1058 results about "Master data" patented technology

This disclosure includes a process for merging legacy databases having different data schema into a principal data store. A computing device retrieves a legacy database from each of a plurality of domains of an organization to form a plurality of legacy databases, where at least two legacy databases in the plurality of legacy databases have a different data schema. For each of the plurality of legacy databases, the computing device retrieves data from the respective legacy database, places the data from the respective legacy database into a respective unstructured database, and merges the respective unstructured database into a principal data store designed to hold data for every domain of the plurality of domains.

A system and method for efficient data storage, transfer, synchronization, and security using automated model monitoring and training. The system analyzes test datasets to detect data drift, retraining encoding and decoding algorithms as needed. New data sourceblocks are created and assigned codewords, compiling an updated codebook for distribution to connected devices. A novel dyadic distribution subsystem simultaneously compresses and encrypts data by transforming input streams into a dyadic distribution. This process generates a compressed main data stream and a secondary stream of transformation information, which are combined into a secure output. The system includes a network device manager for optimizing codebook distribution based on device resource usage. Operating in both lossless and lossy modes, the system offers flexible, efficient, and secure data handling across various network configurations.

The invention relates to the field of data storage and backup, and discloses a method and a system for transmitting disaster recovery backup capability of an emergency recovery unit. The method comprises the steps of establishing a quantum encryption transmission channel, monitoring a network index in real time and predicting transmission quality to start preventive optimization, calculating a link quality score to carry out link switching, verifying integrity and consistency of received data and executing retransmission, carrying out multi-mode data backup, and switching to an emergency recovery unit when a main data center fails. The system comprises a quantum encryption transmission module, a transmission monitoring and switching module, a data verification and retransmission module, a multi-mode backup module and an emergency switching and synchronization module. Through the technical scheme, the problems of data transmission security and high efficiency can be effectively solved, the disaster recovery backup capability of the emergency recovery unit is improved, the service continuity is ensured, and the method and the device are suitable for scenes with high requirements on data security and service continuity.

A system for migrating master data to a target system, comprising: at least one data processor; and at least one memory result in operations comprising: extracting the master data from a source database; validating the extracted master data at a database layer; mapping the validated master data to the target database specific datasets, and inserting the mapped master data into a target database, wherein the extraction, validation, mapping, and insertion are performed at the database layer.

The invention relates to a power distribution network abnormal state intelligent identification method based on unmanned aerial vehicle routing inspection, and the method comprises the following steps: S1, obtaining power distribution network routing inspection related data, including asset main data, historical operation and maintenance data and environment constraints; s2, constructing the digital twinning of the power distribution network based on the power distribution network inspection related data, and obtaining the mapping from the equipment ID to the spatial pose and parameters; s3, generating a risk heat map based on historical defects and environmental risk scoring; s4, constructing an equipment-geography-working condition knowledge graph, and generating inspection targets and priorities according to line sections in combination with mapping from equipment IDs to spatial poses and parameters and a risk heat map to obtain a task package; and S5, performing multi-target route inspection according to the task package, the risk heat map and the mapping from the equipment ID to the spatial pose and the parameter, and intelligently identifying the abnormal state of the power distribution network. The operation reliability of the power distribution network is effectively improved, and the power supply quality is improved.

The invention relates to the technical field of embedded data storage, and discloses a method and a system for prolonging the service life of a FLASH simulation EEPROM (Electrically Erasable Programmable Read-Only Memory) in a single chip microcomputer, and the method comprises the following steps: firstly, initializing the FLASH, dividing the FLASH into a main data area, a mapping table area, a backup area and a transaction log area, selecting a physical block through a dynamic wear leveling algorithm when data is written, and writing the data into a database; the method comprises the following steps of: starting a backup area or a transaction log area, safely updating a mapping table by using a transaction mechanism, performing cyclic redundancy check when reading data, if the cyclic redundancy check fails, starting cascade recovery from the backup area or the transaction log area, and finally, updating a transaction log to record operation so as to form a closed-loop management process. According to the invention, through a set of dynamic wear leveling and data classification management mechanism, global and uniform distribution of the write load in the storage array is realized, the physical block with the least erasing times is selected during writing, the access frequency of the data can be identified, and cold data which is not changed frequently can be actively migrated.

A system and method for adaptive data processing combining compression and encryption. The system analyzes input data characteristics, compares probability distributions, and creates a transformation matrix to convert data into a dyadic distribution. It generates a main data stream of transformed data and a secondary stream of transformation information. The system dynamically selects and applies processing techniques, including transformation, encoding, compression, and encryption algorithms, based on analyzed characteristics and real-time performance metrics. It compresses the main data stream using Huffman coding and implements security measures to protect the output. A feedback loop monitors technique effectiveness, updates a knowledge base, and influences future selections. The system can operate in lossless, lossy, or modified lossless modes, adapting to different application requirements. This approach offers an efficient solution for scenarios where both data reduction and security are critical concerns.

System and methods are provided for automated SKU management. Embodiments include a user interface for receiving diverse catalog files, a Catalog Transformation module, a Real-Time Data Mesh (RTDM) module, a Master Data Governance (MDG) module, a Global Data Repository (GDR), and a Search Platform. The Catalog Transformation module, through iterative learning, transforms catalog files to a standard format and predicts categorization and attribute mapping. The RTDM module is configured to perform real-time data exchange. The MDG module validates the transformed catalogs. The GDR stores validated catalogs. Embodiments can include a Dynamic SKU Creation module and a Global Pricing Engine for real-time pricing. Embodiments improve data accuracy and SKU management, facilitating integrated order processing and fulfillment.

To provide a salary calculation device that makes salary calculation affairs efficient at a company to which public servants are loaned.SOLUTION: An affair support device 100 as a salary calculation device makes total calculations of a total payment amount, a total taxation amount, a total reward amount, a total wages amount, and overtime work reference wages according to an item definition master 106a first, and calculates dispatch adjustment allowances to temporarily determine amounts of money. Then the affair support device makes total calculations of the total payment amount, the total taxation amount, the total reward amount, and the total wages amount based upon data including temporarily determined adjustment allowances according to the item definition master 106a, and calculates dispatch adjustment allowances to determine amounts of money. Further, the affair support device makes total calculations of the overtime reference work wages based upon data including the temporarily determined dispatch adjustment allowances according to the item definition master 106a, makes total calculations of the total payment amount, the total taxation amount, the total reward amount, and the total wages amount based upon required data including the determined dispatch adjustment allowances according to the item definition master 106a, and makes total calculations of deduction total amounts based upon the required data according to the item definition master 106a.SELECTED DRAWING: Figure 1

The invention discloses a data governance method and system based on artificial intelligence, and relates to the technical field of data governance, and the method comprises the steps: effectively improving the recognition capability of structural abnormal behaviors in a device file through introducing an abnormal track extraction mechanism combining image enhancement and cuckoo search, and improving the recognition efficiency. The method combines an isolated forest model optimized by a genetic algorithm, achieves the high-confidence screening of candidate abnormal data, remarkably improves the accuracy and robustness of anomaly detection, and achieves the recognition of a redundant entity through the construction of a semantic conflict graph and the introduction of a graph matching network. The problem that in a traditional method, the field similarity is insufficient to support complex conflict judgment is effectively solved, finally, a standard equipment file is generated through a field-level fusion strategy, a governance evolution graph is synchronously updated, a complete closed loop from discovery, evaluation and fusion to optimization is formed, automation, intelligentization and self-adaptive evolution of equipment master data governance are achieved, and the efficiency is improved. And the consistency, availability and governance efficiency of the equipment data are remarkably improved.

The invention discloses a data analysis visualization processing method and device based on index management and a server, and belongs to the technical field of data processing, and the method comprises the steps: extracting related original data from main data and business data storage positions according to the data source information of each index in a predefined index dictionary, processing the extracted original data into standardized data; for the standardized data, calculating each index value according to a predefined calculation formula in an index dictionary; and obtaining visual configuration content operated by a user, automatically generating a report containing a visual chart according to the calculated index values according to the visual configuration content, and receiving a user operation instruction to export the report of the visual chart. According to the invention, the enterprise data analysis efficiency is improved, the labor cost is saved, the data visualization operation is realized, and convenience is provided for the use of the user.

System and methods are provided for automated SKU management. Embodiments include a user interface for receiving diverse catalog files, a Catalog Transformation module, a Real-Time Data Mesh (RTDM) module, a Master Data Governance (MDG) module, a Global Data Repository (GDR), and a Search Platform. The Catalog Transformation module, through iterative learning, transforms catalog files to a standard format and predicts categorization and attribute mapping. The RTDM module is configured to perform real-time data exchange. The MDG module validates the transformed catalogs. The GDR stores validated catalogs. Embodiments can include a Dynamic SKU Creation module and a Global Pricing Engine for real-time pricing. Embodiments improve data accuracy and SKU management, facilitating integrated order processing and fulfillment.

Provided herein is a method for enabling continuity of access to a primary dataset stored in a computer network, the method utilizing a node, a computer processor, and non-transitory computer-readable media storing computer-executable instructions, the node being connected to the computer network; the method including the steps of:configuring the mobile device for wireless connection to the computer network;configuring the mobile device to receive indication that the node is disconnected from the computer network, and transmit a copy of the primary dataset or a portion thereof from the computer network to the node;configuring the node to enable operations on the dataset copy and keep a record of them; andconfiguring the node to receive indication that the node is connected to the computer network and transmit the record to the computer network.

The invention discloses a real-time data deduplication method and device based on Flink, electronic equipment and a medium, and the method comprises the steps: determining a deduplication rule and a control strategy, and submitting an Flink task; acquiring real-time data in the message queue as an input data stream, determining a key value of the input data stream according to a deduplication rule, and further grouping the input data stream according to the key value through a grouping operator to obtain a grouped data stream; performing data deduplication on the grouped data stream according to the key value through a deduplication operator to obtain a main data stream and a side stream; and outputting the main data stream, and judging whether to store the side stream or not according to the control strategy. Real-time data deduplication is achieved based on the Flink, the data deduplication efficiency and reliability are improved, and the method can be widely applied to the technical field of data processing.

The invention discloses a Region-level remote disaster recovery method, system and device based on a Paas cloud platform and a medium, in the Paas cloud platform, a WAN optimization technology is adopted, and a data compression algorithm, an acceleration algorithm and a cache algorithm are adopted, so that the data transmission time delay and network congestion are reduced, and the data synchronization efficiency and speed are improved; a remote multi-activity technology is introduced, so that the main data center and the backup data center simultaneously provide services to the outside, high availability and disaster tolerance of services are ensured, the main data center is automatically switched to the backup data center when the main data center breaks down, and rapid fault switching is realized; a load balancing mechanism and a fault switching mechanism are adopted, the flow is automatically switched to the backup data center when the main data center breaks down, and rapid fault switching is achieved. By adopting the WAN optimization technology, the time and delay of cross-geographic-position data synchronization are reduced, and the reliability and real-time performance of data synchronization are ensured.

The invention relates to the technical field of data protection, and provides a CDP-based data protection method and system, and the method comprises the steps: incremental snapshot generation: a data source agent monitors the data change on a main data source, and generates an incremental snapshot; real-time copying: the transmission engine transmits the incremental snapshot to a backup server in real time; snapshot management: the backup server manages the incoming incremental snapshot data, including operations of storage, indexing, compression and the like; and recovery operation: the user can select proper recovery options through the management console, such as a specific time point, a specific application program or a specific file level to carry out recovery operation. By adopting the method, a user can realize minimum data loss and fastest-speed recovery of key data.

A device to process data associated with a surgical event of a surgery may include a processor. The processor may be configured to receive multiple data streams during the surgical event. The processor may be configured to select a primary data stream based on a surgical data interface via which the primary data stream is received. The processor may be configured to select a secondary data stream based on a surgical data interface via which the second data stream is received. The processor may be configured to identify the surgical data interfaces. The processor may be configured to generate situational data associated with the primary data stream based on the secondary data stream. The situational data may indicate a medical decision-making factor of the surgical event. The primary data stream and the situational data may be sent during the surgical event.

The invention discloses a database configuration method, system and device and a storage medium, and the method comprises the steps: determining tables needing to be queried by a user and data items needing to be queried in each table according to input information of the user; wherein the data items comprise main data items and sub-data items; according to a selection operation of a user, determining an association mode between the main data item and the sub-data item in different tables; generating data structure index information of the data search library and data synchronization general configuration from the data management library to the data search library; wherein the field type of the main data item in the data structure index information is the field type of the corresponding table of the data management library, and the field type of the sub-data item is an array; and performing data synchronization on the data search library according to the data structure index information and the data synchronization general configuration. According to the method, data synchronization between the data management library and the data search library can be flexibly and efficiently realized, and the practicability of the database can be improved. The method can be widely applied to the technical field of databases.

The embodiment of the invention provides a main data integration method and system based on index weighting, electronic equipment and a storage medium, and belongs to the technical field of data processing. According to the scheme, an evaluation system of main data is determined, and the evaluation system comprises evaluation indexes and corresponding weight values; obtaining a multi-source data set, wherein the multi-source data set comprises main data of a plurality of data sources; constructing a standard model, and performing data relation mapping according to the multi-source data set to obtain a data mapping relation; performing field scanning detection on the multi-source data set based on the standard model and the data mapping relation to obtain a scanning result, and performing weighted calculation on the scanning result according to the evaluation system to obtain a comprehensive scoring result; exporting a field full association table by referring to the comprehensive scoring result, and performing strategy analysis on the field full association table to determine a merging strategy; and integrating the multi-source data set according to the merging strategy. According to the scheme, the accuracy and efficiency of master data integration can be improved.

The invention relates to the technical field of digital twinborn management, and discloses a full-life-cycle digital twinborn management system and a modeling method. A model driving unit; a decision optimization unit; and a credible evidence storage unit. The modeling method comprises the following steps: S1, analyzing a product design bill of materials; s2, establishing a topological mapping relation between the sensor nodes and the virtual model area; s3, running Monte Carlo simulation to predict the defect probability; and S4, binding and uploading the new virtual model version and the physical product serial number. Aiming at the problem of data dispersion in the prior art, the system automatically converges three types of heterogeneous data of geometric dimension design, working condition manufacturing and maintenance monitoring into a shared cache pool through a main data table of a unified metadata structure, so that cross-stage semantic alignment and time sequence synchronization are realized, data format difference is eliminated, and data consistency is remarkably improved.

A system and method are provided for implementing a network component and verifying an update of the network component. The network component can be, e.g., a software-defined wide area network, a firewall, a router, or a load balancer. The network component can be an embedded network edge device that is implemented, e.g., in software, in circuitry, or using hardware acceleration (e.g., a data processing unit (DPU), a smart network interface card (SmartNIC), etc.). The updated version of the network component is verified by implementing it on a shadow dataplane concurrently with the current version operating on a primary dataplane, and comparing the performances of these two versions. Based on this comparison satisfying various verification criteria, the updated version passes a verification test and can be promoted to the primary dataplane.

The invention discloses a heat supply charging customer service system based on a large language model, and relates to the technical field of instant messaging, and the system comprises a user interaction module, a large language model service layer, a cue word optimization module, a heat supply knowledge graph module, an emotion semantic recognition module and a service platform module. A large language model is introduced to be fused with a heat supply professional knowledge graph, so that heat supply charging business query, complaint processing and process execution under natural language multi-round interaction are realized; a cue word adaptive optimization algorithm is adopted, a language model probability guiding genetic algorithm is used for optimizing a cue template, and the ability of understanding complex semantics is enhanced; and the service platform gets through the charging system, the bank interface and the main data to realize real-time query and automatic service processing in the dialogue. The method has the remarkable advantages of intelligent interaction, data fusion, automatic process, efficient response and the like, the user experience is improved, and the operation and maintenance cost is reduced.

The invention relates to the technical field of data management, and discloses a business and financial data governance optimization method for main data dynamic management, which comprises the following steps: step 1, carrying out multi-source data acquisition, including business system data acquisition, financial system data acquisition and other channel data acquisition, step 2, pre-processing the acquired data, numbering and storing, and step 3, carrying out data management on the acquired data. 3, calculating a data quality index, a data change condition, a data value and a data comprehensive coefficient based on the stored data set, and 4, performing feedback according to the data comprehensive coefficient, so that various data sources inside and outside an enterprise can be comprehensively covered, a data island phenomenon is reduced, and meanwhile, the quality and credibility of data are improved; the data comprehensive coefficient is comprehensively evaluated by combining the data quality index, the data change condition and the data value, the data level is comprehensively reflected, a comprehensive perspective is provided for enterprises to see the data, and the enterprises can better understand and manage the data and find potential problems and opportunities.

According to the WeChat operation automation comprehensive service platform provided by the invention, by integrating the firewall architecture module, the unified management module and the user information integration module, safe and efficient management of enterprise WeChat data and seamless integration with enterprise CRM are realized. The firewall architecture module adopts a proxy server technology and intelligent traffic analysis, monitors and filters potential malicious traffic in real time, and ensures data security; the unified management module stores and manages application attributes, main data and public data of enterprise WeChat in a centralized manner by using a structured data warehouse technology, and optimizes a data management process; the user information integration module realizes seamless integration of enterprise WeChat user information and CRM user information through an SSO technology and a data mapping engine; and the operation efficiency and the data management capability of an enterprise on the WeChat platform are greatly improved.

A port is to couple to another die over a die-to-die (D2D) link and includes physical layer (PHY) circuitry including a first number of sideband lanes to carry data for use in training and management of the D2D link, and a second number of mainband lanes to implement a main data path of the D2D link. The mainband lanes include a forwarded clock lane, a valid lane, and a plurality of data lanes. A logical PHY coordinates functions of the sideband lanes and the mainband lanes.

A system and method for simultaneous compression and encryption of data. The system analyzes input data to determine its properties and creates a transformation matrix based on these properties. Using this matrix, the input data is transformed into a modified distribution, generating a main data stream of transformed data and a secondary stream of transformation information. The main data stream is compressed, and both streams are combined into a single output. The system implements security measures to protect against various attacks, including side-channel vulnerabilities. By using a dyadic distribution algorithm, the system achieves both compression and encryption in a single pass over the data, offering significant efficiency gains. The system can operate in both lossless and lossy modes, providing flexibility for different application requirements. This approach offers a unique solution for data transmission and storage scenarios where both data reduction and security are critical concerns.

Length-adapter input parameters for length-adaptive encoding include a data word length and a length-adapted codeword length, which are positive integers. Length-adapter output parameters include a primary data word length, a secondary data word length, a primary codeword length, and a secondary codeword length. A received data word is split according to splitter parameters into a primary data word based on the primary data word length and a secondary data word based on the secondary data word length. The primary data word is encoded in accordance with primary encoder parameters to generate a primary codeword from a primary code. The secondary data word is encoded in accordance with secondary encoder parameters to generate a secondary codeword from a secondary code. The primary and secondary codewords are combined in accordance with combiner parameters to generate a length-adapted codeword transmitted via a channel to a decoder.

A system and method are provided for implementing a network component, such as a software-defined wide area network, a firewall, a router, or a load balancer. The network component can be an embedded network edge device that is implemented, e.g., in software, in circuitry, or using hardware acceleration (e.g., a data processing unit (DPU), a smart network interface card (SmartNIC), etc.). The system can include multiple dataplanes, including a primary dataplane and a shadow dataplane. A packet dispatcher relays received data packets to a primary dataplane and the shadow dataplane. The primary dataplane applies a current version of the network component to data packets, and the secondary dataplane applies a new version of the network component to identical replicas of the data packets. A control plane agent compares performance data gathered from the respective dataplanes to perform verification testing on the new version of the network component.

The invention discloses a cross-border e-commerce service data management method, and relates to the technical field of service data management, and the method comprises the steps: obtaining commodity service data from a plurality of overseas e-commerce platforms, and caching the commodity service data to an edge data pool according to the attributes of a data source; based on source attributes, updating time and historical accuracy of the data sources and supervision rating of judicial jurisdictions, comprehensive credible weight values of the data sources are calculated, and main data channels are screened out according to the weight values; inputting commodity service data in the main data channel into a multi-language semantic encoder, generating semantic vectors, calculating cross-language semantic alignment, and comparing logic consistency of key structured fields; generating a consistency score according to a comparison result of the semantic alignment degree and the structured field, when the score is lower than a preset threshold value, marking as abnormal and entering a rechecking process, and otherwise, entering a compliance review stage; and calling the regional compliance rule base to carry out regulation matching on the data passing the consistency verification.

Technologies are described for correcting data, such as master data, in an unsupervised manner using supervised machine learning. Correction of master data can involve receiving a table containing unlabeled master data. Machine learning models are applied to the fields of one or more columns of the table to predict values of the fields, and the machine learning models use unsupervised learning. For example, a machine learning model can be applied to a particular field of a particular column to predict the value of the particular field. The machine learning model uses the fields of other columns as features. Results of applying the machine learning models include indications of recommended values, indications of probabilities of the recommended values, and indications of which original values do not match their respective recommended values. The results can be used to perform manual and / or automatic correction of the master data.