percentage could be the ratio of 19 estimated business opportunities (2019 estimated business opportunities) divided by 18 brand recruitment (2018 brand recruitment). The estimated business opportunity for 19 can be the fields in the standard business opportunity data table: "Following Up", "WIP", and "Order Placed + Locked Order", with the corresponding information weights summed. For example, the estimated business opportunity for 19 can be 50% of "Following Up" + "WIP" + "Order Placed + Locked Order".

[0125] Optionally, each field in the target dashboard data can be selected via a dropdown menu for easy access to desired information. Furthermore, the left side allows for filtering by other dimensions such as department and industry; for example, filtering to view customers from Industry Department 1.

[0126] Figure 10 A flowchart illustrating a data processing method according to an embodiment of this application is shown. Figure 10 As shown, the method may further include:

[0127] S1001, retrieve the business data table set;

[0128] S1003, count the first target object and the second target object in the business data table set.

[0129] In the embodiments of this specification, statistics can be performed on the first target object and the second target object in the business data table set, such as statistics on projects and customers in the business data table set, to obtain the complete set of projects and the complete set of customers.

[0130] S1005, determine the corresponding standard identifier for each first target object and each second target object.

[0131] In the embodiments of this specification, a corresponding standard identifier can be determined for each first target object and each second target object. For example, one of the identifier information corresponding to each first target object can be determined as the standard identifier for each first target object, or a standard identifier can be determined for each first target object, which is different from the identifier information corresponding to each first target object. Based on the same method, a corresponding standard identifier can be determined for each second target object.

[0132] S1007, Generate the first full target object standard table based on the standard identifier corresponding to each first target object;

[0133] S1009, Generate a second full target object standard table based on the standard identifier corresponding to each second target object.

[0134] In the embodiments of this specification, a first full target object standard table can be generated based on the standard identifier corresponding to each first target object, such that the first full target object standard table includes all standard identifiers of the first target objects, that is, it includes the complete set of standard identifiers of the first target objects. Similarly, a second full target object standard table can be generated based on the standard identifier corresponding to each second target object.

[0135] Optionally, the first and second full-scale target object standard tables can also be updated or maintained. In one possible implementation, an updated set of business data tables can be obtained; and the first and second full-scale target object standard tables can be periodically updated based on the updated set of business data tables.

[0136] In this embodiment, the identification information of the first target object can be periodically extracted from the updated business data table set. A corresponding standard identifier can be searched in the first target object identifier mapping table based on the identification information of the first target object. If no match is found, the identification information of the first target object can be considered as the identification information of a newly added first target object in the business. A corresponding standard identifier can be determined for the identification information of the first target object, and then the standard identifier can be added to the first full-scale target object standard table, thereby achieving periodic updates to the first full-scale target object standard table. Using the same method, periodic updates to the second full-scale target object standard table can be achieved.

[0137] Optionally, the newly added identifier information of the first target object and its corresponding standard identifier can be added to the first target object identifier mapping table to update the first target object identifier mapping table. The second target object identifier mapping table can be updated in the same way.

[0138] By periodically updating the first and second full-volume target object standard tables, the need for continuously increasing business data tables can be met.

[0139] Figure 11 A block diagram of a data processing apparatus according to an embodiment of this application is shown. Figure 11 As shown, the device may include:

[0140] The target Kanban data type determination module 1101 is used to determine the target Kanban data type.

[0141] The target standard business data table and full standard table acquisition module 1103 is used to acquire the target standard business data table and full standard table corresponding to the target dashboard data type; the full standard table includes a first full target object standard table or a second full target object standard table; the first full target object standard table includes the full standard identifier of the first target object, and the second target object standard table includes the full standard identifier of the second target object.

[0142] The target field information extraction module 1105 is used to extract the target field information corresponding to the full standard identifier of the first target object and the target field information corresponding to the full standard identifier of the second target object from the target standard business data table.

[0143] The target dashboard data acquisition module 1107 is used to perform data calculation and processing on the target field information to obtain the target dashboard data corresponding to the full standard identifier of the first target object and the target dashboard data corresponding to the full standard identifier of the second target object.

[0144] By setting the data types of the target dashboard and implementing unified data processing based on standard business data tables and full standard tables, multi-dimensional target dashboard data can be obtained, enabling efficient and unified monitoring of the data. Based on this unified monitoring, the rationality of investment promotion business issuance can be guaranteed, adding a guarantee for the stable development of investment promotion business; and the monitored target dashboard data can be used as a guide to make efficient adjustments to investment promotion strategies, further ensuring the effective progress of investment promotion business.

[0145] Furthermore, the full standard table used for data processing contains only standard identifiers, and the standard business data table also contains only standard identifiers, saving storage resources; and by associating various standard business data tables based on this standard table, unified data processing can be performed, which can simplify the data processing flow, save computing resources, and thus make data processing more efficient and the response to business more timely.

[0146] Furthermore, since all fields in the standard business data table are standardized, and the full standard table contains the full standard identifiers of both the first and second target objects, the comprehensiveness of the acquired first and second target objects can be guaranteed. This ensures that the data obtained from the target standard business data table is also comprehensive, and the target dashboard data obtained based on comprehensive data processing will be more accurate. Moreover, this standardized and unified data processing method has strong adaptability to business expansion and data additions, exhibiting good universality and scalability.

[0147] In one possible implementation, the device may further include:

[0148] The first business data table acquisition module is used to acquire the business data table set;

[0149] The statistics module is used to perform statistics on the first target object and the second target object in the business data table set;

[0150] The standard identifier determination module is used to determine the corresponding standard identifier for each first target object and each second target object;

[0151] The first full-scale target object standard table generation module is used to generate the first full-scale target object standard table based on the standard identifier corresponding to each first target object.

[0152] The second full-scale target object standard table generation module is used to generate a second full-scale target object standard table based on the standard identifier corresponding to each second target object.

[0153] In one possible implementation, the device may further include:

[0154] The target field acquisition module is used to acquire the target field corresponding to the target standard business data table.

[0155] The target field information extraction module 1105 may include:

[0156] The target field information extraction unit is used to extract, based on the target field corresponding to the target standard business data table, the target field information in the target field corresponding to the full standard identifier of the first target object in the full standard table, and the target field information in the target field corresponding to the full standard identifier of the second target object, from the corresponding target standard business data table.

[0157] In one possible implementation, the device may further include:

[0158] The target field processing strategy acquisition module is used to acquire the target field processing strategy corresponding to the target field.

[0159] The target dashboard data acquisition module 1107 may include:

[0160] The target dashboard data acquisition unit is used to process the target field information based on the target field processing strategy to obtain the target dashboard data corresponding to the full standard identifier of the first target object and the target dashboard data corresponding to the full standard identifier of the second target object.

[0161] In one possible implementation, the device may further include:

[0162] The target dashboard data display strategy acquisition module is used to acquire the target dashboard data display strategy corresponding to the target dashboard data type.

[0163] The display module is used to display the corresponding target dashboard data according to the target dashboard data display strategy.

[0164] In one possible implementation, the device may further include:

[0165] The analysis module is used to analyze the target dashboard data and generate early warning information and data prediction information; or, analyze the target dashboard data and generate the early warning information; or, analyze the target dashboard data and generate the data prediction information.

[0166] In one possible implementation, the target Kanban data type determination module 1101 may include:

[0167] The first target Kanban data type determination unit is used to obtain a preset Kanban data type and determine the preset Kanban data type as the target Kanban data type; or,

[0168] The target dashboard data request unit is used to receive target dashboard data requests.

[0169] A Kanban data type acquisition unit is used to acquire the Kanban data type in the target Kanban data request.

[0170] The second target dashboard data type determination unit is used to determine the dashboard data type in the target dashboard data request as the target dashboard data type.

[0171] In one possible implementation, the device may further include:

[0172] The updated business data table acquisition module is used to acquire the updated business data table set;

[0173] The business data table update module is used to periodically update the first full target object standard table and the second full target object standard table based on the updated business data table set.

[0174] In one possible implementation, the device may further include:

[0175] The second business data table acquisition module is used to acquire the business data table set.

[0176] The standardization processing module is used to standardize the business data tables in the business data table set to obtain a standard business data table set; wherein, the standard business data table set includes a standard identifier of a first target object or a standard identifier of a second target object; optionally, the standard business data table set includes a standard identifier of the first target object and a standard identifier of the second target object.

[0177] Accordingly, the target standard business data table and the full standard table acquisition module 1103 may include:

[0178] The target standard business data table acquisition unit is used to acquire the target standard business data table corresponding to the target dashboard data type from the set of standard business data tables.

[0179] In one possible implementation, the standardization processing module may include:

[0180] The mapping relationship table acquisition unit is used to acquire the first target object identifier mapping relationship table and the second target object identifier mapping relationship table;

[0181] The identification information extraction unit is used to extract the identification information of the first target object and the identification information of the second target object from the business data table set.

[0182] The standard identifier acquisition unit is configured to acquire, from the first target object identifier mapping table, the standard identifier of the first target object corresponding to the identifier information of the first target object; and to acquire, from the second target object identifier mapping table, the standard identifier of the second target object corresponding to the identifier information of the second target object;

[0183] The standardization processing unit is configured to replace the identification information of the first target object with the standard identification of the corresponding first target object if the identification information of the first target object does not match the standard identification of the corresponding first target object; and replace the identification information of the second target object with the standard identification of the corresponding second target object if the identification information of the second target object does not match the standard identification of the corresponding second target object; thereby obtaining a corresponding standard business data table.

[0184] The standard business data table set acquisition unit is used to obtain a standard business data table set based on the standard business data table.

[0185] Regarding the apparatus in the above embodiments, the specific manner in which each module and unit performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0186] On the other hand, this application provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the data processing methods provided in the various optional implementations described above.

[0187] Figure 12 This is a block diagram illustrating a data processing apparatus 1200 according to an exemplary embodiment. For example, apparatus 1200 may be provided as a server. (Refer to...) Figure 12 The apparatus 1200 includes a processing component 1222, which further includes one or more processors, and memory resources represented by memory 1232 for storing instructions, such as application programs, that can be executed by the processing component 1222. The application programs stored in memory 1232 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1222 is configured to execute instructions to perform the methods described above.

[0188] Device 1200 may also include a power supply component 1226 configured to perform power management of device 1200, a wired or wireless network interface 1250 configured to connect device 1200 to a network, and an input / output (I / O) interface 1258. Device 1200 can operate on an operating system stored in memory 1232, such as Windows Server™, MacOS X™, Unix™, Linux™, FreeBSD™, or similar.

[0189] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1232 including computer program instructions that can be executed by the processing component 1222 of the device 1200 to perform the above-described method.

[0190] This application may be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this application.

[0191] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0192] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0193] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing the status information of the computer-readable program instructions. These electronic circuits can execute the computer-readable program instructions to implement various aspects of this application.

[0194] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0195] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0196] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0197] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0198] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A data processing method, characterized by, The method includes: Determine the target dashboard data type and the corresponding data processing mechanism; the target dashboard data type includes a preset dashboard data type or the dashboard data type in the target dashboard data request; Based on the aforementioned data processing mechanism, the target standard business data table and the full standard table corresponding to the target dashboard data type are obtained. The full standard table includes either a first full target object standard table or a second full target object standard table. The first full target object standard table includes the full standard identifier of the first target object, and the second full target object standard table includes the full standard identifier of the second target object. The target standard business data table is at least one standard business data table in the standard business data table set. The first target object includes projects, and the second target object includes customers. The full standard identifier of the first target object includes the project standard name of all projects, and the full standard identifier of the second target object includes the customer standard name of all customers. All projects and all customers are obtained based on statistics from the business data table set. Extract the target field information corresponding to the full standard identifier of the first target object or the target field information corresponding to the full standard identifier of the second target object from the target standard business data table. The target field information is processed by a preset operation to obtain the target dashboard data corresponding to the full standard identifier of the first target object or the target dashboard data corresponding to the full standard identifier of the second target object. Before determining the target dashboard data type, the method further includes: obtaining the business data table set, the first target object identifier mapping table, and the second target object identifier mapping table; extracting the identifier information of the first target object and the identifier information of the second target object from the business data table set; obtaining the standard identifier of the first target object corresponding to the identifier information of the first target object from the first target object identifier mapping table; obtaining the standard identifier of the second target object corresponding to the identifier information of the second target object from the second target object identifier mapping table; if the identifier information of the first target object does not match the standard identifier of the corresponding first target object, replacing the identifier information of the first target object with the standard identifier of the corresponding first target object; and if the identifier information of the second target object does not match the standard identifier of the corresponding second target object, replacing the identifier information of the second target object with the standard identifier of the corresponding second target object; thus obtaining the standard business data table set.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the aforementioned business data table set; The first target object and the second target object in the business data table set are statistically analyzed. Determine a corresponding standard identifier for each first target object and each second target object; Based on the standard identifier corresponding to each first target object, the first full target object standard table is generated; Based on the standard identifier corresponding to each second target object, a standard table of the second full target object is generated.

3. The method according to claim 1, characterized in that, The method further includes: Obtain the target field corresponding to the target standard business data table; The step of extracting the target field information corresponding to the full standard identifier of the first target object or the target field information corresponding to the full standard identifier of the second target object from the target standard business data table includes: Based on the target field corresponding to the target standard business data table, extract the target field information from the target field corresponding to the full standard identifier of the first target object in the full standard table, or the target field information from the target field corresponding to the full standard identifier of the second target object in the full standard table.

4. The method according to claim 3, characterized in that, The method further includes: Obtain the target field processing strategy corresponding to the target field; The step of performing preset calculations on the target field information to obtain target dashboard data corresponding to the full standard identifier of the first target object or the full standard identifier of the second target object includes: Based on the target field processing strategy, the target field information is processed to obtain target dashboard data corresponding to the full standard identifier of the first target object, or target dashboard data corresponding to the full standard identifier of the second target object.

5. The method according to claim 1, characterized in that, The method further includes: The target dashboard data is analyzed to generate early warning messages and data prediction information; or, The target dashboard data is analyzed to generate the warning message; or, The target dashboard data is analyzed to generate the data prediction information.

6. The method according to claim 1, characterized in that, The determination of the target dashboard data type includes: Obtain the preset Kanban data type and determine the preset Kanban data type as the target Kanban data type; or, Receive the target dashboard data request; Obtain the data type of the Kanban in the target Kanban data request; The data type of the Kanban data request is determined as the target Kanban data type.

7. The method according to claim 1, characterized in that, The step of obtaining the target standard business data table corresponding to the target dashboard data type includes: Obtain the target standard business data table corresponding to the target dashboard data type from the standard business data table set.

8. A data processing apparatus, characterized in that, include: The target dashboard data type determination module is used to determine the target dashboard data type and the data processing mechanism corresponding to the target dashboard data type. The target dashboard data type includes a preset dashboard data type or the dashboard data type in the target dashboard data request; The target standard business data table and full standard table acquisition module is used to acquire the target standard business data table and full standard table corresponding to the target dashboard data type based on the data processing mechanism; the full standard table includes a first full target object standard table or a second full target object standard table; The first full-volume target object standard table includes the full-volume standard identifier of the first target object, and the second full-volume target object standard table includes the full-volume standard identifier of the second target object; the target standard business data table is at least one standard business data table in the standard business data table set; the first target object includes projects, and the second target object includes customers; the full-volume standard identifier of the first target object includes the project standard name of all projects, and the full-volume standard identifier of the second target object includes the customer standard name of all customers; all projects and all customers are obtained based on statistics from the business data table set; The target field information extraction module is used to extract target field information corresponding to the full standard identifier of the first target object or the target field information corresponding to the full standard identifier of the second target object from the target standard business data table. The target dashboard data acquisition module is used to perform preset calculations on the target field information to obtain the target dashboard data corresponding to the full standard identifier of the first target object or the target dashboard data corresponding to the full standard identifier of the second target object. The apparatus further includes: a second business data table acquisition module, used to acquire the business data table set; a standardization processing module, used to acquire a first target object identifier mapping relationship table and a second target object identifier mapping relationship table; extract the identifier information of the first target object and the identifier information of the second target object from the business data table set; acquire the standard identifier of the first target object corresponding to the identifier information of the first target object from the first target object identifier mapping relationship table; acquire the standard identifier of the second target object corresponding to the identifier information of the second target object from the second target object identifier mapping relationship table; if the identifier information of the first target object does not match the standard identifier of the corresponding first target object, replace the identifier information of the first target object with the standard identifier of the corresponding first target object; and if the identifier information of the second target object does not match the standard identifier of the corresponding second target object, replace the identifier information of the second target object with the standard identifier of the corresponding second target object; thereby obtaining the standard business data table set.

9. The apparatus according to claim 8, characterized in that, The device further includes: The first business data table acquisition module is used to acquire the set of business data tables. The statistics module is used to perform statistics on the first target object and the second target object in the business data table set; The standard identifier determination module is used to determine the corresponding standard identifier for each first target object and each second target object; The first full-scale target object standard table generation module is used to generate the first full-scale target object standard table based on the standard identifier corresponding to each first target object. The second full-scale target object standard table generation module is used to generate the second full-scale target object standard table based on the standard identifier corresponding to each second target object.

10. The apparatus according to claim 8, characterized in that, The device further includes: The target field acquisition module is used to acquire the target field corresponding to the target standard business data table. The target field information extraction module includes: The target field information extraction unit is used to extract, based on the target field corresponding to the target standard business data table, the target field information in the target field corresponding to the full standard identifier of the first target object in the full standard table, and the target field information in the target field corresponding to the full standard identifier of the second target object, from the corresponding target standard business data table.

11. The apparatus according to claim 10, characterized in that, The device further includes: The target field processing strategy acquisition module is used to acquire the target field processing strategy corresponding to the target field. The target dashboard data acquisition module includes: The target dashboard data acquisition unit is used to process the target field information based on the target field processing strategy to obtain the target dashboard data corresponding to the full standard identifier of the first target object and the target dashboard data corresponding to the full standard identifier of the second target object.

12. The apparatus according to claim 8, characterized in that, The device further includes: The analysis module is used to analyze the target dashboard data and generate early warning information and data prediction information; or, analyze the target dashboard data and generate the early warning information; or, analyze the target dashboard data and generate the data prediction information.

13. The apparatus according to claim 9, characterized in that, The target dashboard data type determination module includes: The first target Kanban data type determination unit is used to obtain the preset Kanban data type and determine the preset Kanban data type as the target Kanban data type; or, The target dashboard data request unit is used to receive the target dashboard data request; A Kanban data type acquisition unit is used to acquire the Kanban data type in the target Kanban data request. The second target dashboard data type determination unit is used to determine the dashboard data type in the target dashboard data request as the target dashboard data type.

14. The apparatus according to claim 8, characterized in that, The target standard business data table and the full standard table acquisition module include: The target standard business data table acquisition unit is used to acquire the target standard business data table corresponding to the target dashboard data type from the set of standard business data tables.

15. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

16. A computer program product, characterized in that, Includes computer instructions, which, when executed by a processor, cause the computer to perform the method as described in any one of claims 1 to 7.

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