39 results about "Master data management" patented technology

The invention relates to the field of community old-age care, and discloses a community old-age care-oriented medical-care-and-care-combined data intercommunication and service coordination system, which comprises a sensing module used for acquiring physiological data of old people, old-age care service data, environment data and service demand information to form multi-modal information; the network module is used for carrying out multi-modal information transmission, protocol conversion and edge calculation preprocessing to obtain processed data; and the data module is used for constructing a standardized data lake according to the processed data by adopting a unified data standard and a main data management technology, and carrying out fusion storage, treatment and safety protection to obtain multi-source information. Multi-modal information is collected to provide a data basis for cross-mechanism cooperation, data transmission and preprocessing are performed, and a standardized data lake is constructed through a unified data standard and main data management, so that medical institutions, pension institutions and community grids can share global data such as health states, service records and the like of old people in real time.

The invention relates to the technical field of data processing, in particular to a main data management method and system based on enterprise data governance, and the method comprises the steps: defining a basic model structure based on an enterprise general main data object, and storing the basic model structure in a metadata form; obtaining a business system change event and a manual expansion demand and converting the event and the demand into a structured description; zero-coding extension configuration of attributes, classification and association relationships is completed through a visual interface; executing interface adaptation, data mapping adaptation and rule conflict detection; and synchronizing the effective extension model to a service layer, a cleaning layer and a monitoring layer. The system comprises a demand awareness module, a dynamic modeling module, an extension configuration module, an adaptation engine module and a life cycle management module. According to the method, full-process management of the master data model from demand capture to business landing is realized, and the model expansion efficiency and the business adaptation capability are improved.

The invention belongs to the technical field of resource management, and particularly discloses a multi-service domain integrated customizable multi-tenant management system and method, and the system comprises a multi-tenant architecture which is configured to be used for defining different service domains as different service systems, and splitting a plurality of tenants according to different standards under each service system, different organizations are divided under each tenant, and each organization corresponds to different users; the main data management module is configured to be used for defining the dimension relation of basic data according to the relation of tenants, organizations and users under each business system within each year range, and distributing corresponding basic data to each business system; and the portal control module is configured to be used for realizing login operation and entrance authority control of the user. Tenant splitting can be performed according to different standards under different business systems, so that customized design of a multi-tenant framework is realized, and tenant splitting requirements of different business systems can be met.

The invention provides a main data management method and system based on a strategy mode and a rule engine, and relates to the field of data management. Executing dual verification and calculating a priority; selecting a processing rule set to construct a workflow; dynamically generating a distribution rule based on the quality tag; and writing the main data into a message queue and pushing the main data to the target system according to the weight. Through the differential processing strategy and the self-adaptive data distribution, the main data processing efficiency and quality are improved, and the reliability and flexibility of data circulation are enhanced.

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 embodiment of the invention provides an enterprise material master data management method and device and a storage medium, relates to the technical field of enterprise data management and information, is applied to processing equipment deployed with a material data management model enhancement package, obtains a target material model suitable for a target enterprise, analyzes a material data table file based on the model, and stores the analyzed material data table file. The method comprises the steps of obtaining first material data, verifying the material data based on a quality verification rule base in an enhanced packet, cleaning the material data by adopting a material data cleaning tool in the enhanced packet according to a quality verification result to obtain second material data, and issuing a list and an external business system list according to the material data. And sending the second material data to the target business system through the material data release interface in the enhancement packet, thereby realizing definition and control for the material characteristic value, promoting the target enterprise to carry out comprehensive business process management conforming to the large enterprise, and further improving the material data sharing and cooperation efficiency of the multi-business system.

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 invention discloses a master data management method and system, a storage medium and equipment. The method comprises the steps of collecting to-be-managed master data of an enterprise, performing chaotic mapping, converting the master data into a DNA sequence, converting the master data into a DNA complementary sequence according to a DNA complementary rule, and taking the DNA complementary sequence as a sending end message digest; acquiring an optimal encryption key by adopting a dynamic encryption technology, and encrypting the collected main data into a ciphertext; transmitting the encrypted ciphertext and the sending end message digest to a receiving end of master data management, decrypting, performing chaotic mapping on master data decrypted by the receiving end, converting the master data into a DNA sequence, converting the DNA sequence into a DNA complementary sequence according to a DNA complementary rule, and taking the DNA complementary sequence as a receiving end message digest; whether the sending end message digest is the same as the receiving end message digest is judged, and if yes, the ciphertext received by the receiving end is stored and managed; otherwise, sending out an abnormal prompt. According to the invention, the accuracy of master data management is ensured on the basis of providing master data security.

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.

Systems and methods call a portion of an application programming interface (API) to access a portion of a current state data server of the blockchain computing platform (BCP) configured to perform virtual machine processing, the BCP comprising interconnected data processing nodes that include: a master ledger configured to store data asset records for master data received from decentralized application transactions performed via the interconnected data processing nodes, and peer nodes configured to provide cryptographic algorithmic trust control for master data management of the master data. The calling includes an API call to the current state data server to obtain current state results of certified transaction(s) in the master ledger, the certified transaction(s) having been certified at least in part via an endorsement protocol. Current state results of the certified transaction(s) are received from the current state server and displayed via a user interface of the user device.

Systems and methods call a portion of an application programming interface (API) to access a portion of a current state data server of the blockchain computing platform (BCP) configured to perform virtual machine processing, the BCP comprising interconnected data processing nodes that include: a master ledger configured to store data asset records for master data received from decentralized application transactions performed via the interconnected data processing nodes, and peer nodes configured to provide cryptographic algorithmic trust control for master data management of the master data. The calling includes an API call to the current state data server to obtain current state results of certified transaction(s) in the master ledger, the certified transaction(s) having been certified at least in part via an endorsement protocol. Current state results of the certified transaction(s) are received from the current state server and displayed via a user interface of the user device.

The invention discloses a master data governance method and device, a medium and electronic equipment, and the method comprises the steps: responding to the to-be-governed master data received from an upstream system, and carrying out the governance of the to-be-governed master data based on the system type of the upstream system and the business type of the to-be-governed master data; determining a target rule engine matched with the to-be-governed main data in at least two candidate rule engines; performing compliance verification on the to-be-governed main data by adopting the target rule engine, and performing quality marking on the to-be-governed main data based on an obtained compliance verification result to obtain marked main data; and issuing the marked main data to a downstream system. According to the technical scheme, the integration rate and the utilization rate of the data are improved, and data sharing is achieved.

The present invention discloses a multi-source and multi-database based flow-batch integrated master data governance method and device, which relates to the field of big data. The method comprises: obtaining original data of at least one data source among multiple data sources; performing data cleaning on the original data to obtain standardized data; constructing a master data analysis matrix based on the standardized data, and obtaining basic data through analysis and identification based on the master data analysis matrix; defining the master data table structure according to data requirements and data standards, constructing a conceptual data model based on the basic data, obtaining a logical data model based on the conceptual data model and the master data table structure expansion, establishing a physical data model based on the logical data model, and cross-validating the data generated by the physical data model to obtain master data, which can improve the relevance and availability of data, improve data processing efficiency, and enhance the strategic synergy of the organization.

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 provides a digital management method for small and medium-sized enterprises, which belongs to the technical field of digital management, and is characterized in that an extensible framework is constructed through integration of an open source ERP system and a low-code development platform, and modular configuration is realized in combination with enterprise scale parameters and business type parameters. The method comprises a main data management system based on a hybrid coding rule, a three-level data exchange system, a double-track digital governance mechanism and external system standardized interaction, and a technical debt management and control model and a disaster recovery test mechanism are introduced. According to the method, the problems of high digitalization cost, difficulty in customization, data islanding and the like of small and medium-sized enterprises are solved, low-cost rapid deployment, cross-platform data intercommunication, data quality controllability and service continuity guarantee are realized, and the digitalization management efficiency and the return on investment rate of the small and medium-sized enterprises are remarkably improved.

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.

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 comprise 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 master data management blockchain services, and (b) attribute-based access control (ABAC) time-based rules restricting access to portions of master data. The blockchain computing function also maintains a security framework that controls access to processing node resources across the virtual network.

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 discloses a master data management system in a multi-data source scene, and relates to the technical field of master data management.According to the master data management system, a multi-source receiving module is arranged to collect corresponding service data from multiple service systems in real time, and a data integration unit periodically integrates the collected service data; the master data management unit generates a master data verification sequence according to the master data generated after integration; according to the method, a plurality of regular integer groups obtained by grouping main data are independently processed, for any regular integer group, the number of digits of a character 1 is counted so as to determine a derivative array of the regular integer group, a non-'0' character on the right side of a decimal point of a regular correction group is extracted to determine a conversion array, and finally the derivative array and the conversion array are combined so as to obtain a conversion result. Therefore, the verification array of each regular integer group is determined, the possibility of coupling collision in the data verification process can be effectively reduced, the credibility of the data verification result is enhanced, and the risk of data management of an enterprise is reduced.

The invention discloses a new energy enterprise master data management method based on artificial intelligence, and relates to the technical field of data management, and the method comprises the steps: collecting new energy enterprise master data; performing data verification on the collected main data, and marking abnormal data in the main data; intelligent error correction is carried out on the data marked as abnormal data, and error data are automatically repaired. According to the new energy enterprise master data management method based on artificial intelligence provided by the invention, the automation and intelligence level of data verification and restoration is improved. The problem that a traditional method depends on manual intervention is solved. The machine learning model is adopted to automatically classify the abnormal data into a rule repairable type or an inference repair type, and repair is performed through the predefined business rule and the similar data inference algorithm, so that various abnormal conditions can be flexibly handled, the repair precision is improved, and the data quality and consistency are remarkably improved.

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 logistics data processing, and discloses a logistics transportation data optimization method, which comprises the following steps: acquiring transportation vehicle data, acquiring vehicle positioning data through a multimode positioning terminal, calculating a container loading space utilization rate, and acquiring vehicle dynamic load data; the environment of the distribution center is sensed, a monitoring system is used for recognizing goods stacking violation behaviors of the distribution center and tracking goods, and temperature and humidity environment data of the distribution center are collected; performing standardized processing on multi-source data, cleaning abnormal data based on a rule engine, and constructing a main data management system; performing hybrid calculation and anomaly monitoring, calculating a core index, performing correlation analysis on an abnormal event by adopting a complex event processing technology, and monitoring a condition that data deviates from a threshold value through an anomaly detection model; and intelligently deciding and generating a scheme. According to the method, data version control and historical archiving are realized, accurate back calculation and deep analysis of core indexes can be realized, the decision is more scientific, and the refined management and control and efficiency of the whole transportation process are effectively improved.