Master data management platform

Abstract

The invention discloses a master data management platform. The master data management platform comprises a data entry module used for entering various types of master data; the data cleaning module is used for cleaning main data; the data verification module is used for performing main data verification according to a data verification rule; the data quality monitoring module is used for regularly checking the main data quality according to a data quality monitoring mechanism and carrying out early warning according to a data quality checking result; a globally unique identifier allocation module for allocating a globally unique identifier for the primary data; the security interface module is used for carrying out identity verification on the business system accessing the main data and authorizing the business system passing the identity verification; and the version control and change management module is used for performing data version control and recording the change history of each data update. According to the master data management platform provided by the invention, the problems of difficult integration and difficult application of the master data are solved, unified and automatic management of the master data is realized, and the data management cost of an enterprise is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of data management, and in particular to a master data management platform. Background Art

[0002] In the current enterprise environment, with the expansion and diversification of business, the number of business systems is also increasing. Although each business system is independent, they share the task of processing and storing key business data.

[0003] Due to the wide variety of business systems, master data is widely distributed and in various forms, lacking uniformity and integrity, making the integration and application of master data difficult. At present, a large amount of manual intervention and coordination is required in the data governance process, which not only increases the consumption of human resources, but also increases management costs, and enterprises need to invest more time and money to ensure the accuracy, availability and security of data. This high-cost governance model not only affects the operational efficiency of the enterprise, but may also become a bottleneck restricting the development of the enterprise. Summary of the invention

[0004] To this end, the present application provides a master data management platform to solve the problems of difficult master data integration and application and high cost in the prior art.

[0005] In order to achieve the above objectives, this application provides the following technical solutions:

[0006] A master data management platform, comprising:

[0007] Data entry module, used to enter various types of master data according to pre-established master data models and data dictionaries;

[0008] Data cleaning module, used to clean master data according to pre-established data identification rules and processing strategies;

[0009] Data validation module, used to perform master data validation according to pre-established data validation rules;

[0010] Data quality monitoring module, which is used to regularly check the master data quality according to the pre-established data quality monitoring mechanism and issue early warnings based on the data quality inspection results;

[0011] A globally unique identifier allocation module, used for allocating a globally unique identifier to the master data according to a globally unique identifier generation method;

[0012] The security interface module is used to authenticate the business systems that access the master data and authorize the business systems that have passed the authentication.

[0013] The version control and change management module is used to perform data version control and record the change history of each data update.

[0014] Preferably, the master data model includes entities, attributes and relationships.

[0015] Preferably, the data dictionary includes the definition, format, data type, length and value range of the data items.

[0016] Preferably, the data quality monitoring module determines data quality using indicators including completeness, accuracy, consistency, timeliness and reliability.

[0017] Preferably, the data quality check result includes problem type, discovery time and impact scope.

[0018] Preferably, it further comprises a data correction module for correcting data according to the data quality check result of the data quality monitoring module.

[0019] Preferably, the security interface module supports the REST standard protocol or the SOAP standard protocol.

[0020] Preferably, the security interface module adopts a token-based identity authentication mechanism when performing identity authentication.

[0021] Preferably, the token-based authentication mechanism is OAuth 2.0 or JSON Web Tokens.

[0022] Preferably, the change history recorded for each data update includes the change content, change time and change personnel.

[0023] Compared with the prior art, this application has at least the following beneficial effects:

[0024] The present application provides a master data management platform, including: a data entry module for entering various types of master data according to a pre-established master data model and data dictionary; a data cleaning module for cleaning master data according to pre-established data identification rules and processing strategies; a data verification module for verifying master data according to pre-established data verification rules; a data quality monitoring module for regularly checking the quality of master data according to a pre-established data quality monitoring mechanism and issuing early warnings based on the results of data quality inspections; a globally unique identifier allocation module for allocating a globally unique identifier to master data according to a globally unique identifier generation method; a security interface module for authenticating business systems that access master data and authorizing business systems that have passed the authentication; a version control and change management module for performing data version control and recording the change history of each data update. The master data management platform provided by the present application solves the problems of difficult master data integration and application, realizes unified and automatic management of master data, and reduces the cost of enterprise data management. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more intuitively illustrate the prior art and the present application, exemplary drawings are given below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing the present application; for example, those skilled in the art are capable of easily making conventional adjustments or further optimizations to the addition / reduction / attribution division, specific shapes, positional relationships, connection methods, dimensional ratios, etc. of certain units (components) based on the technical concepts and exemplary drawings disclosed in the present application.

[0026] Figure 1 A schematic diagram of the structure of a master data management platform provided for this application. DETAILED DESCRIPTION

[0027] The present application is further described below in detail through specific embodiments in conjunction with the accompanying drawings.

[0028] In the description of this application: unless otherwise specified, the meaning of "plurality" is two or more. The terms "first", "second", "third", etc. in this application are intended to distinguish the objects referred to, and do not have special meanings in terms of technical connotations (for example, they should not be understood as emphasizing the importance or order, etc.). Expressions such as "including", "comprising", "having", etc. also mean "not limited to" (certain units, components, materials, steps, etc.).

[0029] The terms such as "upper", "lower", "left", "right", "middle", etc. cited in this application are usually used to indicate the general relative position relationship for the purpose of intuitive understanding by referring to the drawings, and are not absolute limitations on the position relationship in the actual product.

[0030] In order to solve the problems mentioned in the background technology, enterprises need to adopt more advanced data management strategies and technologies. For example, by establishing a unified data platform to achieve centralized storage and management of data, the consistency and availability of data can be improved. At the same time, the use of automated tools and processes to reduce reliance on manual operations can reduce the error rate and improve the efficiency of data processing. In addition, by formulating clear data governance policies and standards, the quality and security of data can be ensured throughout the life cycle.

[0031] In order to clarify the functions of the master data management platform, this application conducted project preparation, research and analysis, and system planning before establishing the master data management platform. Specifically, project preparation includes formulating a project charter, including project goals, implementation scope, construction content, and project plans; at the same time, determining the project organization, staffing, and resource management. Research and analysis include: understanding the company's current status and needs in data management, data classification, data standards, data maintenance, etc. through questionnaire surveys, on-site interviews, etc. System planning includes designing the company's internal organizational structure, master data management system, assessment method standards and specifications, and master data operation methods.

[0032] Based on this, this application provides a master data management platform, including:

[0033] The data entry module is used to enter various types of master data based on the pre-established master data model and data dictionary.

[0034] Specifically, the master data model and data dictionary can ensure that the input data format is consistent. The master data model defines the structure and relationship of the data, including entities, attributes and relationships, and determines the classification and stratification of the data. The data dictionary can clarify the definition, format, data type, length, value range, etc. of each data item. When entering data, it is necessary to enter it according to the pre-established data entry specifications, including mandatory items and input formats.

[0035] The data cleaning module is used to clean the master data according to pre-established data identification rules and processing strategies.

[0036] Specifically, the present application can use data cleaning tools to identify and remove duplicate, erroneous or inconsistent records during data cleaning, thereby ensuring the integrity, uniqueness and accuracy of the data. The data cleaning tool can select a suitable data cleaning tool or develop a customized data cleaning program, and determine the frequency and process of data cleaning.

[0037] The data validation module is used to perform master data validation according to pre-established data validation rules.

[0038] Specifically, the data validation rules pre-established in this application can ensure the accuracy and consistency of the data. Data validation includes front-end validation and back-end validation.

[0039] The data quality monitoring module is used to regularly check the master data quality according to the pre-established data quality monitoring mechanism and issue early warnings based on the data quality inspection results.

[0040] Specifically, this application has established a data quality monitoring mechanism to regularly check data quality and regularly evaluate the integrity, accuracy and uniqueness of master data through continuous data quality checks. Specific quality standards, thresholds and warning mechanisms are formulated for each data item. Once data quality problems are found, the correction process is triggered in a timely manner to ensure data reliability.

[0041] In other words, the data quality monitoring module sets thresholds for data quality indicators. Once the thresholds are exceeded, the system automatically issues a warning and records all data quality issues found, including problem type, discovery time, impact scope, etc. Depending on the severity of the problem, the data correction process is automatically or manually triggered to correct the problems found and update the data. Data quality reports can also be generated regularly to report data quality status to management and relevant personnel, so as to adjust technical implementation as needed, optimize data quality monitoring processes, and record the configuration of all monitoring tools, inspection processes, and problem-solving steps.

[0042] Specifically, the indicators used by the data quality monitoring module to determine data quality include: completeness, accuracy, consistency, timeliness and reliability; data quality monitoring tools can be selected according to the needs and resources of the organization; methods for evaluating data quality include automated testing and manual review; regular data quality checks include inspection frequency and scope.

[0043] The globally unique identifier allocation module is used to allocate a globally unique identifier to the master data according to the globally unique identifier generation method.

[0044] Specifically, the globally unique identifier assignment module assigns a globally unique identifier (GUID) to master data, ensuring that each entity's record is unique in the system, helping to track and associate data to avoid duplication and conflict.

[0045] Specifically, when assigning a globally unique identifier, you need to determine the generation rules and format of the GUID to ensure its global uniqueness. The globally unique identifier generation method can use a system-generated GUID or a custom generation method. Integrating the GUID generation mechanism in the data creation process can ensure that each new record is automatically assigned a GUID. When updating the master data model, you need to reserve space for the GUID field and define its properties. Add instructions for using the GUID in the data entry specification to ensure that data entry personnel understand its importance.

[0046] Specifically, for existing data, perform a comprehensive mapping to assign GUIDs to each record. During data migration, smoothly transition existing data to the new GUID system. Establish a problem-solving process to handle issues that arise in GUID allocation and use. Update data backup and recovery processes to ensure the consistency and integrity of GUIDs. Before assigning GUIDs, perform data cleansing to ensure data accuracy and consistency. Continuously optimize GUID generation and management methods based on usage feedback and technological developments.

[0047] The security interface module is used to authenticate the business systems that access the master data and to authorize the business systems that have passed the authentication.

[0048] Specifically, the security interface module uses authentication and authorization mechanisms to ensure that only authorized business systems can access master data. The security interface module should follow standard protocols, such as REST or SOAP, and should include data verification and integrity checks to prevent data from being tampered with during transmission.

[0049] Specifically, the security interface module needs to determine the requirements of the API interface, including functional, performance and security requirements, and clarify the API functions, input and output parameters, data formats and return values. The security interface module uses a token-based authentication mechanism for authentication, such as OAuth 2.0 or JWT (JSON Web Tokens). Define roles and permissions, role-based access control (RBAC) or more fine-grained access control.

[0050] Specifically, use the HTTPS protocol to encrypt data transmission to prevent data from being eavesdropped or tampered with during transmission; require strict input validation to prevent security threats such as SQL injection and cross-site scripting (XSS); implement data verification logic at the API level to ensure that the received data conforms to the expected format and business rules; implement API flow control strategies to prevent API abuse and denial of service attacks (DoS); implement API monitoring and logging to track API usage and detect anomalies in a timely manner; conduct API security audits regularly to identify and fix potential security vulnerabilities. Develop a disaster recovery plan for the API to ensure that services can be quickly restored in the event of a failure; encrypt sensitive data to ensure data confidentiality and integrity.

[0051] The version control and change management module is used to perform data version control and record the change history of each data update.

[0052] Specifically, the version control and change management module is used for data version control, recording the change history of each data update in order to trace errors and track data changes. When sharing data, the latest and verified version is distributed through the interface to avoid misuse of old data. At the same time, a data update notification mechanism is provided so that the business system can obtain new master data information in a timely manner.

[0053] Specifically, determine the rules and processes for data version control; select a suitable version control system, such as Git, SVN, etc., or use the version control function of the database. Add version control fields to the data model, such as version number, creation time, modification time, etc.; record the history of each data change, including the content of the change, change time, change personnel and other information; formulate a data update process, including change request, approval, implementation and verification; implement a review and approval mechanism for data changes to ensure the rationality and compliance of data changes; back up data before updating so that it can be restored to the old version when necessary; implement version control in the API interface to ensure that different versions of the interface can coexist and be compatible; design a data distribution mechanism to ensure that the business system can obtain the latest and verified data version; provide a data update notification mechanism, such as Webhooks, message queues, etc., so that the business system can obtain new master data information in a timely manner. Perform consistency checks after data updates to ensure data integrity and accuracy; implement data audits and monitoring to track data changes and usage; record policies, processes, and operational guidelines for version control and change management; update technical documentation, including API documentation, database design, and system architecture; ensure that version control and change management comply with relevant regulations and standards; and develop a data recovery process so that data can be quickly restored when errors occur.

[0054] When the master data management platform provided by this application is implemented, the master data management platform will be integrated with various target information systems to realize interactive operations such as the collection and distribution of master data; the implementation of master data includes the formulation of coding classification, attributes, fields, approval processes, integrated cleaning distribution, integrated switching strategies, etc.

[0055] On the basis of the master data management platform provided in this application, an operation system, consulting planning and enterprise organizational structure can also be established. Establishing an operation system includes: building a master data management operation organization, formulating management standards such as master data management methods, maintenance rules, and application assessment standards; consulting planning includes understanding the overall project requirements through research during the consulting planning stage, including the view of the master data model, the data source of data integration, etc.; the enterprise organizational structure includes building a three-tier organizational structure system, including the decision-making layer, the management layer and the execution layer, to support the work of master data management.

[0056] In addition, you can also establish a master data management system, master data management scope, and master data sharing. The master data management system includes the formulation of a corresponding master data management system, which stipulates the business, technology, and implementation-related specifications and guidelines in the master data management process; the master data management scope includes determining the systems and departments involved, as well as the scope of master data, such as personnel, departments, business units, etc.; master data sharing includes distributing master data to various business systems for use after construction is completed, which can be achieved through interface distribution.

[0057] In summary, the master data management platform provided by this application has the following advantages:

[0058] (1) Improving data quality: Through functions such as data cleaning, verification, and matching, the platform can ensure the accuracy and consistency of data and solve problems such as data duplication, errors, and incompleteness.

[0059] (2) Realize unified data management: The platform supports centralized management of various types of master data (such as customers, products, suppliers, etc.), eliminates data silos, and realizes a unified view of data.

[0060] (3) Enhanced data accessibility and transparency: Through centralized storage and metadata management, the platform improves the manageability and traceability of data and ensures the standardization of data governance.

[0061] (4) Support data-driven decision-making: The platform provides real-time data analysis and data mining tools to help enterprises make business decisions quickly and improve response speed and decision-making efficiency.

[0062] (5) Promote data sharing and collaboration: The platform supports real-time synchronization and sharing of multi-source data, breaks down data silos, improves data utilization efficiency, and promotes business collaboration and information sharing.

[0063] (6) Improve the flexibility of IT structure: The platform can enhance the adaptability of IT structure, build a data management foundation and corresponding specifications covering the entire enterprise, and flexibly adapt to changes in business needs.

[0064] (7) Reduce operating costs: Through automated data management processes, the platform reduces cost waste caused by data inconsistencies and errors and improves the level of automation in data processing.

[0065] (8) Strengthening data security and compliance: The platform implements fine-grained data access control, data encryption and auditing to ensure the security of data during transmission and storage, and meet the data security and compliance requirements of enterprises.

[0066] (9) Improve enterprise operational efficiency: The platform uses integrated master data management to achieve one-time entry and multi-party use, reduce data duplication and errors, improve data utilization efficiency, and thus improve overall operational efficiency.

[0067] The technical features of the above embodiments may be arbitrarily combined (as long as there is no contradiction in the combination of these technical features). To make the description concise, not all possible combinations of the technical features in the above embodiments are described; these embodiments that are not explicitly written should also be considered to be within the scope of this specification.

Claims

1. A master data management platform, characterized in that: include: Data entry module, used to enter various types of master data according to pre-established master data models and data dictionaries; Data cleaning module, used to clean master data according to pre-established data identification rules and processing strategies; Data validation module, used to perform master data validation according to pre-established data validation rules; Data quality monitoring module, which is used to regularly check the master data quality according to the pre-established data quality monitoring mechanism and issue early warnings based on the data quality inspection results; A globally unique identifier allocation module, used for allocating a globally unique identifier to the master data according to a globally unique identifier generation method; The security interface module is used to authenticate the business systems that access the master data and authorize the business systems that have passed the authentication. The version control and change management module is used to perform data version control and record the change history of each data update.

2. The master data management platform according to claim 1, characterized in that: The master data model includes entities, attributes and relationships.

3. The master data management platform according to claim 1, characterized in that: The data dictionary includes the definition, format, data type, length and value range of data items.

4. The master data management platform according to claim 1, characterized in that: The data quality monitoring module determines the data quality indicators including: completeness, accuracy, consistency, timeliness and reliability.

5. The master data management platform according to claim 1, characterized in that: The data quality inspection results include problem type, discovery time and impact scope.

6. The master data management platform according to claim 1, characterized in that: It also includes a data correction module, which is used to correct the data according to the data quality inspection result of the data quality monitoring module.

7. The master data management platform according to claim 1, characterized in that: The security interface module supports the REST standard protocol or the SOAP standard protocol.

8. The master data management platform according to claim 1, characterized in that: The security interface module adopts a token-based identity authentication mechanism when performing identity authentication.

9. The master data management platform according to claim 8, characterized in that: The token-based authentication mechanism is OAuth 2.0 or JSON Web Tokens.

10. The master data management platform according to claim 1, characterized in that: The change history recorded for each data update includes the change content, change time and change personnel.

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