CN117635371A - An enterprise data quality management method, device, electronic equipment and storage medium - Google Patents

Abstract

This application relates to the technical field of data management, and in particular to an enterprise data quality management method, device, electronic equipment and storage medium. The method includes: obtaining business data, and determining original data based on the business data; inputting the original data into the source layer to determine incremental data information; and determining problem data based on the incremental data information, and the problem data is Data that does not meet quality standards; based on the problem data, determine the rectification report and display the feedback. This application can improve the accuracy of data quality management.

Description

An enterprise data quality management method, device, electronic equipment and storage medium

Technical field

This application relates to the technical field of data management, and in particular to an enterprise data quality management method, device, electronic equipment and storage medium.

Background technique

Construction group enterprises are diversified enterprises with architectural design, construction, and management as their main businesses. Such enterprises usually have complex business structures and diversified data sources; due to the influence of business characteristics, construction groups Large-scale enterprises also have stricter data quality requirements.

Traditional enterprise data management methods mainly achieve comprehensive management of data by manually formulating data standards, standardizing data processing procedures, and establishing data quality management platforms.

However, traditional enterprise data management methods and data quality management methods often only focus on the normalization and standardization of data, and are easily affected by human factors, resulting in low accuracy of data quality in construction industry group enterprises.

Contents of the invention

In order to improve the accuracy of data quality management, this application provides an enterprise data quality management method, device, electronic equipment and storage medium.

In the first aspect, this application provides an enterprise data quality management method, adopting the following technical solutions:

An enterprise data quality management approach that includes:

Obtain business data, and determine original data based on the business data, where the business data is data corresponding to enterprise business, and the original data is data that needs to be tested for data quality;

Input the original data into the source layer to determine the incremental data information. The incremental data information is;

Based on the incremental data information, problem data is determined, and the problem data is data that does not meet quality standards;

Based on the problem data, determine the rectification report and display the feedback.

By using the above technical solution, business data is obtained to determine the specific enterprise data of the construction group enterprise. Then, based on the business data, the original data is determined, thereby eliminating duplicate or blank business data in the business data. Adapt to subsequent data processing and analysis; then, input the original data into the source layer to identify the incremental data information, thereby determining the specific changed data and the specific content of the change; based on the incremental data information, determine the inconsistencies Quality standard data is problem data; once problem data is discovered, a rectification report will be determined based on the problem data, and feedback will be displayed to provide relevant technical personnel with corresponding rectification suggestions; thereby improving the accuracy of data quality management.

In a possible implementation, determining problem data based on the incremental data information includes:

Based on the incremental data information, determine the data table information;

Acquisition quality issues;

Determine the quality subject based on the data table information and the quality issues;

Determine quality rule information based on the quality problem and the quality subject;

If the quality rule information is consistent with the preset quality rule threshold, the quality rule information is determined to be the target quality rule information;

Based on the target quality rule information, determine the execution method;

According to the execution method, the problem data is determined.

By adopting the above technical solution, the data table information is obtained by analyzing the incremental data information; after obtaining the quality problems, the quality subject is obtained by identifying and analyzing the quality problems and data table information, so as to better carry out quality management. ; Then, based on the quality issues and the main body of the corridor, the quality rule information is determined, which provides guidance and constraints for subsequent data and analysis; the quality rule information is compared with the preset quality rule threshold. If the quality rule information is different from the preset quality rule If the thresholds are consistent, it means that the quality rule information meets the requirements, and then the quality rule information is retained and set as the target quality rule information; based on the target quality rule information, the corresponding execution method is determined, and the problematic data is determined through the execution method , thereby improving the accuracy of determining problem data.

In a possible implementation, determining the quality subject based on the data table information and the quality problem includes:

Obtain business requirements;

Based on the business requirements, determine the change information;

Based on the change information and the data table information, determine the target table;

Determine the first keyword according to the target table;

According to the quality problem, determine the second keyword;

If the first keyword is consistent with the second keyword, the quality problem corresponding to the second keyword is input into the preset table to determine the quality subject.

By using the above technical solutions, business needs are obtained, and change information is determined based on business needs, so as to further understand the changes in data; change information and data table information are analyzed and identified, and the data tables associated with the change information are determined. , that is, the target table is determined; then, keywords are set for the target table and the quality problem respectively, and the first keyword and the second keyword are determined respectively, where the target table corresponds to the first keyword, and the quality problem corresponds to the second keyword. keyword; then, the first keyword and the second keyword are matched. If the first keyword and the second keyword are consistent, the quality problem corresponding to the second keyword is input into the preset table to determine Quality subject, thereby improving data utilization efficiency.

In a possible implementation, determining quality rule information based on the quality problem and the quality subject includes:

Based on the quality issues, determine the quality template;

Determine filling information according to the quality subject;

If the quality template successfully matches the quality problem, the filling information is added to the quality rule threshold, and the quality rule information is determined.

By adopting the above technical solution, after obtaining the quality problem, the corresponding quality template is determined according to the description of the quality problem, thereby determining the problem handling method and requirements; then, based on the quality subject, the filling information is determined for supplementary Improve the quality rule threshold; match the quality template with the quality problem. If the quality template matches the quality problem successfully, add the filling information to the quality rule threshold to determine the quality rule information, which provides guidance for subsequent data processing and analysis. and constraints.

In a possible implementation, determining an execution method based on the target quality rule information includes:

Get quality tasks;

Based on the quality task, determine task attribute information;

The execution mode is determined based on the task attribute information and the target quality rule information.

By adopting the above technical solution, after obtaining the task quality, based on the analysis of the quality task, the task attribute information corresponding to the quality task is determined, which provides a basis for subsequent determination of the execution method; then, based on the task attribute information and the target quality rule information, the task attribute information corresponding to the quality task is determined. Come up with corresponding execution methods to achieve effective management of different tasks and improve the efficiency and accuracy of task execution.

In a possible implementation, determining the problem data according to the execution method includes:

Based on the execution method, determine the quality statement details;

Check the incremental data information according to the quality statement details and determine the consulted data;

If the query data does not exist in the preset exception database, the query data is input into the problem database to determine the problem data.

By adopting the above technical solution, after the execution mode is determined, the corresponding quality statement details are determined according to the execution mode; then, the incremental data information is reviewed according to the quality statement details, and the query data is determined; after that, the query data is determined The data is matched with the preset exception database. If the query data does not exist in the preset exception database, the data corresponding to the query data will be transferred to the problem database to determine the problem database; thereby improving the accuracy of determining the problem data.

In a possible implementation, determining a rectification report based on the problem data, and displaying the feedback, further includes:

Obtain the rectified data after rectification;

Verify the rectification data and determine the verification results.

By using the above technical solution, the rectified data after rectification is obtained, so as to further understand the rectified data; then, the rectified data is verified and the verification results are determined; thereby the quality level of the rectified data is understood.

In the second aspect, this application provides an enterprise data quality management device that adopts the following technical solution:

An enterprise data quality management device, including: an original data determination module, an incremental data information determination module, a problem data determination module and a rectification report determination module, wherein,

The original data determination module is used to obtain business data and determine the original data based on the business data;

The incremental data information determination module is used to input the original data into the source layer and determine the incremental data information;

A problem data determination module, configured to determine problem data based on the incremental data information, where the problem data is data that does not meet quality standards;

The rectification report determination module is used to determine the rectification report based on the problem data and provide feedback for display.

By adopting the above technical solution, the original data determination module obtains the business data, thereby determining the specific enterprise data of the construction group enterprise. Then, based on the business data, the original data is determined, thereby removing duplicate or blank businesses in the business data. Data is removed to adapt to subsequent data processing and analysis; then, the incremental data information determination module inputs the original data into the source layer, identifies the incremental data information, and thereby determines the specific changed data and the specific content of the change; Based on the incremental data information, the problem data determination module determines the data that does not meet the quality standards, that is, problem data; once the rectification report determination module finds the problem data, it determines the rectification report based on the problem data, and displays the feedback to provide relevant technical personnel with Corresponding rectification suggestions; thereby improving the accuracy of data quality management.

In a possible implementation, the problem data determination module includes: a data table information determination unit, a quality problem acquisition unit, a quality subject determination unit, a quality rule information determination unit, a target quality rule information determination unit, and an execution mode determination unit and the problem data determination unit, where,

A data table information determining unit, configured to determine data table information based on the incremental data information;

Quality problem acquisition unit, used to obtain quality problems;

A quality subject determination unit, used to determine the quality subject based on the data table information and the quality problem;

A quality rule information determination unit, configured to determine quality rule information based on the quality problem and the quality subject;

A target quality rule information determination unit configured to determine that the quality rule information is the target quality rule information if the quality rule information is consistent with the preset quality rule threshold;

An execution mode determination unit, configured to determine the execution mode based on the target quality rule information;

A problem data determining unit is used to determine the problem data according to the execution mode.

In a possible implementation, the quality subject determination unit is specifically used for:

Obtain business requirements;

Based on the business requirements, determine the change information;

Based on the change information and the data table information, determine the target table;

Determine the first keyword according to the target table;

According to the quality problem, determine the second keyword;

If the first keyword is consistent with the second keyword, the quality problem corresponding to the second keyword is input into the preset table to determine the quality subject.

In a possible implementation, the quality rule information determining unit is specifically used to:

Based on the quality issues, determine the quality template;

Determine filling information according to the quality subject;

If the quality template successfully matches the quality problem, the filling information is added to the quality rule threshold, and the quality rule information is determined.

In a possible implementation, the execution mode determination unit is specifically used for:

Get quality tasks;

Based on the quality task, determine task attribute information;

The execution mode is determined based on the task attribute information and the target quality rule information.

In a possible implementation, the problem data determination unit is specifically used for:

Based on the execution method, determine the quality statement details;

Check the incremental data information according to the quality statement details and determine the consulted data;

If the query data does not exist in the preset exception database, the query data is input into the problem database to determine the problem data.

In a possible implementation, the enterprise data quality management device further includes: a rectification data acquisition module and a verification result determination module, wherein,

The rectification data acquisition module is used to obtain the rectification data after rectification;

The verification result determination module is used to verify the rectification data and determine the verification result.

In the third aspect, this application provides an electronic device that adopts the following technical solution:

An electronic device including:

at least one processor;

memory;

At least one application program, wherein at least one application program is stored in the memory and configured to be executed by at least one processor, the at least one application program is configured to: execute the above enterprise data quality management method.

In the fourth aspect, this application provides a computer-readable storage medium, adopting the following technical solution:

A computer-readable storage medium includes: storing a computer program that can be loaded by a processor and execute the above enterprise data quality management method.

To sum up, this application includes the following beneficial technical effects:

The business data is obtained to determine the specific enterprise data of the construction group enterprise. Then, based on the business data, the original data is determined to eliminate duplicate or blank business data in the business data to adapt to subsequent data processing and Analysis; then, input the original data into the source layer to identify the incremental data information, thereby determining the specific changed data and the specific content of the change; based on the incremental data information, determine the data that does not meet the quality standards, that is, Problem data; once problem data is discovered, a rectification report will be determined based on the problem data, and feedback will be displayed to provide relevant technical personnel with corresponding rectification suggestions; thereby improving the accuracy of data quality management.

Description of drawings

Figure 1 is a schematic flow chart of the enterprise data quality management method of this application;

Figure 2 is a block diagram of the enterprise data quality management device of this application;

Figure 3 is a schematic diagram of an electronic device according to an embodiment of the present application.

Detailed ways

The present application will be further described in detail below in conjunction with Figures 1-3.

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments These are part of the embodiments of this application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

The embodiment of the present application provides an enterprise data quality management method, which is executed by an electronic device. The electronic device can be a server or a terminal device. The server can be an independent physical server or multiple physical servers. The server cluster or distributed device formed by it can also be a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be connected directly or indirectly through wired or wireless communication methods. The embodiments of the present application are not limited to this. Make restrictions.

Referring to Figure 1, the method includes: step S101, step S102, step S103 and step S104, wherein:

Step S101: Obtain business data and determine original data based on the business data.

In the application embodiment, the business data includes master data, production and operation data, and marketing data; the master data specifically includes project master data, management agency master data, counterparty unit master data, and financial institution master data, and the production and operation data specifically includes contract Information, project information, delivery information, completion information, and marketing data specifically include real estate monthly production, corporate adjustment tables, newly signed contract tables, and contract tables; the original data is data that needs to be tested for data quality.

Specifically, after receiving the business data transmitted by technical personnel, the electronic device cleans the data and removes invalid, duplicate or blank data. Then the electronic device converts the business data corresponding to each business system into a unified data format. And store the converted business data in the data lake STG (buffer layer), and the electronic device sets the business data falling into the data lake STG (buffer layer) as original data.

After the electronic device determines the original data, since not all the original data needs to be inspected and processed, the electronic device will generate an SQL statement to create a view in the database by writing an SQL statement or dragging and dropping, thereby controlling the scope of the data inspection. .

Step S102: Input the original data into the source layer to determine the incremental data information.

In the application embodiment, the incremental data information includes incremental data and increase period information for each incremental data entry.

Specifically, after obtaining the original data, the electronic device integrates the original data in the STG (buffer layer) of the data lake into the source layer through operations such as data extraction, conversion and loading; then, the electronic device increments the data in the source layer. Identify the data, determine the updated or new original data, set these data as incremental data, and determine the period information added to each incremental data entry, such as adding a timestamp and date to each incremental data entry; This ensures data accuracy and completeness.

Step S103: Determine problem data based on the incremental data information.

In the application embodiment, the problem data is data that does not meet quality standards.

Specifically, the electronic device performs a quality check on the data in the source layer, and evaluates the integrity and accuracy of the data by checking the incremental data rules. The electronic device identifies abnormalities or errors by comparing and analyzing the incremental data information. Wrong data entries; then, the electronic device sets the abnormal or erroneous data entries as problem data, and stores the identified problem data in the problem database for subsequent rectification and processing.

Step S104: Determine the rectification report based on the problem data, and display the feedback.

Specifically, the electronic device reads the problem database based on the identified problem data and the results of the data quality inspection, and displays the problem data summarized and detailed in different dimensions; the electronic device determines the status of each piece of problem data based on the historical data of the problem database. The weight is scored based on the historical data of the problem database and the weight of each problem data; the electronic equipment determines the corresponding rectification report based on the business requirements transmitted to the electronic equipment by the technical personnel, and transmits them to the technical personnel's display equipment. The technician is prompted to rectify the data according to the rectification report; after the technician makes the rectification, the electronic device obtains the rectified data and verifies the rectified data. If the data is exceptional data, the corresponding data is transferred to the exception database.

The embodiment of the present application provides an enterprise data quality management method to obtain business data, thereby determining the specific enterprise data of the construction group enterprise, and then determine the original data based on the business data, thereby duplicating the business data or blank business data is eliminated to adapt to subsequent data processing and analysis; then, the original data is input into the source layer to identify the incremental data information, thereby determining the specific changed data and the specific content of the change; based on the incremental Quantitative data information is used to determine data that does not meet quality standards, that is, problem data; once problem data is found, a rectification report is determined based on the problem data, and feedback is displayed to provide relevant technical personnel with corresponding rectification suggestions; thereby improving data quality management accuracy.

In step S103, problem data is determined based on incremental data information, which specifically includes: determining data table information based on incremental data information; obtaining quality issues; determining quality subjects based on data table information and quality issues; based on quality issues and quality subjects , determine the quality rule information; if the quality rule information is consistent with the preset quality rule threshold, determine the quality rule information as the target quality rule information; determine the execution method based on the target quality rule information; determine the problem data based on the execution method.

In the application embodiment, the quality issues are offline documents compiled based on actual business, mainly describing the content to be checked in business language; the work group is a collection of users; the rule group is a collection of SQL statements.

Specifically, the electronic device identifies the different data tables corresponding to each incremental data information by identifying the incremental data information. After the electronic device obtains the quality issues transmitted by the technical personnel, it will locate the data in the different data tables. The table information is matched with the quality issues, and the data table information that successfully matches the quality issues is integrated and linked to construct a quality subject that contains all the information that needs to be applied or displayed; then, the electronic device fields the quality issues and the quality subject respectively. Extract and match the extracted fields to determine the corresponding quality rule information.

Further, after the quality rule information is determined, the quality rule information is compared with the preset quality rule threshold. If the instruction rule information is consistent with the preset quality rule threshold, it means that the corresponding quality rule information is a quality rule that needs to be uniformly executed. information; if the quality rule information is consistent with the preset quality rule threshold, the corresponding quality rule information is determined to be the target quality rule information; then, the electronic device collects and organizes the target quality rules and determines the execution method; after determining the execution method , the electronic device determines data that does not meet the quality standard requirements, that is, problem data, based on the execution method.

Among them, each quality rule has corresponding permissions. The permissions of the control rules are managed through work groups and rule groups. Electronic devices manage SQL statements in batches through configuring rule groups.

Determine the quality subject based on the data table information and quality issues, including: obtaining business requirements; determining change information based on business requirements; determining the target table based on the change information and data table information; determining the first keyword based on the target table; For quality issues, determine the second keyword; if the first keyword is consistent with the second keyword, enter the quality issues corresponding to the second keyword into the preset table to determine the quality subject.

In the application embodiment, the change information is data table information that needs to be added, deleted, and changed.

Specifically, after receiving the business requirements transmitted by the technical personnel, the electronic device retrieves and matches the data table information according to the business requirements, determines the data table information corresponding to the business requirements, and the electronic device retrieves the data table information corresponding to the business requirements. Set as change information; then, the electronic device sorts and summarizes the change information and data table information, obtains a new data table, and sets it as the target table; after that, the electronic device performs keyword analysis on the target table and quality issues respectively. Extract and obtain the first keyword and the second keyword respectively; the electronic device matches the first keyword and the second keyword. If the first keyword and the second keyword match successfully, it means that the corresponding keyword appears in the target table. If there is a quality problem, the electronic device will input the quality problem corresponding to the second keyword into the preset table and store it in the designated subject view storage library to determine the quality subject.

Among them, the method of storing into the designated subject view repository is that the electronic device selects the database storage that needs to be stored when determining the quality subject, including database address, port, user name, password and other information, and then the electronic device determines that the storage is to be established. The SQL statement of the view, each quality subject matches a view, and the name of the view is the name of the quality subject.

Determine the quality rule information based on the quality problem and the quality subject, including: determining the quality template based on the quality problem; determining the filling information based on the quality subject; if the quality template matches the quality problem successfully, the filling information is added to the quality rule threshold , determine the quality rule information.

In the application embodiment, the filling content includes configuring rule names, rule descriptions, rule groups to which they belong, checking data sources, whitelists, quality templates, and selecting data tables and fields in the database to fill variables specified in the quality template.

Specifically, the electronic device identifies the quality problem, selects the corresponding inspection data, determines the quality template, and matches the SQL statement corresponding to the quality template. For example, if the quality problem is that the project name in the project table cannot be empty, the quality can be determined directly. The template is select count(*) FROM ${table_a} WHERE ${column_a} IS NULL; since the quality template cannot be used 100% with other data table information in actual data services, the electronic device will combine the quality template with the default The quality template is matched to determine a reusable quality template; the electronic device determines the filling information by identifying the quality subject; if the quality template matches the quality problem successfully, the electronic device adds the filling content to the quality rule threshold. Determine the quality rule information that conforms to the quality subject.

Based on the target quality rule information, the execution method is determined, which specifically includes: obtaining the quality task; based on the quality task, determining the task attribute information; and determining the execution method based on the task attribute information and the target quality rule information.

In the application embodiment, the task attribute information includes task name, scheduling period, and business label.

Specifically, the technician creates a new quality task in the quality task operation interface and transmits it to the electronic device. After receiving the quality task, the electronic device determines the task attribute information corresponding to each quality task based on the quality task. Better understand the requirements and goals of the task; then the electronic device determines the corresponding execution method based on the determined task attribute information and target quality rule information, thereby determining the execution method that meets the needs.

Determine the problem data based on the execution method, including: Determine the quality statement details based on the execution method; Check the incremental data information based on the quality statement details to determine the query data; If the query data does not exist in the preset exception database, then Check the data and enter it into the problem database to determine the problem data.

Specifically, after determining the execution method, the electronic device immediately reads the task code of the configuration quality task platform and generates a quality statement detailed instruction to obtain all target quality rule information under the task quality; the electronic device queries or retrieves and obtains the corresponding task. The electronic device stores the quality statement details of all target quality rule information under quality in the ODS layer; then, the electronic device queries the quality statement details stored in the ODS layer and sets the data at the query location. It is determined as query data; after the electronic device determines the query data, it compares the query data with the data in the preset exception database. If the query data does not exist in the preset exception database, the query data is transmitted to the problem database. and set it as problem data; if the query data exists in the preset exception database, the query data will be deleted; after the electronic device determines the problem data, it will place the determined problem data according to the quality task dimension. Enter different data table information in the database.

Based on the problem data, determine the rectification report and provide feedback for display. This also includes: obtaining the rectification data after rectification; verifying the rectification data and determining the verification results.

Specifically, when the technical staff rectifies the data according to the rectification report, the electronic equipment extracts the rectified data and determines the extracted data as rectified data; in order to determine whether the data meets the requirements after rectification, the electronic device The device will verify the rectification data before issuing the rectification report. If the rectification data exists in the preset exception database at this time, the corresponding rectification data will be transferred to the exception database.

Referring to Figure 2, enterprise data quality management 20 may specifically include: original data determination module 201, incremental data information determination module 202, problem data determination module 203, and rectification report determination module 204, wherein,

The original data determination module 201 is used to obtain business data and determine the original data based on the business data;

The incremental data information determination module 202 is used to input the original data into the source layer and determine the incremental data information;

The problem data determination module 203 is used to determine problem data based on the incremental data information. The problem data is data that does not meet the quality standards;

The rectification report determination module 204 is used to determine the rectification report based on the problem data and provide feedback for display.

In a possible implementation of the embodiment of this application, the problem data determination module 203 includes: a data table information determination unit, a quality problem acquisition unit, a quality subject determination unit, a quality rule information determination unit, a target quality rule information determination unit, and an execution method. Determine the unit and the problem data determine the unit, where,

The data table information determination unit is used to determine the data table information based on incremental data information;

Quality problem acquisition unit, used to obtain quality problems;

The quality subject determination unit is used to determine the quality subject based on the data table information and quality issues;

The quality rule information determination unit is used to determine quality rule information based on quality issues and quality subjects;

The target quality rule information determination unit is used to determine the quality rule information as the target quality rule information if the quality rule information is consistent with the preset quality rule threshold;

The execution mode determination unit is used to determine the execution mode based on the target quality rule information;

The problem data determination unit is used to determine the problem data according to the execution mode.

One possible implementation of the embodiment of this application, the quality subject determination unit, is specifically used for:

Obtain business requirements;

Based on business needs, determine change information;

Based on the change information and data table information, determine the target table;

According to the target table, determine the first keyword;

Based on quality issues, determine the second keyword;

If the first keyword is consistent with the second keyword, the quality issue corresponding to the second keyword is input into the preset table to determine the quality subject.

A possible implementation manner of the embodiment of this application, the quality rule information determination unit, is specifically used for:

Based on quality issues, determine the quality template;

According to the quality subject, determine the filling information;

If the quality template matches the quality problem successfully, the filling information is added to the quality rule threshold to determine the quality rule information.

One possible implementation manner of the embodiment of this application, the execution mode determination unit, is specifically used for:

Get quality tasks;

Based on quality tasks, determine task attribute information;

Determine the execution method based on task attribute information and target quality rule information.

One possible implementation manner of the embodiment of this application, the problem data determination unit, is specifically used for:

Based on the execution method, determine the quality statement details;

Check the incremental data information according to the quality statement details and determine the data to be checked;

If the query data does not exist in the preset exception database, the query data will be entered into the problem database to determine the problem data.

One possible implementation of the embodiment of this application, the enterprise data quality management device 20, also includes: a rectification data acquisition module and a verification result determination module, wherein,

The rectification data acquisition module is used to obtain the rectification data after rectification;

The verification result determination module is used to verify the rectification data and determine the verification results.

Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be described again here.

The embodiment of the present application also introduces an electronic device from the perspective of a physical device, as shown in Figure 3. The electronic device 30 shown in Figure 3 includes: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, electronic device 30 may also include a transceiver 304. It should be noted that in practical applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

The processor 301 may be a CPU (Central Processing Unit, central processing unit), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit, application specific integrated circuit), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various illustrative logical blocks, modules, and circuits described in connection with this disclosure. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

Bus 302 may include a path that carries information between the above-mentioned components. The bus 302 may be a PCI (Peripheral Component Interconnect, Peripheral Component Interconnect Standard) bus or an EISA (Extended Industry Standard Architecture, Extended Industry Standard Architecture) bus, etc. The bus 302 can be divided into an address bus, a data bus, a control bus, etc. For ease of presentation, only one thick line is used in Figure 3, but it does not mean that there is only one bus or one type of bus.

The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, RAM (Random Access Memory, random access memory) or other types that can store information and instructions. Dynamic storage devices can also be EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact DiscRead Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, Laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or any other device capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer medium, but not limited to this.

The memory 303 is used to store application program code for executing the solution of the present application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the contents shown in the foregoing method embodiments.

Among them, electronic devices include but are not limited to: mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PAD (tablet computers), PMP (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc. mobile terminals such as digital TVs, desktop computers, etc. Also for servers etc. The electronic device shown in FIG. 3 is only an example and should not impose any restrictions on the functions and usage scope of the embodiments of the present application.

It should be understood that although various steps in the flowchart of the accompanying drawings are shown in sequence as indicated by arrows, these steps are not necessarily performed in the order indicated by arrows. Unless explicitly stated in this article, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least some of the steps in the flow chart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and their execution order is also It does not necessarily need to be performed sequentially, but may be performed in turn or alternately with other steps or sub-steps of other steps or at least part of the stages.

The above are only some of the embodiments of the present application. It should be pointed out that those of ordinary skill in the art can also make several improvements and modifications without departing from the principles of the present application. These improvements and modifications should also be regarded as This is the protection scope of this application.

Claims (10)

1. A method for enterprise data quality management, comprising:

acquiring service data, and determining original data based on the service data, wherein the service data is data corresponding to enterprise service, and the original data is data needing to be subjected to data quality detection;

inputting the original data into a source pasting layer, and determining incremental data information, wherein the incremental data information is;

based on the incremental data information, determining problem data, wherein the problem data is data which does not accord with a quality standard;

and determining a correction report according to the problem data, and feeding back and displaying the correction report.

2. The method of claim 1, wherein said determining problem data based on said incremental data information comprises:

determining data table information based on the incremental data information;

acquiring quality problems;

determining a quality main body according to the data sheet information and the quality problem;

determining quality rule information based on the quality issue and the quality body;

if the quality rule information is consistent with a preset quality rule threshold, determining the quality rule information as target quality rule information;

determining an execution mode based on the target quality rule information;

and determining the problem data according to the execution mode.

3. The method of claim 2, wherein said determining a quality body based on said data table information and said quality problem comprises:

acquiring service requirements;

determining change information based on the service demand;

determining a target table based on the change information and the data table information;

determining a first keyword according to the target table;

determining a second keyword according to the quality problem;

and if the first keyword is consistent with the second keyword, inputting a quality problem corresponding to the second keyword into a preset table, and determining the quality main body.

4. The method of claim 2, wherein said determining quality rule information based on said quality problem and said quality body comprises:

determining a quality template based on the quality problem;

determining filling information according to the quality main body;

and if the quality template is successfully matched with the quality problem, adding the filling information into a quality rule threshold value, and determining the quality rule information.

5. The method for managing quality of enterprise data according to claim 2, wherein said determining an execution mode based on said target quality rule information comprises:

acquiring a quality task;

determining task attribute information based on the quality task;

and determining the execution mode according to the task attribute information and the target quality rule information.

6. The method for managing quality of enterprise data according to claim 2, wherein said determining said problem data according to said execution mode comprises:

determining quality statement details based on the execution mode;

referring to the incremental data information according to the quality statement details, and determining reference data;

and if the reference data does not exist in the preset exception database, inputting the reference data into a problem database, and determining problem data.

7. The method for managing enterprise data quality as claimed in claim 1, wherein said determining a correction report based on said problem data, and feeding back for display, further comprises:

obtaining rectifying data after rectifying;

and verifying the rectification data, and determining a verification result.

8. An enterprise data quality management apparatus, comprising:

the system comprises an original data determining module, a service data processing module and a data processing module, wherein the original data determining module is used for acquiring service data and determining the original data based on the service data;

the incremental data information determining module is used for inputting the original data into the source pasting layer and determining incremental data information;

the problem data determining module is used for determining problem data based on the incremental data information, wherein the problem data is data which does not accord with the quality standard;

and the correction report determining module is used for determining a correction report according to the problem data and feeding back and displaying the correction report.

9. An electronic device, comprising:

at least one processor;

a memory;

at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: an enterprise data quality management method as claimed in any one of claims 1 to 7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed in a computer, causes the computer to perform an enterprise data quality management method according to any of claims 1-7.