22 results about "Master data management" patented technology

The present application relates to the technical field of data processing, and more particularly to a kind of master data management method and system based on enterprise data governance, including based on enterprise general master data object definition basic model structure and store in the form of metadata;Business system change event and artificial extension demand are obtained and converted into structured description;Attribute, classification and correlation are completed by visual interface Zero coding extension configuration;Interface adaptation, data mapping adaptation and rule conflict detection are executed;Synchronization of effective extension model to service layer, cleaning layer and monitoring layer.The system includes requirement perception, dynamic modeling, extension configuration, adaptation engine and life cycle management module.The present application realizes the whole process management of master data model from requirement capture to business landing, improves model extension efficiency and business adaptation capability.

The invention discloses a lightweight master data management method, which relates to the technical field of digital office, and realizes flexible iteration and cross-system data collaboration of a master data specification by creating a master data source system, issuing a dynamic adaptation system and standard and utilizing a master data classification dynamic mapping mechanism to clarify a master data unique source system; the method comprises the following steps: establishing an intelligent workflow, establishing a main data application function and approval permission intelligent adaptation engine in an office OA, and automatically generating a main data distribution interface with permission binding after obtaining approval, thereby improving the approval efficiency and the main data use security; an adaptive API interface is created, an interface dynamic adaptation and load balancing mechanism is constructed in a main data source system, and efficient and direct distribution of main data is achieved; through main data distribution quality closed-loop monitoring, log analysis and dynamic optimization engine linkage are utilized, and the main data distribution quality is guaranteed.

A method for managing Master Data Management (MDM) data sets is provided. The method stores a second MDM data set into a second data repository separate and distinct from a first data repository storing a first MDM data set; continuously protects data integrity of the first and second MDM data sets, by: (i) maintaining separation between the first data repository and the second data repository, and (ii) preventing unauthorized data sharing by the first and second MDM data sets; detects a change to an MDM record of the first MDM data set, via a communication platform; determines that the second MDM data set includes a second MDM record associated with the patient, based on recognition of the patient by the second data repository; creates a cross-reference identifier for the patient; and updates the first MDM data set and the second MDM data set to include the cross-reference identifier.

The invention provides a material main data full-process governance method based on an adaptive fusion large model. The method comprises the following steps: firstly, obtaining to-be-governed material main data; inputting the material main data into the adaptive fusion large model to obtain a material main data governance result; wherein the adaptive fusion large model takes a multi-modal basic model as a base, and integrates a dynamic weight adjustment engine, a scene perception module and a collaborative optimization module; the multi-modal basic model is used for carrying out cross-modal feature fusion on the material main data; the scene sensing module is used for identifying a current service scene; and the dynamic weight adjustment engine is used for determining the weight of the collaborative optimization module according to scene requirements and data features. According to the method, the large adaptive model integrating scene perception, multi-modal fusion and dynamic weight adjustment is constructed, so that the jump of a material main data governance strategy from static solidification to intelligent dynamic solidification is realized, and the governance accuracy and the whole-process automation level in a cross-business scene are remarkably improved.

The application relates to a power distribution network operation and industry expansion engineering multi-source business data fusion method and system, which comprises the following steps: S1: a unified data access and adaptation platform is constructed to realize full-coverage access of power distribution network operation and industry expansion engineering related data; S2: based on the accessed data, an enterprise-level master data management system covering the whole domain of power distribution network operation and industry expansion engineering is established; S3: a knowledge graph in the field of power distribution network operation and industry expansion engineering is constructed; S4: based on the knowledge graph in the field of power distribution network operation and industry expansion engineering, a whole-process digital process model of power distribution network operation and industry expansion engineering is constructed based on business process management technology, and intelligent management of the business process is realized; and S5: based on the knowledge graph in the field of power distribution network operation and industry expansion engineering, a time-space integrated data fusion framework is constructed, business data, geographic space information and time sequence information are deeply fused, and a four-dimensional data model is formed. The application realizes whole-process data fusion and cooperation of power distribution network operation and industry expansion engineering.

The application discloses a master data management system and a master data management method. The master data management system comprises a background storage system and at least one front-end business system. The background storage system receives first standardized master data of the front-end business system through an input interface, approves and stores the first standardized master data. The front-end business system uses second standardized master data in the background storage system through an output interface of the background storage system. Different front-end business systems set different personalized approval processes and personalized interactive interfaces according to business requirements. In the application, the background storage system stores master data of each front-end business system as standardized master data after approving the master data through the personalized approval process. On this basis, each front-end business system calls the standardized master data of the background storage system and realizes utilization of the standardized master data through the personalized interactive interface, thereby realizing centralized management of master data and personalized processes of business systems.

The invention discloses a full-process verification method, a mistake proofing method and a system thereof for medicines. The verification method comprises the following steps: obtaining a verification main file set of all verification objects; performing real-time monitoring and maintenance on the verification period, and screening the verification main archives in the verification main archive set according to the verification period or verification project requirements; formulating a first-year verification total plan according to the screened verification main file, and formulating a second-year verification total plan according to the department verification plan; and according to an early warning mechanism, regularly sending the to-do list to the verification sub-archive principal in advance, executing the verification plan, and after the verification plan is completed, updating the archive library. Electronic full-process verification system closed-loop management is realized, verification management efficiency is greatly improved, and manual operation omissions are reduced; according to the error proofing method based on main data management, the quality and service interruption risk is effectively avoided, the traceability requirement of laws and regulations on the whole verification process is met, and the verification management efficiency and normalization are greatly improved.

The application provides a nuclear power plant handover and production transfer whole process collaborative management system and method, the system includes main data management, handover package plan, business process engine, knowledge graph and improved GNN intelligent reasoning, joint inspection collaboration, rule verification, data storage and unified workbench and other modules. The core uses five tuple knowledge graph, improved GNN and BERT / LSTM / SOM AI model, realizes dependent reasoning, completeness verification, text analysis, construction period prediction and defect clustering. The system abandons the traditional extensive mode, solves the pain points such as difficult artificial combing dependence, weak data isolation and loose closed-loop management through semantic modeling, graph intelligent reasoning and rule rigid execution. Realize multi-unit parallel management and control, full-factor structured embedding, digital signature storage, opinion item forced closed loop and report automatic generation, promote the upgrade of business from online to technology driven mode.

The invention provides a method for distributing production master data of multiple factories based on a message bus, and relates to the technical field of Internet of Things, industrial Internet and intelligent factories. The multi-factory production master data distribution method based on the message bus comprises the steps of flexible modeling of production master data, data access and updating, distribution object configuration, dynamic distribution based on the message bus, and distribution data verification and feedback. Different industry data structures are adapted through visual modeling, an affiliation domain field is introduced to define the factory affiliation right, and accurate, real-time and reliable distribution of multi-factory data is realized in combination with incremental real-time distribution and active release modes. The method solves the problems that an existing scheme is poor in adaptability, fuzzy in data affiliation and insufficient in distribution real-time performance and fault tolerance, is suitable for a group multi-factory architecture, can effectively support the main data management requirement in digital transformation of a manufacturing enterprise, and has good practicability and expansibility.

This invention relates to the field of data management technology and proposes a master data management method and system based on element ontology. The method includes: expanding and allocating dynamic attribute dimension sets and state change rule sets for core elements in a manufacturing scenario; uniformly encoding the static attribute set, dynamic attribute dimension set, and state change rule set of the core elements to obtain an integrated element ontology of the core elements; semantically binding real-time data in the manufacturing scenario with the integrated element ontology to obtain a manufacturing element knowledge graph of the core elements; extracting the target generation element from the production demand change instruction when a production demand change instruction is received; locating the associated attributes in the manufacturing element knowledge graph based on the target generation element, and performing attribute changes on the integrated element ontology based on the associated attributes. This invention can improve the efficiency of master data management.

A system (100) for automated account, call and sample reconciliation in commercial life sciences operations, the system comprising: an agent-based AI orchestration engine (1) configured to independently initiate, sequence, and manage voting workflows across multiple data sources; a relational data warehousing and lineage layer (2) configured to ingest, normalize, correlate and store structured operational data associated with accounts, calls and samples; an MDM synchronization and golden record management module (3) configured to synchronize master data entities and generate consistent golden records across different platforms; an engine for reconciling accounts, calls and samples (4) configured to compare related records across the synchronized records and to identify mismatches, missing links, duplicate records and transaction inconsistencies; a module for compliance rules, exception notifications and policy validation (5) that is configured to validate reconciled data against predefined business, regulatory and sample responsibility rules; a human-in-the-loop workflow, recommendation, and resolution console (6) configured to present detected exceptions along with corrective suggestions and to enable user-assisted or automated resolution; and a module (7) for audit analysis, continuous learning and reporting, configured to generate audit trails, reconciliation summaries, performance analyses and adaptive learning updates based on historical exception resolution results.

The invention relates to a distribution network operation and business expansion project multi-source business data fusion method and system. The method comprises the following steps: S1, constructing a unified data access and adaptation platform, and realizing full-coverage access of distribution network operation and business expansion project related data; s2, based on the accessed data, establishing an enterprise-level main data management system covering the whole domain of the distribution network operation and the business expansion project; s3, constructing a knowledge graph of the distribution network operation and business expansion engineering field; s4, constructing a whole-process digital process model of the distribution network operation and the business expansion project based on a business process management technology according to the knowledge graph of the field of the distribution network operation and the business expansion project, and realizing intelligent management of the business process; and S5, constructing a time-space integrated data fusion framework according to the knowledge graph of the distribution network operation and business expansion engineering field, and carrying out deep fusion on the business data, the geographic space information and the time sequence information to form a four-dimensional data model. According to the invention, the whole-process data fusion and collaboration of the distribution network operation and the business expansion project are realized.

The invention discloses an informatization management system for warehouse logistics, and belongs to the technical field of informatization processing. Comprising a warehouse main data management module used for managing warehouse information, warehouse area information, warehouse location information, a warehouse location template, platform information, stacker information and a goods collection route; the business main data management module is used for managing cargo owner information, material information, business partner information, packaging information, a batch attribute template and business parameters; and the rule management module is used for managing a quality inspection rule, a positioning rule, condition configuration, distribution logic global assignment, a package distribution rule, a storage location distribution rule, a bar code analysis rule, a UDI verification rule, a wave plan rule and a replenishment rule. And during material information management, corresponding packaging information, a batch attribute template, a quality inspection rule, a bar code analysis rule, a UDI verification rule, a positioning rule, a storage location distribution rule, a replenishment rule and storage area information are selected, and owner information and material information are received from the MDC.

This invention discloses a product identifier method based on encoding rules for automatic generation, belonging to the field of product identifier encoding management technology, and is used to solve the problems of encoding chaos and identification difficulties. This invention constructs a closed-loop encoding generation mechanism that covers attribute standardization, rule chain compilation, candidate generation, conflict verification, full lifecycle binding, and log traceability. This ensures that product identifiers have uniqueness, structural integrity, and business applicability during the generation stage. Then, semantic alignment is achieved through field dictionary and alias comparison. Candidate identifiers are dynamically generated by combining exclusive constraints and value domain verification. The availability and consistency of identifiers are ensured through pre-occupied number segments, mapping verification, and rule change sandbox exercises. The platform supports binding external identifiers and lifecycle objects, improving master data management efficiency and system collaboration capabilities.

The invention relates to the technical field of data integration, provides a data integration method and system for multi-source heterogeneous data, and solves the problem that data security control and business application flexibility are difficult to effectively cooperate in a cross-domain data integration process. The method comprises the following steps: collecting multi-source heterogeneous data from different security domains, and associating a credibility level identifier with a digital certificate; according to the credible level identifier, performing encrypted transmission on the multi-source heterogeneous data to generate encrypted transmission data; in the target security domain, verifying and decrypting the encrypted transmission data by using a public key infrastructure (PKI) according to the digital certificate to obtain plaintext data, and performing hierarchical storage on the plaintext data by using a key derivation function to obtain hierarchical data; and adopting a data integration algorithm, calling a preset master data management specification and a semantic mapping table to carry out entity merging and attribute alignment on the hierarchical data, and generating credible data assets. According to the invention, secure transmission, trusted processing and intelligent integration of multi-source heterogeneous data can be realized.

The invention relates to the technical field of oil field information engineering, and discloses a main data management method based on an oil field heterogeneous system, which comprises the following steps of: sorting objects, analyzing various business activities and data of an enterprise, sorting core business objects and key attributes which are uniformly managed in each business process according to a high-value and high-sharing principle, and managing the business activities and the data of the business activities. Determining master data management content; object attribute management: managing object attribute information including contents of names, codes, descriptions, types, manufacturers, dates and sizes; and data set management: managing other business information of the object, including personalized attribute data of different devices. According to the method, the core business objects and the key attributes of the unified management are subjected to object carding, and the main data management content is clarified, so that the problem that cross-system, cross-business and cross-process data cannot be associated and shared can be solved, the data can be managed in a unified manner, and the efficiency of the business process is improved.

The application provides a kind of strategy mode and rule engine-based master data management method and system, related to data management field, including receiving master data and self-adapting flow limiting;Perform double check and calculate priority;Select processing rule set to construct workflow;Based on quality mark dynamic generation distribution rule;Master data is written into message queue and pushed to target system according to weight.The application improves master data processing efficiency and quality through differentiated processing strategy and adaptive data distribution, enhances the reliability and flexibility of data flow.

The invention relates to the technical field of equipment management, and discloses an equipment attribute unified management system, which comprises an equipment information storage model, an object template system, a main data management system, a material model data source and a measuring point management system, establishing an owner data table by taking the specific attributes of the equipment as main data; storing an incidence relation table of the material models and the main data; constructing a material model library, and performing structured design to obtain a material model data source; according to the method, the equipment information storage model is established to uniformly store equipment information, the flexibility and the expandability are enhanced, the uniform object template system and the main data management system are established, the equipment attribute management is standardized, and the material model library is constructed into a material model data source; a data foundation is laid for automatic filling of equipment attributes, the measuring points are managed in a unified mode through a measuring point management system, and the standardization and efficiency of measuring point management are guaranteed.

The present application relates to the technical fields of digital workshop and intelligent manufacturing, in particular to a production management system and method of an electric control system product, comprising a MMS subsystem, an AGV scheduling subsystem, an ERP subsystem and an IAM subsystem, the MMS subsystem is integrated with the AGV scheduling subsystem, the ERP subsystem and the IAM subsystem, and is used for realizing digital control of the production process; wherein the MMS subsystem comprises a main data management module, a work order management module, a production execution module, a quality management module, a material management module, a personnel management module, a technical document module, a process management module and a process management module. Through the production management system and method, the problems of high investment cost and unstable operation can be effectively solved.

A strategic master data management blockchain computing platform includes virtual machine(s) configured and deployed to execute an operating system of the blockchain computing platform across a virtual network, and a plurality of interconnected data processing nodes each comprising a plurality of functional layers, where the plurality of functional layers comprises an identity management access layer that is configured to establish a blockchain computing function. The blockchain computing function includes defining (a) role-based access control (RBAC) policies for access to node-based core operations and trust data asset management blockchain services, and (b) attribute-based access control (ABAC) time-based rules restricting access to portions of master data and reference data for trust data assets. The blockchain computing function also maintains a security framework that controls access to processing node resources and trust data asset results available across the enterprise virtual network.

The present invention relates to a comprehensive system designed to prevent and control fraudulent sales, understood as any type of unlawful transaction, including the sale of counterfeit, stolen or illicitly acquired goods. This system assigns unique public codes to goods and services, linking them to registered owners and providing complementary secret codes that can only be accessed by these owners. This combination ensures the authenticity, traceability and security of the goods and services at any stage of their life cycle. The system allows owners to transfer ownership in a secure and authorised manner without the buyer having direct access to the secret code, thereby protecting the integrity of the process. In addition, it allows transfer authorisations to be delegated to third parties in a controlled and secure manner. During each transaction, the system automatically updates the ownership record, disables the previous secret codes and generates new unique secret codes for the new owner, thereby strengthening security and preventing duplications or fraud. The platform that supports the system can be implemented in both centralised environments, with a main data-management server, and decentralised environments using technologies such as blockchain to distribute and protect information. This technological flexibility allows the system to adapt to different infrastructures and operating models, thereby ensuring an effective implementation in a wide variety of contexts. The system is also widely applicable in sectors such as the consumer goods trade, the purchase and sale of used products, the pharmaceutical industry, the fashion industry, issuance of educational certificates, digital services management and event tickets, among others. The versatility of the system ensures that it is functional in both in-person and remote transactions, acting as a guarantor in these transactions in order to verify authenticity and oversee compliance with the purchase and sale

Solutions are disclosed that synergize fragmented data for use by business enterprise operations. Examples use a master data management (MDM) platform to tag business enterprise data, such as customer relations management (CRM), billing, and enterprise resource planning (ERP) data with unique entity identifiers (IDs) and generate multi-domain master records. A customer data platform (CDP) is built that includes customer data products such as customer disconnection, lead scoring, and market segmentation. A data services layer has artificial intelligence (AI), generative AI, and an API layer, that permit efficient and accurate generation of next best action (NBA) and predictive analytics solutions, as well as access to the customer data products by a business-to-business (B2B) website server that leverages the data from the plurality of customer data products to improve B2B customer experience.