183 results about "Business intelligence" patented technology

The invention relates to the cross technical field of business intelligence and natural language processing, in particular to an interactive AI report generation method and system based on intelligent semantic driving, and the method comprises the steps: (1) a large language model analyzes user question semantics, calculates the matching degree with a report subject, and dynamically selects a question correction or report generation process; (2) the fuzzy query is converted into a deterministic request based on the domain knowledge base, and semantic ambiguity is eliminated; (3) analyzing field association in combination with database metadata, and generating an executable SQL (Structured Query Language); (4) dynamically rewriting SQL (Structured Query Language) according to user roles, adding permission filtering conditions, executing query and desensitizing sensitive data; (5) analyzing result features, automatically matching a visual form and generating natural language interpretation; and (6) collecting user feedback, and optimizing a semantic model and a query strategy. According to the scheme, the accuracy of natural language query and the adaptive capacity of the system can be remarkably improved, and the security of data access is guaranteed.

The invention provides an implementation method, system and equipment of a commercial intelligent system based on a large model ReAct, and belongs to the technical field of artificial intelligence. The method is applied to a ChatBI platform. Comprising the steps that a main agent receives query request information from a user terminal and guides an LLM to conduct cyclic reasoning on the query request information according to a preset ReAct normal form through a preset Prompt project, and the cyclic reasoning process comprises the steps that 1, input information from an upstream task is analyzed through the LLM, and a to-be-executed action corresponding to a downstream task is determined; step 2, according to each action task corresponding to the action to be executed and the action task type thereof, executing a reasoning action; 3, receiving an inference action feedback result, updating a loop inference context, and determining whether to trigger a next round of loop inference or not until a preset loop termination condition is met; and based on each decision analysis result obtained by loop reasoning, generating a query result and sending the query result to the user terminal.

The invention provides a knowledge graph construction method based on a low-code development platform, and belongs to the technical field of knowledge graph construction. The method comprises the following steps: counting and carding metadata and business entity structures in a low-code development platform, and formulating a mapping specification for mapping from a relational database to semantic data; obtaining a target relational database in the configuration file, extracting table data and column data in the target relational database, and converting the table data and the column data into entity class parameters and attribute class parameters in the knowledge graph based on a mapping specification; extracting an unstructured data source related to the target business from the low-code development platform, and converting the unstructured data source into structured data; and associating the structured data with the entity class parameters and the attribute class parameters, and storing the associated data in the knowledge graph. Automatic mapping and storage from the relational database to the knowledge graph are realized, so that the data utilization rate and the business intelligence level are improved.

A system (100) for adaptive data blending across heterogeneous BI platforms for real-time decision making, comprising: (a) a data source abstraction module configured to establish standardised and secure connections with several different Business Intelligence (BI) platforms and convert their native data structures into a unified intermediate schema; (b) a real-time data ingestion and synchronisation module operable to continuously monitor and retrieve data updates from the BI platforms using event-driven mechanisms and configurable synchronisation policies; c) an adaptive data mapping and transformation module designed to intelligently harmonize, adapt, and semantically translate disparate data formats using rule-based logic and AI-assisted schema mapping; (d) a semantic context and metadata management module configured to maintain a unified data dictionary, track data sequence and maintain semantic consistency across platforms; (e) a cross-platform query orchestration engine designed to decompose common user queries, translate them into platform-specific query languages, execute them across the relevant BI platforms, and aggregate the results into a coherent output; (f) a decision intelligence and recommendation module that analyses the mixed data to generate real-time insights, alerts and contextual recommendations for decision support; and (g) a security, governance and compliance module configured to enforce access controls, maintain audit trails and ensure compliance with data protection regulations; h) the system provides seamless, real-time and secure data blending to enable consistent analytics and decision-making across heterogeneous BI environments.

Systems and methods for managing a business intelligence database are described, for example, by receiving ETL event data associated with an execution of a set of tasks of the ETL process; processing the ETL event data to identify at least one of a resource and a first task limiting performance of the ETL process, wherein the resource is memory, storage, processor bandwidth, or network bandwidth; and automatically modifying the at least one of the resource and the first task to improve performance of the ETL process.

The invention relates to the technical field of medical data analysis and business intelligence, and discloses a hospital pharmacy competitiveness evaluation method and system based on multi-source data fusion, and the method comprises the following steps: collecting and processing multi-source data, and constructing a market entity feature vector; constructing an initial market causal atlas based on the feature vectors; initializing a digital twinning environment, and setting a dynamic behavior rule of a simulation entity; running simulation to obtain a reference competitiveness evolution trajectory; real data is periodically acquired to calculate simulation deviation; and if the deviation is greater than a preset threshold value, correcting the causal atlas and updating the simulation entity rule. The system comprises a data processing and feature construction module; a market causal relationship graph construction module; a market digital twin environment initialization module; a competitiveness evolution simulation module; a simulation reality deviation calculation module; and a causal atlas correction module. According to the method, the dynamic causal model is constructed by fusing multi-source data, so that accurate and prospective competitiveness evaluation is realized.

A system and method for combining data from disparate business intelligence systems and data sources. The method includes aggregating data in real-time across multiple, disparate data platforms of more than one third party, by mapping nonmatching data parameters used in the different platforms to a common data field. The business intelligence systems are queried to identify responsive data fields, which are then meshed in a translation and / or unification module into the common data field for display. The meshing of the data allows for efficient filtering according to user inputs. The system and method further include applications to allow users to create parameter mappings for the data meshing.

A system (100) for real-time monitoring of key performance indicators (KPIs) and automatic alarm generation using self-service business intelligence (BI) platforms, comprising: a) a data integration and aggregation module to connect and consolidate data from multiple sources, including internal databases, cloud services and external APIs; (b) a KPI definition and configuration module that allows users to define, configure and customize KPIs based on predefined or user-defined formulas, as well as to set thresholds and timeframes; c) a data processing and analysis module to analyze incoming data in real time and apply algorithms for KPI tracking, trend analysis and anomaly detection; d) a visualization and dashboard module to display KPIs and data insights through customizable visualizations such as graphs, charts, and gauges; (e) an alert and notification generation module for automatically generating and sending alerts to users when predefined thresholds are exceeded or anomalies are detected; f) a user management and access control module for the secure management of user roles and permissions, ensuring authorized access to system data and functions.

A system may include a directory-based identity-related services component that authenticates and authorizes enterprise users and computers in a network and enforces security policies. A business intelligence, application development, and application connectivity component may implement business workflow products and exchange application authentication data with the directory-based identity-related services component. A database storage component may provide document management and storage of dashboard tables and lists associated with inventory data received from the business intelligence, application development, and application connectivity component. A cloud-based storage and data management engine may exchange secure authentication storage data with the business intelligence, application development, and application connectivity component. At least one governance or user application may then automatically determine enterprise site inventory information, and, responsive to the determined enterprise site inventory information, automatically determine enterprise site membership information. The dashboard tables and lists may be exchanged in support of a graphical user display.

The invention discloses a dialogue type business intelligent analysis method based on a natural language, and relates to the technical field of business management systems, and the method mainly comprises the steps: recognizing the intention type of a user intention contained in a natural language request through a general large language model; according to the identified specific intention type, calling a corresponding special analysis module to perform semantic analysis and parameter extraction on the natural language request so as to generate an operable analysis instruction; calling a business intelligent system data interface to execute the analysis instruction, and obtaining corresponding structured data from a business intelligent system data warehouse; and generating a comprehensive analysis report which is matched with the identified intention type and the corresponding structured data and comprises visual elements and analysis explanations based on the identified intention type and the corresponding structured data. According to the method, the intention type of the natural language request of the user is understood through the large language model, so that the user with a non-professional background can easily perform complex data exploration, and the use threshold is reduced.

The invention provides a data processing method and system based on a business intelligence system. The method comprises the following steps: receiving request data, and standardizing the request data to obtain standardized data; analyzing the standardized data based on a pre-constructed dynamic semantic map to obtain an analysis result; the dynamic semantic graph is a directed attribute graph constructed based on business terms, data entities and business concepts; performing logic compiling on the analysis result to generate an executable operation chain; the executable operation chain comprises sequenced atomic operation steps, and the atomic operation steps comprise data processing logic and metadata binding information; and running the executable operation chain to obtain an analysis result corresponding to the request data. The method comprises the following steps: analyzing request data based on a dynamic semantic map; and the analysis result is logically compiled, an executable operation chain is generated, and the data processing process is decomposed into sequenced atomic operation steps, so that the data processing flow becomes clear, and the accuracy and efficiency of request data processing are improved.

A computing device and computer-implemented method to provide access to business intelligence data via a conversational interface is described. The method begins with receiving prior user interactions based on corresponding pairs of user queries and computing device responses, with the conversational interface. Received also is a business intelligence ontology and access to a conversational space structure for the conversational interface. The computing device executes a machine learning model based upon the prior user interactions, business intelligence ontology, and the conversational space structure to predict possible next queries. The possible next queries are sent to a user. In one example, the computing device receives a user query, which is in addition to the prior user interactions with the conversational interface. A response to the query is generated. The response to the query is sent to the user prior to sending the possible next queries, which have been predicted.

Implementations described herein relate to systems and methods to generate a response to a business intelligence question received from a user. In some implementations, a computer-implemented method may include receiving the question as a natural language string, determining one or more fragments based on the natural language string, identifying one or more query operators based on the one or more fragments, constructing a structured query tree based on the one or more query operators, executing at least a portion of the structured query tree on a data source, receiving, from the data source, an output result based on the execution, generating the response based on the output result, and providing the response to the user.

The invention relates to an AI-driven system for data analytics, processing, mining, and user interaction, utilizing large language models (LLMs) and machine learning (ML) techniques. The system enables personalized, real-time access to company data, guided by AI Agents. These Agents handle tasks such as data extraction, transformation, and loading, with a multi-stage processing pipeline that includes raw data ingestion, curation, and modeling. Specialized Agents like Fixing and Modeling Agents ensure data quality, analysis, and visualization. The system also integrates with BI dashboards for generating insights and predictive analytics. Users interact via natural language queries (NLQs) to receive context-aware, AI-generated answers, including various types of plots, graphs and charts, thus improving decision-making and data management efficiency.

Methods and system are disclosed to implement an interactive companion table alongside graphical data visualizations within a computing environment, aimed at enriching data analysis and interpretation. The underlying numerical data of the graphs are displayed through a specialized table and responses to user interactions between the graphs and the table are highly synchronized with the establishment of the bidirectional links between each graph and its corresponding cells in the table. The method encompasses several key procedures: initializing a table object, accessing graphs in the active data visualization, incorporating cell blocks to represent data elements of graphs, adding bidirectional links, refreshing the table display, and handling user interactions. The methods and system enhance the data analysis experience by closely integrating visual and numerical information and is especially useful in areas that demand an in-depth examination of data alongside a broad visualization, including financial analysis, scientific research, and business intelligence.

The invention relates to the technical field of data processing, can be applied to the fields of medical treatment and finance, and discloses a data query method, device and equipment based on a large language model and a medium, a natural language query request is rapidly analyzed through the large language model and converted into executable query key information, the query request understanding precision is improved, and the query efficiency is improved. And the query result accuracy is improved. High-correlation target data is screened out from a multi-modal fusion database fusing various types of data through a business intelligence BI tool, data of different sources and types are integrated, and the accuracy and integrity of a query result are ensured. The target data obtained through query is converted into a visual chart form through a chart data mapping model, so that the complex data relation and trend are clear, the decision support effect of the multi-modal data in the fields of financial risk assessment, medical diagnosis analysis and the like is fully played, a user can quickly understand a data analysis result, and the user experience is improved. Therefore, decisions based on the multi-modal data can be made more efficiently.

In accordance with an embodiment, described herein is a system and method for providing query acceleration with a computing environment such as, for example, a business intelligence environment, database, data warehouse, or other type of environment that supports data analytics. A middle layer is provided as a long-term table data storage format; and one more acceleration formats, or acceleration tables, can be periodically regenerated from the middle layer, wherein a determination can be made as to whether an accelerated table exists for a dataset table, and if so, then the accelerated table is used to process the query.

The invention relates to the technical field of data processing, in particular to a report generation method and device based on a business intelligence BI tool and electronic equipment, and is used for solving the problems that a traditional BI tool is high in use threshold, tedious in process and low in data processing efficiency. The method comprises the following steps: in response to a query request based on a natural language, performing semantic analysis on the query request by utilizing a pre-deployed language large model, and generating a structured query instruction corresponding to the query request; generating a target query statement based on the language large model and the structured query instruction; loading a target data source based on the target query statement, and executing the target query statement based on the loaded target data source to generate a data query result; analyzing the data query result by utilizing a language large model, and determining a first report generation strategy; and based on the first report generation strategy, generating the first report and performing visual display, so that the use threshold of the user can be reduced, the process can be optimized, and the data processing efficiency can be improved.

The invention aims to provide an intelligent data analysis multi-round reasoning method. The method comprises the following steps: receiving natural language query request data; performing entity recognition and intention recognition on the natural language query request data; performing complexity quantitative analysis on the natural language query request data by adopting complexity measurement evaluation to obtain a complexity evaluation result; constructing five types of Agents to carry out collaborative reasoning; a standardized cooperation interface and a data transmission protocol among the Agents are established; the accuracy and the reliability of a preliminary reasoning result are ensured through a cooperative conflict resolution mechanism; and sorting any preliminary retrieval result according to the evaluation data, and outputting a final retrieval result. According to the invention, intelligent processing of complex BI data analysis tasks is realized, and an efficient, reliable and intelligent technical solution is provided for enterprise data analysis and business intelligent application.

The invention provides an automatic process management method and system applied to foreign trade business intellectualization, and relates to the technical field of foreign trade business management.The method comprises the steps that firstly, initial order data, preset document template data, logistics resource configuration data and order change data of foreign trade business are obtained and integrated to form a foreign trade business total data set; then, carrying out change influence definition processing on the order change data, and determining influenced foreign trade business links and associated data; performing linkage adaptation processing on the associated data based on a defining result, and adjusting preset document template data and logistics resource configuration data; according to a linkage adaptation processing result and a foreign trade business process knowledge base, generating operation execution instructions of all links; finally, the instructions are distributed to the corresponding execution main bodies according to the execution sequence, operation execution results are received and integrated to form feedback information, automatic and intelligent management of the foreign trade business process is achieved, and the management efficiency and accuracy are improved.

The invention provides an intelligent engine collaboration method and system oriented to multi-modal query, and relates to the technical field of data collaboration process.The method comprises the steps that query dimension analysis is conducted according to a received multi-modal query request, a query analysis result is generated, tasks are dynamically distributed to matched engines based on the analysis result, and the tasks are distributed to the matched engines. All the engines execute processing operation in parallel or in a serialization mode, multi-source data association fusion is conducted on heterogeneous engine results, and fusion results are packaged into visual data to be fed back to a user; the system comprises a query dimension analysis module, an engine task distribution module, an engine execution module, a multi-source data association fusion module and a result visualization packaging module. According to the method, the multi-modal query fingerprint database and the graph structure collaborative network are constructed, and the pre-training graph convolutional network is combined to optimize the control parameters, so that the query performance is remarkably improved, the query delay is reduced, the accuracy is improved, and the method is suitable for complex scenes such as smart cities and business intelligence.

A system and method for generating an improved user interface for data analytics is provided. A first type of data analytics action is performed based on a user request. Data insights are fetched based on the first type of data analytics action for rendering one or more data assets as one or more result sets. Further, a sharing functionality is provided for sharing the one or more data assets for multiple access. Lastly, data assets are rendered in the form of one or more visualization types associated with different Business Intelligence (BI) tools based on a pre-defined set of rules. The rendered multiple data assets are combined based on a second type of data analytics action for configuring and rendering dashboard.

The invention belongs to the technical field of artificial intelligence, and provides a dialogue type business intelligent platform process optimization method, system and equipment in order to solve the problems of random errors, result adaptability defects and the like existing in a ChatBI process, and output results of all links in the dialogue type business intelligent platform process are obtained. Multi-dimensional verification is carried out on output results of all links in sequence according to the process execution sequence, the process links which possibly have problems can be found in time, and correction and optimization are carried out in time before errors are diffused to the next process link; and the output result is verified from three aspects of adapting to the original demand of the user input problem, conforming to the business logic of the process link and adapting to the use demand of the downstream process link, so that the suitability of the result is ensured, and the problems that each process link has no obvious error, but the output of the process link is disjointed from the downstream process link are avoided.

The application belongs to the technical field of business intelligence evaluation, and specifically provides a service provider SLA evaluation dynamic business model implementation method and system. The method mainly comprises: obtaining SLA evaluation source data of a service provider, wherein the SLA evaluation source data comprises operator SLA data, enterprise end-to-end APM data, third-party network quality data and dependent link probe data between service providers; taking the service provider as a node, setting a credibility weight for each node according to a preset rule, determining a directed edge between nodes according to a preset dependent relationship between service providers, and determining a connection weight of the directed edge according to the dependent link probe data. The application realizes dynamic and accurate evaluation under multi-dimensional data fusion, improves the objectivity and credibility of SLA achievement rate evaluation results, and provides reliable decision support for enterprise screening of cloud service providers and optimization of service deployment.

The invention belongs to the technical field of self-media operation and business decision, and particularly relates to a self-media account business intelligent quotation method and system, and the method comprises the following specific steps: S1, collecting self-media account basic data, user portrait data, commercial value data and market dynamic data; s2, encrypting and storing the sensitive data through AES-256; s3, adopting a random forest algorithm to construct a basic quotation model, and combining account operation fluctuation and market nodes to realize dynamic adjustment; s4, displaying quotation composition details to the account party and supporting parameter adjustment preview; and S5, generating a multi-format personalized quotation list, and negotiating and recording full-link data based on the quotation and the cooperation effect. According to the method and the system, through integrating the self-media account basic data, the user portrait data, the commercial value data and the market dynamic data, the key information influencing the quotation is covered in multiple dimensions, the quotation association factors are comprehensively considered, the deviation caused by single data limitation is reduced, and the quotation accuracy is improved.

Comprehensive systems and methods manage software lifecycle processes in an enterprise environment, and ensures consistent, secure, and efficient handling of software applications, packages, and distribution methods. The system features a web application interface that validates user input, enforces multi-level authentication, and manages user roles and permissions. A directory system dynamically selects stored procedures based on input data and current database structure, executing operations entirely within the database. Stored procedures enforce business logic, manage complex data relationships, support data encryption, and anonymize sensitive information. Hierarchical data structures organize records with multi-level granularity, temporal tracking, and partitioning. The database management system optimizes operations, implements automatic failover, and supports real-time data synchronization. The system also includes advanced error handling, real-time monitoring with predictive alerts, a secure audit trail, and a reporting module integrating with external business intelligence tools. Automated maintenance and disaster recovery ensure scalable, secure software lifecycle management.

The invention relates to the technical field of natural language processing, and provides an ASR and NLP technology-based intelligent voice system for purchasing, which comprises an integrated application layer, a voice service layer and a data storage layer, the integrated application layer comprises an external APP, an internal purchasing subsystem and a voice assistant; the voice service layer comprises an intelligent voice model integrating an ASR voice recognition model and a UIE information extraction model; the data storage layer comprises a database component and a knowledge graph and is used for data storage and information query; the voice service layer is connected through the integrated application layer, voice data are input, an intelligent voice model of the voice service layer carries out semantic understanding on voice, and result information is output by querying the data storage layer. The intelligent voice technology and natural language processing (intelligent questions and answers) can be applied to internal purchase management and external client communication, internal company and client service voices are effectively utilized, and the improvement of operation intelligence and the improvement of service level are facilitated.

The invention discloses an intelligent service adaptation method based on a canal, and relates to the technical field of digital information transmission. The method comprises the following steps: step 1, configuring and filtering a data source to ensure that a Canal can be accurately connected with and monitor a binlog of a source database, and screening related data according to service requirements to reduce unnecessary data transmission; 2, data analysis and processing: converting data in a binlog into a format which can be identified by a system, and filtering and assembling the data according to a service rule so as to construct an SQL (Structured Query Language) statement and a cache Key which are required by the service, and 3, data synchronization and recording: pushing the processed data to a downstream system through multiple protocols, recording a synchronization result, and sending the synchronization result to the system. Therefore, the synchronization process can be monitored and backtracked. The method has remarkable advantages in the aspects of solving the service synchronization problem, guaranteeing the service stability, reducing the enterprise cost and realizing efficient synchronization of the system, and is an important support for realizing high-quality, high-availability and high-stability services for enterprises.

Embodiments described herein are generally related to computer data analytics, and computer-based methods of providing business intelligence data, and are particularly related to systems and methods for use with enterprise data for profile matching and generating gap scores and upskilling recommendations. In accordance with an embodiment, the system can operate to match a set of position requirements with candidate attributes or skillsets, ranking them on the basis of match scores. The system can be used, for example, to determine a skill gap between the position requirements and candidate attributes, and recommend which skills might be augmented to better address the position requirements.

The invention discloses an enterprise business intelligent aid decision-making method, device and equipment based on a multi-source large language model and a storage medium, relates to the field of artificial intelligence, is applied to terminal equipment carrying a target intelligent aid decision-making system, and comprises the following steps: obtaining a to-be-decided task related to a target enterprise business to determine target label data; obtaining corresponding target portrait data from a target business portrait database of the corresponding dimension based on the target label data by using the target business knowledge database to generate a corresponding structured parameter packet; based on a task type corresponding to the task to be decided and a pre-acquired target mapping table, determining a target large language model corresponding to the task type; and utilizing the target large language model to generate an intelligent auxiliary decision related to the target enterprise business based on the structured parameter packet and the target cue word template, so as to complete the target enterprise business based on the intelligent auxiliary decision. According to the invention, different large models can be called according to business requirements.