Database-based data processing method, device, equipment and storage medium

Abstract

Embodiments of the present application provide a kind of based on database data processing method, device and equipment and storage medium.The method comprises: obtaining the data set generated by preset business in preset use scene;Wherein, multiple business links are included in preset business, business link includes at least one of business item and business department, and the data set includes in the first time period of preset, the multiple detailed data of business department on business item;For each business department and each business item, determine the target details of business department on business item in the first time period of preset;Wherein, target details represent the multiple detailed data of business department in business item;According to the target details of each business department in each business item, build target data table;Wherein, the data stored in target data table is used to generate the data report of preset business.The method is used to improve the data processing efficiency of database.

Description

Technical Field

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

[0002] With the explosive growth of enterprise data, there is a need to store the data to meet data analysis requirements.

[0003] In traditional data warehouses, there is a high degree of data redundancy between data tables, which leads to low efficiency in database data processing (such as database operations such as adding, deleting, modifying, and querying).

[0004] Therefore, how to optimize data storage in a database to improve its data processing efficiency has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides a database-based data processing method, apparatus, device, and storage medium to achieve the technical effect of improving the data processing efficiency of the database.

[0006] In a first aspect, embodiments of this application provide a database-based data processing method, including:

[0007] Acquire a dataset generated by a preset business under a preset usage scenario; wherein, the preset business includes multiple business links, the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of business departments on business projects within a preset first time period;

[0008] For each business department and each business project, the target details of the business department in the business project are determined within the preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project.

[0009] Based on the detailed objectives of each business department for each business project, a target data table is constructed; wherein, the data stored in the target data table is used to generate data reports for preset businesses.

[0010] In one possible implementation, the dataset includes environmental information and identification information corresponding to the business process, wherein the environmental information represents a detailed explanation of the business process; and before determining the target details of the business project within the preset first time period, the dataset further includes:

[0011] A first data table is generated based on multiple detailed data entries of the business department on business projects, the identification information of the business department, and the identification information of the business project. In this first data table, rows represent preset times; the preset times are located within a preset first time period; the preset times represent the time when the detailed data was generated; the first data table includes at least a first column, a second column, and a third column, where the first column represents the business department, the second column represents the business project, and the third column represents the detailed data; the field values ​​corresponding to the rows and the first column represent the identification information of the business department, the field values ​​corresponding to the rows and the second column represent the identification information of the business project, and the field values ​​corresponding to the rows and the third column represent the detailed data.

[0012] A second data table is determined based on the identification information of the business process and the environmental information corresponding to the business process; wherein the second data table includes at least a fourth column and a fifth column; the fourth column identifies the identification information of the business process, and the fifth column identifies the environmental information of the business process.

[0013] In one possible implementation, determining the target details of the business department for each business unit and each business project within the preset first time period includes:

[0014] Obtain detailed data of each business department for each business project from the first data table;

[0015] For each business unit and each business project, the target details of the business unit in the business project are determined based on multiple detailed data.

[0016] In one possible implementation, constructing the target data table based on the target details of each business department for each business project includes:

[0017] Obtain the identification information and environmental information of each business process from the second data table;

[0018] Based on the identification information of each business link, the environmental information of each business link, and the target details of each business department in each business project, a target data table is constructed; wherein, the target data table includes a sixth column, a seventh column, and an eighth column; the sixth column identifies the identification information of the business link; the seventh column identifies the environmental information of the business link; the eighth column identifies the target details; and the rows of the target data table represent preset usage scenarios.

[0019] In one possible implementation, generating a first data table based on multiple detailed data entries of the business department on business projects, the identification information of the business department, and the identification information of the business projects includes:

[0020] According to the preset first data processing rule, the multiple detailed data of the business department on the business project, the identification information of the business department, and the identification information of the business project are respectively converted and processed.

[0021] The first data table is obtained based on the processed data.

[0022] In one possible implementation, after constructing a target data table based on the target details of each business department for each business project, the method further includes:

[0023] Based on the target data table, and using a preset second time period, multiple target details for each business department are obtained; the preset second time period includes at least one first time period.

[0024] A third data table is constructed based on the identification information of the business department and the multiple target details of the business department; wherein, the rows in the third data table represent a preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column representing the identification information of the business department; and the tenth column representing the sum of the multiple target details corresponding to the business department.

[0025] In one possible implementation, the method further includes:

[0026] From the third data table, obtain the sum of multiple target details for the business department within a preset second time period;

[0027] Retrieve the detailed target information of the business department within a preset second time period from the target data table;

[0028] Based on the sum of the multiple target details and the multiple target details, a fourth data table corresponding to the business department is constructed; wherein, the rows of the fourth data table represent a preset first time period; the fourth data table includes at least an eleventh column and a twelfth column; the eleventh column represents the target details of the business department; the twelfth column represents the ratio; the ratio represents the ratio of the target details to the sum of the multiple target details.

[0029] In one possible implementation, the method further includes:

[0030] Obtain the real-time generated data of the preset service in each business process;

[0031] Based on the real-time generated data and the fourth data table, a data report for the preset business is generated.

[0032] In one possible implementation, the method further includes:

[0033] In response to a data table query command, a data table to be queried is determined; wherein, the data table to be queried is at least one of a first data table, a second data table, a third data table, a fourth data table, and a target data table;

[0034] Starting from the fourth data table, the data table to be queried is obtained based on the preset data table query order.

[0035] Secondly, embodiments of this application provide a database-based data processing apparatus, comprising:

[0036] The acquisition module is used to acquire the dataset generated by the preset business under the preset usage scenario; wherein, the preset business includes multiple business links, the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of the business department on the business project within a preset first time period;

[0037] The determination module is used to determine, for each business department and each business project, the target details of the business department in the business project within the preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project;

[0038] The construction module is used to build a target data table based on the target details of each business department in each business project; wherein, the data stored in the target data table is used to generate data reports for preset businesses.

[0039] Thirdly, embodiments of this application provide a database-based data processing device, including: a memory and a processor;

[0040] The memory stores computer-executed instructions;

[0041] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0042] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0043] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0044] The database-based data processing method, apparatus, device, and storage medium provided in this application acquire a dataset generated by a preset business in a preset usage scenario. The preset business includes multiple business steps, each including at least one of business projects and business departments. The dataset includes multiple detailed data entries from each business department on a business project within a preset first time period. Since the detailed data is associated with the business department and business project, it can be used to construct a data table subsequently, incorporating this association. For each business department and each business project, target details are determined within the preset first time period. These target details represent multiple detailed data entries from each business department on the business project. Preliminary aggregation of these multiple detailed data entries is performed to ensure that the aggregated target details meet the data requirements for generating subsequent data reports. Aggregated target details also reduce query time, thereby improving data processing efficiency. A target data table is constructed based on the target details of each business department on each business project. The data stored in the target data table is used to generate data reports for the preset business. Because detailed data is related to business departments and projects, and target details represent multiple detailed data entries, target details are also related to business departments and projects. The target data table built based on target details can aggregate target details, business departments, and business projects. This allows for accurate data retrieval by simply scanning and filtering a single table when generating subsequent data reports, thereby reducing the number of query operations and improving data processing and management efficiency. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] Figure 1 Flowchart of the database-based data processing method provided in this application Figure 1 ;

[0047] Figure 2 Flowchart of the database-based data processing method provided in this application Figure 2 ;

[0048] Figure 3 A schematic diagram of the first data table provided for this application;

[0049] Figure 4 A schematic diagram of the target data table provided for this application;

[0050] Figure 5 Flowchart of the database-based data processing method provided in this application Figure 3 ;

[0051] Figure 6 Flowchart of the database-based data processing method provided in this application Figure 4 ;

[0052] Figure 7 A schematic diagram of the database structure provided in this application;

[0053] Figure 8 A schematic diagram of the structure of the database-based data processing device provided in this application;

[0054] Figure 9 A schematic diagram of the structure of the database-based data processing device provided in this application.

[0055] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0056] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0057] First, let me explain the terms used in this application:

[0058] Data lake: A centralized storage system used to centrally store raw, unprocessed data;

[0059] A data warehouse is a highly structured, integrated data storage system used to store data that has undergone processing, cleaning, modeling, and other data processing operations.

[0060] The application scenarios of this application include storing data of enterprises (especially those with large data output, such as oil companies).

[0061] In the era of big data, the amount of enterprise data is growing explosively. This data includes highly structured data, semi-structured data, and unstructured data, which can be stored in databases.

[0062] In related technologies, data lakes and data warehouses are used to store data. Data lakes can store structured, semi-structured, and unstructured data, while data warehouses can store structured data. Data is stored by creating tables within the data lake and data warehouse. Different tables in data lakes and data warehouses are interconnected, potentially storing a large amount of redundant data. For example, a department table might be created in the data lake to store department information, and a project table might be created to store project information. To retrieve project information, the corresponding department information could also be retrieved, resulting in the project table also storing complete department information, leading to a large amount of redundant data in both tables. Similarly, when creating a database, to facilitate data copying, the data warehouse might copy a large amount of business-irrelevant data from the data lake and store it in data tables, resulting in a large amount of redundant data in the data warehouse.

[0063] Because data lakes do not require data processing (such as data modeling) and can directly store raw data, they offer high flexibility and can store data in various formats. However, the diverse structured data also leads to low query efficiency in data lakes. Data warehouses, on the other hand, store structured data, enabling rapid aggregation and scanning of large amounts of data, thus offering high query efficiency. However, the highly structured data results in lower flexibility, making it unable to store data in multiple formats. Related technologies have failed to leverage the respective advantages of data lakes and data warehouses in their data table design, creating numerous tables solely based on business needs. This leads to low data management efficiency, high data maintenance costs, and low data manipulation efficiency.

[0064] The database-based data processing provided in this application is intended to solve the aforementioned technical problems.

[0065] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0066] Figure 1 Flowchart of the database-based data processing method provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0067] S101. Obtain the dataset generated by the preset business under the preset usage scenario; wherein, the preset business includes multiple business links, and the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of the business departments on business projects within the preset first time period.

[0068] It should be noted that the executing entity of this application can be a business management system of an enterprise or other electronic devices; this application does not make any requirements regarding which. The following explanation uses a business management system as the executing entity.

[0069] For example, in response to a data storage instruction sent by a user, the instruction may instruct the data generated by a preset business in a preset scenario to be saved to a database. The database is used to store the data, and the business management system obtains the dataset generated by the preset business in the preset usage scenario. The preset business includes multiple business steps, which may include at least one of business projects and business departments. The dataset includes multiple detailed data entries from the business departments on business projects within a preset first time period. These detailed data entries may be a breakdown of costs incurred by the business departments when executing business projects, such as labor costs and equipment procurement costs.

[0070] The preset business can be any business activity of the enterprise, such as the enterprise's software development business. The preset use case can be the use case corresponding to the dataset. Each piece of data in a dataset can be generated under different preset use cases. For example, the software development business generates human resource cost data, and the use case corresponding to human resource cost data is the payment of wages to software development personnel. The software development business also generates procurement cost data, and the use case corresponding to procurement cost data is the configuration of hardware equipment for software development. Human resource cost data and procurement cost data are data in the dataset. Therefore, the data in the dataset includes data generated under at least two preset use cases, namely: the use case of paying wages to software development personnel and the use case of configuring hardware equipment for software development.

[0071] Business projects represent projects within a predefined business scope, such as software development projects or oilfield extraction projects. Business departments represent departments that execute business projects, such as departments that perform software development or oilfield extraction. When constructing data tables later, data can be organized according to business processes. For example, if a business process includes both business projects and business departments, detailed data corresponding to both can be recorded in the data table; if a business process includes business departments but not business projects, detailed data corresponding to the business departments can be recorded in the data table; if a business process includes business projects but not business departments, detailed data corresponding to the business projects can be recorded in the data table.

[0072] The first time period can be a preset time length during the business execution process. For example, if a preset business data report needs to be generated based on subsequent requirements, and the data in the data report is accurate to at least daily data, then the first time period can be 24 hours of a day. Therefore, the first time period is 24 hours of a specific day during the business execution process.

[0073] Each piece of detailed data can be a single data point from a business department on a business project at any given moment within the first time period. For example, detailed data can be obtained from a business invoice. If a cost expense in the business invoice is a single expenditure, such as the purchase cost expense data at 9:00 AM on a certain day, then the detailed data obtained will be that purchase cost expense data. If a cost expense in the business invoice is an accumulated expenditure, such as the sum of purchase cost expenses from the start of the business up to 9:00 AM on a certain day, then the detailed data obtained will be the sum of those purchase cost expenses.

[0074] S102. For each business department and each business project, determine the target details of the business department in the business project within a preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project.

[0075] For example, for each business department and each business project, the target details of the business department in executing the business project are determined within a preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project.

[0076] For example, for any business department and any business project, if the detailed data is a single expenditure, the sum of multiple detailed data of the business department in the business project within a preset first time period can be calculated, and the sum obtained can be determined as the target details of the business department in the business project within the preset first time period.

[0077] If the detailed data represents the sum of multiple expenditures, for any business department and any business project, the maximum value of multiple detailed data points for that business department within that business project can be calculated within a preset first time period. This maximum value is then determined as the target detail for that business department within the business project within the preset first time period. In other words, if a single detailed data point represents the sum of multiple expenditures, then one of these detailed data points is taken as the target detail, and this target detail is the maximum value among the multiple detailed data points.

[0078] S103. Based on the target details of each business department in each business project, construct a target data table; the data stored in the target data table is used to generate data reports for preset businesses.

[0079] For example, after obtaining the target details for each business department in each business project, a target data table can be constructed based on these details. The data stored in the target data table is used to generate data reports for pre-defined business operations. The target data table can be constructed within a data lake or data warehouse.

[0080] For example, based on the target details of each business department in each business project, a target data table is built in the data warehouse. The data in the target data table includes each target detail. The data in the target data table can also include the business department and business project corresponding to the target detail. For example, the constructed target data table includes multiple rows and multiple columns. Rows represent preset use cases; different rows can correspond to the same use case or different use cases. Any column can represent any one of the target detail, business department, or business project. If the column represents the target detail, then the row and the corresponding field value of the column represent the target detail. If the column represents the business department, then the row and the corresponding field value of the column represent the business department. If the column represents the business project, then the row and the corresponding field value of the column represent the business project. Each target detail is recorded in different rows of the same column in the target data table; that is, for each row under that column, the row and the corresponding field value of the column represent the target detail. Each business department is recorded in different rows of the same column in the target data table. This means the column is different from the column corresponding to the target details. For each row under this column, the field values ​​of that row and column represent the business department. For example, the first row under this column has the field value for the department performing software development, and the second row has the field value for the department performing oilfield extraction. Similarly, each business project is recorded in different rows of the same column in the target data table. This column is different from the column corresponding to the target details and the column corresponding to the business department. For each row, the field values ​​of that row and column represent the business project. For example, the first row under this column has the field value for a software development project, and the second row has the field value for an oilfield extraction project. For each row, the target details in that row correspond to the target details of the business department within that row for that specific business project.

[0081] When generating data reports for a pre-defined business, database query statements can be used to retrieve data from the target data table, such as target details and the corresponding business departments and projects. Based on the retrieved data, a data report is generated. The data report contains the target details and the corresponding business departments and projects. Specifically, database software query statements can be used to retrieve all target details for the target business project in the target data table. A data report is then generated based on all retrieved target details, and the generated data report contains at least one target detail from the target business project.

[0082] The database-based data processing method provided in this application embodiment acquires a dataset generated by a preset business in a preset usage scenario. The preset business includes multiple business steps, each including at least one of business projects and business departments. The dataset includes multiple detailed data entries from each business department on a business project within a preset first time period. Since the detailed data is associated with business departments and business projects, it can be used to construct a data table that contains this association information. For each business department and each business project, the target details for that business department within the business project are determined within the preset first time period. These target details represent multiple detailed data entries from each business department within the business project. Preliminary aggregation of these multiple detailed data entries can be performed to ensure that the aggregated target details meet the data requirements for generating subsequent data reports. Aggregated target details can also reduce query time, thereby improving data processing efficiency. Based on the target details of each business department in each business project, a target data table is constructed. The data stored in the target data table is used to generate data reports for the preset business. Because detailed data is related to business departments and projects, and target details represent multiple detailed data entries, target details are also related to business departments and projects. The target data table built based on target details can aggregate target details, business departments, and business projects. This allows for accurate data retrieval by simply scanning and filtering a single table when generating subsequent data reports, thereby reducing the number of query operations and improving data processing efficiency.

[0083] In some specific embodiments, the dataset centrally includes environmental information and identification information corresponding to business processes, with the environmental information providing a detailed explanation of the business process. Before determining the target details of the business project within a preset first time period, the above method further includes:

[0084] First, based on multiple detailed data entries from business departments on business projects, the identification information of business departments, and the identification information of business projects, a first data table is generated. In this first data table, rows represent preset times; the preset times are within a preset first time period; the preset times represent the time when the detailed data was generated; the first data table includes at least a first column, a second column, and a third column. The first column represents business departments, the second column represents business projects, and the third column represents detailed data. The field values ​​corresponding to rows and the first column represent the identification information of business departments, the field values ​​corresponding to rows and the second column represent the identification information of business projects, and the field values ​​corresponding to rows and the third column represent detailed data.

[0085] Second, based on the identification information of the business process and the environmental information corresponding to the business process, determine the second data table; wherein the second data table includes at least the fourth column and the fifth column; the fourth column describes the identification information of the business process, and the fifth column describes the environmental information of the business process.

[0086] Figure 2 Flowchart of the database-based data processing method provided in this application Figure 2 ,like Figure 2 As shown, the method includes:

[0087] S201. Obtain the dataset generated by the preset business under the preset usage scenario; wherein, the preset business includes multiple business links, and the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of the business departments on business projects within the preset first time period.

[0088] The execution process of S201 is the same as that of S101, and will not be described again here.

[0089] S202. For each business department and each business project, a first data table is generated based on the multiple detailed data entries of the business department on the business project, the identification information of the business department, and the identification information of the business project. The rows in the first data table represent preset times; the preset times are within a preset first time period; the preset times represent the time when the detailed data was generated; the first data table includes at least a first column, a second column, and a third column. The first column represents the business department, the second column represents the business project, and the third column represents the detailed data. The field values ​​corresponding to the rows and the first column represent the identification information of the business department, the field values ​​corresponding to the rows and the second column represent the identification information of the business project, and the field values ​​corresponding to the rows and the third column represent the detailed data. The target details represent multiple detailed data entries of the business department on the business project.

[0090] For example, the dataset centrally includes environmental information and identification information corresponding to business processes. Environmental information provides a detailed explanation of the business process. Identification information serves as a unique identifier for each business process. For instance, if a business process includes a business department and a business project, the environmental information includes the department code and department name information corresponding to the business department. The department code represents a string defined for information management of the business department. It also includes the business project code and business project name corresponding to the business project. The business project code represents a string defined for information management of the business project. Identification information includes the identification information for the business department and the identification information for the business project. The identification information for the business department is a unique identifier for the business department. The identification information for the business project is a unique identifier for the business project.

[0091] For each business department and each business project, a first data table is generated based on multiple detailed data entries for the business department on the business project, the business department's identification information, and the business project's identification information. The rows in the first data table represent preset times, and the first data table includes multiple rows. The preset times are located within a preset first time period, and each preset time represents the time when the detailed data was generated. There are multiple preset times; that is, within the first time period, there are multiple preset times, and each preset time generates one piece of detailed data.

[0092] The first data table includes at least three columns: the first column represents the business department, the second column represents the business project, and the third column represents the detailed data. The field values ​​corresponding to the rows and the first column represent the identification information of the business department, such as the business department ID (identity document). The field values ​​corresponding to the rows and the second column represent the identification information of the business project, such as the business project ID. The field values ​​corresponding to the rows and the third column represent the detailed data. Target details represent multiple detailed data entries for a business department within a business project.

[0093] Figure 3 A schematic diagram of the first data table provided in this application. (See diagram below.) Figure 3 As shown, the first column of the first data table stores the business department ID, the second column stores the business project ID, and the third column stores detailed data. The first data table also includes two columns: one storing the preset time and the other storing the usage scenario. The first data table has multiple rows. For each row, the detailed data is the detailed data for the corresponding business department under the corresponding business project at the preset time in the usage scenario. For example, detailed data of "500" means that the labor cost for business department 001 in business project 001 was 500 yuan at 9:00 AM on January 1, 2025.

[0094] S203. Based on the identification information of the business process and the environmental information corresponding to the business process, determine the second data table; wherein the second data table includes at least the fourth column and the fifth column; the fourth column describes the identification information of the business process, and the fifth column describes the environmental information of the business process.

[0095] For example, a second data table is determined based on the identification information of the business process and the corresponding environmental information. The second data table includes at least a fourth column and a fifth column; the fourth column represents the identification information of the business process, and the fifth column represents the environmental information of the business process. There can be multiple second data tables, and each second data table can have multiple rows, including multiple fifth columns.

[0096] For example, if the environmental information for a business process includes the department code and department name information corresponding to the business department, and the project code and project name information corresponding to the business project, then there are two second data tables. The first second data table is used to store the environmental information corresponding to the business department, and the second second data table is used to store the environmental information corresponding to the business project.

[0097] For example, the first second data table includes multiple rows, a fourth column, and two fifth columns. The fourth column stores the business unit's identification information; the first fifth column stores the business unit's department code; and the second fifth column stores the business unit's department name. This second data table may also include several other columns to store other environmental information about the business unit, such as its creation time.

[0098] S204. Based on the target details of each business department for each business project, construct a target data table; the data stored in the target data table is used to generate data reports for preset businesses.

[0099] The execution process of S204 is the same as that of S103, and will not be described again here.

[0100] In these embodiments, a first data table is generated based on multiple detailed data entries from business departments on business projects, the identification information of business departments, and the identification information of business projects. The first data table stores the original data in the dataset, including detailed data, department identification information, and project identification information. Detailed data and its corresponding department and project identification information can be found through the first data table, providing raw data for subsequent aggregation of detailed data. A second data table is determined based on the identification information of business processes and the corresponding environmental information. The second data table stores the original identification information of business departments and their corresponding environmental information, as well as the project identification information of business projects and their corresponding environmental information. The second data table allows for quick retrieval of business departments and their corresponding environmental information, or business projects and their corresponding environmental information. Both the first and second data tables store the original information, and the stored data does not change with historical data, thus ensuring data reliability.

[0101] In some specific implementations, in S102 above, for each business department and each business project, the target details of the business department in the business project within a preset first time period include:

[0102] S1021. Obtain detailed data of each business department for each business project from the first data table.

[0103] For example, after obtaining multiple detailed data entries, the detailed data of each business department on each business project is obtained from the first data table.

[0104] For example, for each business department and each business project, data matching can be performed in the first data table based on the identification information of the business department and the identification information of the business project. At least one row in the first data table that matches the identification information of the business department and the identification information of the business project can be found, and detailed data in the at least one matching row can be obtained. The detailed data in the at least one matching row is the detailed data of the business department on the business project obtained from the first data table.

[0105] S1022. For each business department and each business project, determine the target details of the business department in the business project based on multiple detailed data.

[0106] For example, after obtaining the detailed data, for each business department and each business project, the target details of the business department in the business project are determined based on multiple detailed data.

[0107] For example, for any business department and any business project, if the detailed data is a single expenditure, at least one detailed data can be obtained and summed according to S1031, and the sum obtained can be determined as the target detail.

[0108] If the detailed data is the sum of multiple expenditures, for any business department and any business project, the maximum value of at least one detailed data can be obtained according to S1021, and the maximum value is determined as the target detail.

[0109] In these implementations, for each business department and each business project, detailed data for that business department and project is retrieved from a first data table, and target details are determined based on the retrieved detailed data. The target details can be initially aggregated to obtain the target details, which meet the data requirements for subsequently generating data reports for preset business operations. That is, the data used to generate the preset business data reports is the target details, not the retrieved detailed data. Therefore, the determined target details provide a foundation for subsequently generating high-quality data tables.

[0110] In some specific implementations, S103 above includes the following sub-steps:

[0111] S1031. Obtain the identification information of each business process and the environmental information of each business process from the second data table.

[0112] For example, after constructing the first data table and the second data table, the identification information of each business process and the environmental information of each business process are obtained from the second data table.

[0113] For example, the identification information of business projects and the corresponding environmental information, such as project code and project name, can be obtained from the first data table. Based on the obtained business project identification information and corresponding environmental information, a fifth data table can be generated. The rows of the fifth data table represent business departments, and the columns represent environmental information.

[0114] The fifth data table stores the identification information of business projects and the corresponding environmental information. For example, one column in the fifth data table stores the identification information of business projects, with the identification information of each business project stored in different rows of the same column in the fifth data table; another column stores the project code information of business projects, with the code information of each business project stored in different rows of the same column in the fifth data table; and a third column stores the project name of business projects, with the project name of each business project stored in different rows of the same column in the fifth data table.

[0115] The identification information of the business departments and their corresponding environmental information can be obtained from the first data table. Based on the obtained identification information and environmental information of the business departments, such as the department code and department name, a sixth data table is generated. The rows of the sixth data table represent the business departments, and the columns represent the environmental information.

[0116] The sixth data table stores the identification information of business departments and the corresponding environmental information. For example, one column in the sixth data table stores the identification information of business departments, with the identification information of each business department stored in different rows of the same column in the sixth data table; another column stores the department code information of business departments, with the code information of each business department stored in different rows of the same column in the sixth data table; and a third column stores the department name of business departments, with the department name of each business project stored in different rows of the same column in the sixth data table.

[0117] S1032. Based on the identification information of each business link, the environmental information of each business link, and the target details of each business department in each business project, construct a target data table; wherein, the target data table includes a sixth column, a seventh column, and an eighth column; the sixth column represents the identification information of the business link; the seventh column represents the environmental information of the business link; the eighth column represents the target details; the rows of the target data table represent the preset usage scenarios.

[0118] For example, after obtaining the identification information and environmental information of each business link, a target data table is constructed based on the identification information, environmental information, and target details of each business department in each business project. The target data table includes a sixth column, a seventh column, and an eighth column. The sixth column represents the identification information of the business link; the seventh column represents the environmental information of the business link; and the eighth column represents the target details. The rows of the target data table represent preset usage scenarios.

[0119] For example, a target data table can be constructed based on the identification information and environmental information of each business project obtained from the fifth data table, the identification information and environmental information of each business department obtained from the sixth data table, and the target details determined in S1022.

[0120] Figure 4 A schematic diagram of the target data table provided in this application. (Example) Figure 4 As shown, the target data table includes multiple columns: one column stores the business department ID (each business department ID is stored in different rows of the same column in the target data table); one column stores the business department code (each business department code is stored in different rows of the same column in the target data table); one column stores the business department name (each business department name is stored in different rows of the same column in the target data table); one column stores the business project ID (each business project ID is stored in different rows of the same column in the target data table); one column stores the business project code (each business project code is stored in different rows of the same column in the target data table); one column stores the business project name (each business project name is stored in different rows of the same column in the target data table); one column stores the target details (each target details are stored in different rows of the same column in the target data table); one column stores the time period (i.e., the first time period) (each time period is stored in different rows of the same column in the target data table); and one column stores the application scenario (each application scenario is stored in different rows of the same column in the target data table). The target data table has multiple rows. For each row, the target details are the target details of the corresponding business department under the corresponding business project within the first time period of the use scenario. For example, target detail 800 is the procurement cost of the software R&D department (software R&D department ID is 001, code is A) on January 1, 2025, for the software R&D project (software R&D project ID is 001, code is C).

[0121] In these implementations, by obtaining the identification information and environmental information of each business process from the second data table, the identification information and environmental information of each business process can be modeled. This means that the data information needed to generate data reports is extracted from the raw data in the second data table, while unnecessary data is removed, thereby reducing data redundancy. A target data table is constructed based on the identification information of each business process, the environmental information of each business process, and the target details of each business department in each business project. The constructed target data table contains a variety of information, and the data in the target data table can meet most of the data requirements for generating subsequent data reports. Therefore, when generating subsequent data reports, data can be obtained from the target data table, thereby reducing the number of queries to the original data, improving data query efficiency, and significantly reducing the maintenance cost of the data table.

[0122] In some specific embodiments, the generation of the first data table in S202 above, based on multiple detailed data entries of the business department on the business project, the identification information of the business department, and the identification information of the business project, includes the following sub-steps:

[0123] S2021. According to the preset first data processing rules, the multiple detailed data of the business department on the business project, the identification information of the business department, and the identification information of the business project are converted and processed respectively.

[0124] For example, after acquiring the dataset, multiple detailed data entries of the business department on business projects, the identification information of the business department, and the identification information of the business project can be transformed according to a preset first data processing rule. The first data processing rule is used to process the detailed data, the identification information of the business department, and the identification information of the business project to unify the data format.

[0125] For example, after obtaining the dataset, a sixth and seventh data table can be constructed based on the data in the dataset. The rows in the sixth data table represent preset time points; the sixth data table includes at least columns thirteen, fourteen, and fifteen. Column thirteen represents business departments, column fourteen represents business projects, and column fifteen represents detailed data. The field values ​​corresponding to the rows and columns thirteen represent the unprocessed identification information of business departments, the corresponding field values ​​corresponding to the rows and columns fourteen represent the unprocessed identification information of business projects, and the corresponding field values ​​corresponding to the rows and columns fifteen represent the unprocessed detailed data.

[0126] The seventh data table includes at least columns sixteen and seventeen; column sixteen represents the identification information of the business process that has not been converted, and column seventeen represents the environmental information of the business process that has not been converted.

[0127] The first data processing rule may include: adjusting the unconverted detailed data in the sixth data table based on numerical data with two decimal places; adjusting the unconverted business department identification information in the sixth and seventh data tables based on a preset first-length string for business department identification information; and adjusting the unconverted business project identification information in the sixth and seventh data tables based on a preset second-length string for business project identification information. The first data processing rule may also include correcting erroneous data, standardizing data types, adding data modification timestamps, and updating user information for added data.

[0128] S2022. Based on the processed data, the first data table is obtained.

[0129] For example, after the data is transformed, a first data table is obtained based on the processed data.

[0130] For example, after transforming the data in the first data table, we obtain the second data table. Similarly, after transforming the data in the second data table, we obtain the third data table.

[0131] In these embodiments, according to a preset first data processing rule, multiple detailed data entries of the business department on business projects, the identification information of the business department, and the identification information of the business projects are transformed and processed respectively. Based on the processed data, a first data table is obtained. Data processing can be performed on the data in the dataset to standardize the data format, reduce erroneous data, and thus improve data quality.

[0132] In some specific embodiments, after constructing the target data table based on the target details of each business department for each business project, the above method further includes:

[0133] First, based on the target data table and a preset second time period, obtain multiple target details for each business department.

[0134] Second, based on the identification information of the business departments and the multiple target details of the business departments, a third data table is constructed; wherein, the preset second time period includes at least one first time period; the rows in the third data table represent the preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column representing the identification information of the business departments; and the tenth column representing the sum of the multiple target details corresponding to the business departments.

[0135] Figure 5 Flowchart of the database-based data processing method provided in this application Figure 3 ,like Figure 5 As shown, the method includes:

[0136] S501. Obtain the dataset generated by the preset business under the preset usage scenario; wherein, the preset business includes multiple business links, and the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of the business departments on business projects within the preset first time period.

[0137] The execution process of S501 is the same as that of S101, and will not be described again here.

[0138] S502. For each business department and each business project, determine the target details of the business department in the business project within a preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project.

[0139] The execution process of S502 is the same as that of S102, and will not be described again here.

[0140] S503. Based on the target details of each business department in each business project, construct a target data table; the data stored in the target data table is used to generate data reports for preset businesses.

[0141] The execution process of S503 is the same as that of S103, and will not be described again here.

[0142] S504. Based on the target data table and a preset second time period, obtain multiple target details for each business department; the preset second time period includes at least one first time period.

[0143] For example, after determining the target data table, multiple target details of each business department are obtained based on the target data table and a preset second time period; the preset second time period includes at least one first time period.

[0144] For example, if the first time period is a single day, and the data report needs to compile detailed target information for each business department within a month, then the second time period would be a week. In this case, the detailed target information for each week from Monday to Sunday of that month would be retrieved from the target data table.

[0145] S505. Based on the identification information of the business department and the multiple target details of the business department, construct a third data table; wherein, the rows in the third data table represent a preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column representing the identification information of the business department; the tenth column representing the sum of the multiple target details corresponding to the business department.

[0146] For example, after obtaining multiple target details, a third data table is constructed based on the identification information of the business department and the multiple target details of the business department; wherein, the rows in the third data table represent a preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column representing the identification information of the business department; the tenth column representing the sum of the multiple target details corresponding to the business department.

[0147] For example, the rows in the third data table represent one week, with the first row representing week one, the second row representing week two, the third row representing week three, and the fourth row representing week four. The ninth column stores the department IDs of the business units. The tenth column stores the sum of multiple target details for each week.

[0148] It should be noted that it is also possible to obtain multiple target details for each business project, and generate a data table for the second preset period of the business project based on these multiple target details. Alternatively, it is possible to obtain multiple target details for both business departments and business projects, and generate a data table for the second preset period of the business department and business project based on these multiple target details.

[0149] In these embodiments, based on the target data table and a preset second time period, multiple target details for each business department are obtained. A third data table is then constructed based on the business department's identification information and these multiple target details. The third data table further aggregates the target details from the target data table to make the data more suitable for subsequent data report generation. When generating data reports, if the third data table meets the data requirements, data can be retrieved from the third data table first, eliminating the need to retrieve data from the target data table and then integrate it. This improves the efficiency of data querying.

[0150] In some specific embodiments, the above method further includes:

[0151] First, obtain the sum of multiple target details for this business department within the preset second time period from the third data table.

[0152] Second, retrieve the details of multiple targets for the business unit within the preset second time period from the target data table.

[0153] Third, based on the sum of multiple target details and the multiple target details, construct a fourth data table corresponding to the business department; wherein, the rows of the fourth data table represent the preset first time period; the fourth data table includes at least an eleventh column and a twelfth column; the eleventh column represents the target details of the business department; the twelfth column represents the ratio; the ratio represents the ratio of the target details to the sum of multiple target details.

[0154] Figure 6Flowchart of the database-based data processing method provided in this application Figure 4 ,like Figure 6 As shown, the method includes:

[0155] S601. Obtain the dataset generated by the preset business under the preset usage scenario; wherein, the preset business includes multiple business links, and the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of the business department on the business project within the preset first time period.

[0156] The execution process of S601 is the same as that of S501, and will not be described again here.

[0157] S602. For each business department and each business project, determine the target details of the business department in the business project within a preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project.

[0158] The execution process of S602 is the same as that of S502, and will not be described again here.

[0159] S603. Based on the target details of each business department in each business project, construct a target data table; the data stored in the target data table is used to generate data reports for preset businesses.

[0160] The execution process of S603 is the same as that of S503, and will not be described again here.

[0161] S604. Based on the target data table and a preset second time period, obtain multiple target details for each business department; the preset second time period includes at least one first time period.

[0162] The execution process of S604 is the same as that of S504, and will not be described again here.

[0163] S606. Construct a third data table based on the identification information of the business department and the multiple target details of the business department; wherein, the rows in the third data table represent the preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column representing the identification information of the business department; the tenth column representing the sum of the multiple target details corresponding to the business department.

[0164] The execution process of S605 is the same as that of S505, and will not be described again here.

[0165] S606. From the third data table, obtain the sum of multiple target details for the business department within the preset second time period.

[0166] For example, after generating the third data table, the sum of multiple target details of the business department within a preset second time period is obtained from the third data table.

[0167] If, based on the needs of subsequent data reports, more departmental information needs to be displayed in the data reports, the sum of multiple target details for the second time period (e.g., one week) of that business department (e.g., the software R&D department) can be obtained from the third data table.

[0168] S607. Obtain the details of multiple targets for this business unit within a preset second time period from the target data table.

[0169] For example, after generating the third data table, multiple target details of the business department within a preset second time period are obtained from the target data table.

[0170] If the data report needs to display more detailed target information based on the needs of the end users, then multiple target details for the second time period (e.g., one week) of that business department (e.g., the software development department) can be obtained from the target data table.

[0171] S608. Based on the sum of multiple target details and the multiple target details, construct a fourth data table corresponding to the business department; wherein, the rows of the fourth data table represent a preset first time period; the fourth data table includes at least an eleventh column and a twelfth column; the eleventh column represents the target details of the business department; the twelfth column represents the ratio; the ratio represents the ratio of the target details to the sum of multiple target details.

[0172] For example, after obtaining the sum of multiple target details and the multiple target details, a fourth data table corresponding to the business department is constructed based on the sum of multiple target details and the multiple target details; wherein, the rows of the fourth data table represent a preset first time period; the fourth data table includes at least an eleventh column and a twelfth column; the eleventh column represents the target details of the business department; the twelfth column represents the ratio; the ratio represents the ratio of the target details to the sum of multiple target details.

[0173] The eleventh column of the fourth data table stores the details of multiple targets; the twelfth column stores the ratio of the target detail to the sum of the multiple target details. The fourth data table has multiple rows. For each row, the corresponding fields include a target detail and the ratio of that target to the sum of the multiple target details.

[0174] In these implementations, a fourth data table is constructed by obtaining the sum of multiple target details of the business department within a preset second time period from the third data table, obtaining multiple target details of the business department within a preset second time period from the target data table, and constructing the sum of multiple target details and the multiple target details. The constructed fourth data table is a data table customized according to a specific application scenario. The fourth data table is directly oriented to the end users of the data table, thereby reducing the number of times the end users access other data tables and improving the data response efficiency of the end users.

[0175] In some specific embodiments, the above method further includes:

[0176] First, obtain the real-time generated data of the preset business in each business process.

[0177] For example, in response to receiving a user's instruction to retrieve a data report, the instruction instructs the retrieval of data from a data table. Based on the retrieved data and combined with implementation data, a data report is generated. This retrieves real-time data generated at each stage of a pre-defined business process.

[0178] For example, if the preset business is software development work in the software R&D department, and the software development work is not yet completed, but generates real-time data, such as the labor cost for the day, then the labor cost for that day will be retrieved.

[0179] Second, based on the real-time generated data and the fourth data table, generate data reports for the preset business.

[0180] For example, after obtaining the real-time generated data, a data report for a preset business can be generated based on the real-time generated data and the fourth data table.

[0181] For example, the target details and ratio data of each business project under the responsibility of the software R&D department for the previous three weeks can be obtained from the fourth data table. Combined with the target details and ratio data generated in real time for this week, a data report of the software R&D project can be generated. This data report includes the target details and ratio data of each business project of the software R&D department for the previous three weeks, as well as the target details and ratio data for this week.

[0182] In these embodiments, by acquiring real-time generated data of the preset service in each business process, and combining the real-time generated data with the fourth data table, a data report of the preset service can be generated, thereby enriching the content of the data report.

[0183] It should be noted that the generated data tables are stored in the database. Figure 7 A schematic diagram of the database structure provided in this application. (For example...) Figure 7As shown, the database's data comes from a data source, which stores the most original data generated from multiple preset business processes, including historical data and real-time data.

[0184] The fifth and sixth data tables are stored in the data lake, and they retrieve the raw data from the data source. The first and second data tables are also stored in the data lake, and they retrieve data from the fifth and sixth data tables respectively, performing data transformation. The first and fifth data tables are linked by corresponding identification information (such as business project identification information and business department identification information), and the second and sixth data tables are linked by corresponding identification information (such as business project identification information or business department identification information).

[0185] The seventh and eighth data tables are stored in the data warehouse. The seventh data table processes and models the data in the second data table according to business needs. The second and seventh data tables are linked through corresponding identification information. The eighth data table processes and models the data in the second data table. The second and eighth data tables are linked through corresponding identification information.

[0186] The target data table is stored in the data warehouse. The target data table obtains data from the seventh and eighth data tables, as well as the first data table. The obtained data is aggregated. The target data table is associated with the seventh, eighth, and first data tables through corresponding identification information.

[0187] The third data table is stored in the data warehouse. The third data table obtains data from the target data table, performs further aggregation on the obtained data, and is associated with the target data table through corresponding identification information.

[0188] The fourth data table is stored in the data warehouse. It retrieves data from the third data table and combines it with real-time data to generate the poems provided to end users. The real-time data is generated by the data source in real time. The fourth and third data tables are linked through corresponding identification information. Real-time data may include identification information, such as identification information for business departments or business projects, which is used to link the data in the fourth data table.

[0189] The fourth data table is used to provide data for the end users.

[0190] The final user sends a query command, which instructs the database's software query code to retrieve data from the database. The retrieved data may be stored in at least one table in the database. The execution process of the database query command is as follows:

[0191] First, in response to a data table query command, determine the data table to be queried; wherein the data table to be queried is at least one of the first data table, the second data table, the third data table, the fourth data table, and the target data table.

[0192] For example, if a query instruction specifies that data should be retrieved from a target data table, then the data table to be queried is determined to be the target data table. The data table to be queried can also be at least one of the first data table, the second data table, the third data table, the fourth data table, and the target data table.

[0193] Second, starting from the fourth data table, the data table to be queried is obtained based on the preset data table query order.

[0194] For example, after determining the data table to be queried, starting from the fourth data table, the data tables to be queried are obtained based on a preset data table query order. The preset data table query order is determined according to the relationship properties of the tables.

[0195] For example, if the fourth data table is associated with the third data table, then access to the third data table can begin from the fourth data table. Since the third data table is associated with the target data table, access to the target data table can be done from the third data table. This allows the final data needed by the user to be returned from the target data table. In this case, the default data table query order is: first query the fourth data table, then the third data table, and finally the target data table.

[0196] In these embodiments, data tables are stored in a database, while the first, second, fifth, and sixth data tables are stored in a data lake, and the third, target, seventh, and eighth data tables are stored in a data warehouse. This combines the advantages of both data lakes and data warehouses, providing unified data storage and analysis capabilities. Raw, unprocessed data is stored in the data lake, satisfying the data storage needs of numerous data sources, even though this data is not directly accessible to end users. Processed data is stored in the data warehouse, where data aggregation at varying degrees ensures it meets all data requirements. Furthermore, a target data table is generated, aggregating most of the data, thus satisfying most data needs. The third data table further aggregates the data from the target data table, satisfying even more data requirements. The fourth data table further aggregates the data from the third data table, satisfying some specific data requirements. The data in the data warehouse directly provides data to end users based on different data needs, thereby reducing redundant data and forming a database with efficient storage and computation.

[0197] Figure 8 A schematic diagram of the structure of the database-based data processing device provided in this application is shown below. Figure 8 As shown, the database-based data processing device 80 provided in this embodiment includes:

[0198] The acquisition module 801 is used to acquire the dataset generated by the preset business under the preset usage scenario; wherein, the preset business includes multiple business links, and the business links include at least one of business projects and business departments, and the dataset includes multiple detailed data of the business departments on business projects within the preset first time period;

[0199] The determination module 802 is used to determine the target details of each business department and each business project within a preset first time period; wherein, the target details represent multiple detailed data of the business department in the business project.

[0200] Module 803 is used to construct target data tables based on the target details of each business department in each business project; the data stored in the target data tables is used to generate data reports for preset businesses.

[0201] In one possible implementation, the dataset centrally includes environmental information and identification information corresponding to business processes, with the environmental information representing a detailed explanation of the business process; before determining the target details of the business project within a preset first time period, module 902 is further used for:

[0202] Based on multiple detailed data entries from business departments on business projects, the identification information of business departments, and the identification information of business projects, a first data table is generated. In this first data table, rows represent preset times; the preset times are located within a preset first time period; and the preset times represent the time when the detailed data was generated. The first data table includes at least a first column, a second column, and a third column. The first column represents business departments, the second column represents business projects, and the third column represents detailed data. The field values ​​corresponding to rows and the first column represent the identification information of business departments, the field values ​​corresponding to rows and the second column represent the identification information of business projects, and the field values ​​corresponding to rows and the third column represent detailed data.

[0203] A second data table is determined based on the identification information of the business process and the corresponding environmental information; the second data table includes at least a fourth column and a fifth column; the fourth column describes the identification information of the business process, and the fifth column describes the environmental information of the business process.

[0204] In one possible implementation, the determining module 802 is also used for:

[0205] Obtain detailed data for each business department and each business project from the first data table;

[0206] For each business unit and each business project, the specific objectives of the business unit for the business project are determined based on multiple detailed data points.

[0207] In one possible implementation, the building module 803 is also used for:

[0208] Obtain the identification information and environmental information of each business process from the second data table;

[0209] Based on the identification information of each business link, the environmental information of each business link, and the target details of each business department in each business project, a target data table is constructed. The target data table includes columns six, seven, and eight. Column six represents the identification information of the business link; column seven represents the environmental information of the business link; column eight represents the target details; and the rows of the target data table represent the preset usage scenarios.

[0210] In one possible implementation, the determining module 802 is also used for:

[0211] According to the preset first data processing rules, the multiple detailed data of the business department in the business project, the identification information of the business department, and the identification information of the business project are transformed and processed respectively.

[0212] Based on the processed data, the first data table is obtained.

[0213] In one possible implementation, the database-based data processing device 80 further includes a second building module for:

[0214] Based on the target data table and a preset second time period, multiple target details for each business department are obtained; wherein the preset second time period includes at least one first time period.

[0215] A third data table is constructed based on the identification information of the business departments and the multiple target details of the business departments; the rows in the third data table represent the preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column represents the identification information of the business departments; the tenth column represents the sum of the multiple target details corresponding to the business departments.

[0216] In one possible implementation, the database-based data processing device 80 further includes a third building module for:

[0217] From the third data table, obtain the sum of multiple target details for this business unit within the preset second time period;

[0218] Retrieve detailed information on multiple targets for this business unit within a pre-defined second time period from the target data table;

[0219] Based on the sum of multiple target details and multiple target details, a fourth data table corresponding to the business department is constructed; wherein, the rows of the fourth data table represent a preset first time period; the fourth data table includes at least an eleventh column and a twelfth column; the eleventh column represents the target details of the business department; the twelfth column represents the ratio; the ratio represents the ratio of the target details to the sum of multiple target details.

[0220] In one possible implementation, the database-based data processing device 90 further includes a reporting module for:

[0221] Obtain real-time generated data for preset business processes at each stage;

[0222] Based on the real-time generated data and the fourth data table, generate data reports for preset business operations.

[0223] In one possible implementation, the database-based data processing device 80 further includes a query module for:

[0224] In response to a data table query command, determine the data table to be queried; wherein the data table to be queried is at least one of the first data table, the second data table, the third data table, the fourth data table, and the target data table;

[0225] Starting from the fourth data table, the data table to be queried is obtained based on the preset data table query order.

[0226] The database-based data processing device provided in this embodiment can execute the methods provided in the above-described method embodiments. Its implementation principle and technical effects are similar, and will not be described in detail here.

[0227] Figure 9 This is a schematic diagram of the structure of the database-based data processing device provided in this application. Figure 9 As shown, the database-based data processing device 90 provided in this embodiment includes at least one processor 901 and a memory 902. Optionally, the database-based data processing device 90 further includes a communication component 903. The processor 901, memory 902, and communication component 903 are connected via a bus.

[0228] In a specific implementation, at least one processor 901 executes computer execution instructions stored in memory 902, causing at least one processor 901 to perform the above-described method.

[0229] The specific implementation process of processor 901 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0230] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0231] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0232] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0233] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0234] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0235] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0236] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0237] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0238] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0239] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0240] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0241] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0242] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A database-based data processing method, characterized in that, include: Acquire a dataset generated by a preset business under a preset usage scenario; wherein the preset business includes multiple business steps, and the business steps include at least one of business projects and business departments; the dataset includes multiple detailed data of the business departments on business projects within a preset first time period; the dataset includes environmental information and identification information corresponding to the business steps, and the environmental information represents a detailed explanation of the business steps; A first data table is generated based on multiple detailed data entries of the business department on business projects, the identification information of the business department, and the identification information of the business project. In this first data table, rows represent preset times; the preset times are located within a preset first time period; the preset times represent the time when the detailed data was generated; the first data table includes at least a first column, a second column, and a third column, where the first column represents the business department, the second column represents the business project, and the third column represents the detailed data; the field values ​​corresponding to the rows and the first column represent the identification information of the business department, the field values ​​corresponding to the rows and the second column represent the identification information of the business project, and the field values ​​corresponding to the rows and the third column represent the detailed data. Obtain detailed data of each business department for each business project from the first data table; For each business department and each business project, the target details of the business department in the business project are determined based on multiple detailed data; wherein, the target details represent multiple detailed data of the business department in the business project. Based on the detailed objectives of each business department for each business project, a target data table is constructed; wherein, the data stored in the target data table is used to generate data reports for preset businesses.

2. The method according to claim 1, characterized in that, The method further includes: A second data table is determined based on the identification information of the business process and the environmental information corresponding to the business process; wherein the second data table includes at least a fourth column and a fifth column; the fourth column identifies the identification information of the business process, and the fifth column identifies the environmental information of the business process.

3. The method according to claim 2, characterized in that, The step involves constructing a target data table based on the detailed targets of each business department for each business project, including: Obtain the identification information and environmental information of each business process from the second data table; Based on the identification information of each business link, the environmental information of each business link, and the target details of each business department in each business project, a target data table is constructed; wherein, the target data table includes a sixth column, a seventh column, and an eighth column; the sixth column identifies the identification information of the business link; the seventh column identifies the environmental information of the business link; the eighth column identifies the target details; and the rows of the target data table represent preset usage scenarios.

4. The method according to claim 1, characterized in that, The step of generating a first data table based on multiple detailed data entries of the business department on business projects, the identification information of the business department, and the identification information of the business projects includes: According to the preset first data processing rule, the multiple detailed data of the business department on the business project, the identification information of the business department, and the identification information of the business project are respectively converted and processed. The first data table is obtained based on the processed data.

5. The method according to any one of claims 1-4, characterized in that, After constructing the target data table based on the target details of each business department for each business project, the method further includes: Based on the target data table, and using a preset second time period, multiple target details for each business department are obtained; the preset second time period includes at least one first time period. A third data table is constructed based on the identification information of the business department and the multiple target details of the business department; wherein, the rows in the third data table represent a preset second time period; the third data table includes at least a ninth column and a tenth column, the ninth column representing the identification information of the business department; and the tenth column representing the sum of the multiple target details corresponding to the business department.

6. The method according to claim 5, characterized in that, The method further includes: From the third data table, obtain the sum of multiple target details for the business department within a preset second time period; Retrieve the detailed target information of the business department within a preset second time period from the target data table; Based on the sum of the multiple target details and the multiple target details, a fourth data table corresponding to the business department is constructed; wherein, the rows of the fourth data table represent a preset first time period; the fourth data table includes at least an eleventh column and a twelfth column; the eleventh column represents the target details of the business department; the twelfth column represents the ratio; the ratio represents the ratio of the target details to the sum of the multiple target details.

7. The method according to claim 6, characterized in that, The method further includes: Obtain the real-time generated data of the preset service in each business process; Based on the real-time generated data and the fourth data table, a data report for the preset business is generated.

8. The method according to claim 7, characterized in that, The method further includes: In response to a data table query command, a data table to be queried is determined; wherein, the data table to be queried is at least one of a first data table, a second data table, a third data table, a fourth data table, and a target data table; Starting from the fourth data table, the data table to be queried is obtained based on the preset data table query order.

9. A database-based data processing device, characterized in that, include: An acquisition module is used to acquire a dataset generated by a preset business under a preset usage scenario; wherein the preset business includes multiple business steps, and the business steps include at least one of business projects and business departments; the dataset includes multiple detailed data entries of the business department on the business project within a preset first time period; the dataset includes environmental information and identification information corresponding to the business steps, and the environmental information represents a detailed explanation of the business steps; a determination module is used to generate a first data table based on the multiple detailed data entries of the business department on the business project, the identification information of the business department, and the identification information of the business project; wherein the rows in the first data table represent preset times; the preset times are located within the preset first time period. The preset time represents the time when the detailed data is generated; the first data table includes at least a first column, a second column, and a third column, the first column representing business departments, the second column representing business projects, and the third column representing detailed data; the field values ​​corresponding to the row and the first column represent the identification information of the business department, the field values ​​corresponding to the row and the second column represent the identification information of the business project, and the field values ​​corresponding to the row and the third column represent the detailed data; detailed data of each business department on each business project are obtained from the first data table; for each business department and each business project, the target details of the business department on the business project are determined based on multiple detailed data; wherein, the target details represent multiple detailed data of the business department on the business project; The construction module is used to build a target data table based on the target details of each business department in each business project; wherein, the data stored in the target data table is used to generate data reports for preset businesses.

10. A database-based data processing device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-8.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-8.

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