14 results about "Physical data model" patented technology

Adaptable data warehousing computing systems and methods are disclosed for improved and flexible declarative control for programmatic modeling and database building, including in compute intense environments. A declarative scripting engine executes computing commands defined in a domain specific language (DSL), which is configured to programmatically configure a conceptual data model defining business object(s). A logical data model may be generated based on a declarative command defining the conceptual data model. A physical data model may be generated based on the logical data model, where the physical data model defines stage, core layer, and / or a data mart layers that may be deployed to a target database or data warehouse, and where the stage, core layer, and / or a data mart layers are the same or similar to those of the logical data model.

Adaptable data warehousing computing systems and methods are disclosed for improved and flexible declarative control for programmatic modeling and database building, including in compute intense environments. A declarative scripting engine executes computing commands defined in a domain specific language (DSL), which is configured to programmatically configure a conceptual data model defining business object(s). A logical data model may be generated based on a declarative command defining the conceptual data model. A physical data model may be generated based on the logical data model, where the physical data model defines stage, core layer, and / or a data mart layers that may be deployed to a target database or data warehouse, and where the stage, core layer, and / or a data mart layers are the same or similar to those of the logical data model.

The invention provides a data reporting method and system based on model configuration, electronic equipment and a storage medium, and relates to the field of computer software, and the method comprises the steps: configuring a physical data model, a quality control rule model and a value domain coding model based on a data reporting requirement; extracting original data, and mapping, converting and integrating the original data as required through a physical data model to generate an intermediate data set; verifying the intermediate data set through a quality control rule model and a value domain coding model, and generating a quality control result report according to a verification result; storing the verified intermediate data set and the quality control result report into a service database; processing the intermediate data set based on the quality control result report to generate a final data set; and based on the final data set, generating a file meeting the requirement and reporting the file. According to the method, configuration and closed loop of the data reporting process are realized in a model configuration mode, the data quality and the reporting efficiency are improved, and the practicability is relatively high.

The invention relates to a method for collecting industrial data within a plant (100), which includes an industrial device that executes a process within a station (ST01, ST02) included in an operation (OP600; OP630). According to the invention, the method comprises the following steps: - instantiating a physical data model on a local server (120), the model having a hierarchical structure with a first class, a second class and a third class, respectively, comprising variables related to the process, the station and the operation, respectively, the first class being dependent on the second class, which in turn is dependent on the third class, each variable having a type and a physical address for allocating a value of the variable to the industrial device, the station, or the operation, the variables originating from a database of the variables; - collecting the data according to the data model, for each variable, the local server being connected to the physical address of the variable in order to record its value; - storing the data on a remote server (140).

The invention discloses a data modeling method and device for demand modeling in software development, equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring enterprise-level business data; dividing and establishing an enterprise subject domain model based on the business domain; for each subject domain model, forming an enterprise concept data model; mapping the business concepts into business entities, defining entity relationships among the business entities, and determining attributes and attribute domains for the business entities; dividing the plurality of attribute domains into an attribute domain group, and determining an attribute domain instance for the attribute domain belonging to the code class; forming an enterprise logic data model based on the business entity, the entity relationship, the attribute and the attribute domain; generating an application physical data model based on the enterprise logic data model; wherein the enterprise concept data model is visually presented to business personnel in the form of a classification hierarchy graph; and presenting the enterprise logic data model to technicians in the form of an entity relation graph. The data quality of an enterprise is improved.

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 application provides a kind of data sharing method and system based on embedded rule, extracts entity under each subject domain and the association between entities, constructs entity relationship model, and embeds data constraint rules in entity relationship model, maps entity relationship model into physical data model, after extracting the business data required by customer, the rules embedded in physical data model can be directly called to check data. Based on the traditional mode, the business rules are scattered in the application code, database trigger or artificial experience, it is difficult to extract and reuse. Through systematic analysis, the core business rules (verified by pilot) are coded into the entity relationship model, and the data is issued together. After receiving, customers can directly call these preset rules for data verification, without starting from scratch to build a verification system, significantly reducing implementation costs.

The present invention discloses a tunnel grouting simulation method and system based on a conditional generative adversarial network, belonging to the field of geotechnical engineering technology. The method comprises the following steps: obtaining working condition information of the tunnel area to be grouted, using the working condition information as conditional variables of a conditional generative adversarial network, inputting random noise and the conditional variables into a generator, generating grouting simulation data suitable for the complexity of the current working condition, and constructing a grouting simulation dataset; gridding the area to be grouted, and constructing a physical mathematical model of the entire grouting process based on discretized continuity equations and momentum equations based on the grouting simulation dataset, and setting boundary conditions and initial conditions for each grid area; based on the constructed physical data model, predicting the grouting pressure, grouting velocity, and slurry diffusion morphology at the next time based on the current working condition information, and continuously updating the model to complete the simulation of the tunnel grouting process. The present invention can achieve accurate simulation of the tunnel grouting process.

Various methods and processes, apparatuses or systems, and media for decommissioning of applications, related components, and data are disclosed. The method includes: receiving first information that relates to an application for decommissioning; retrieving second information that relates to components and data sources associated with the application; obtaining third information that relates to data usage associated with the application; identifying an alternate data source associated with a target platform; constructing a physical data model in the alternate data source; migrating a predetermined set of data associated with the application to the alternate data source; obtaining a confirmation for a decommissioning of the application and for an archival of legacy data; performing a lockdown operation and a physical decommissioning of the application, the components, and the data sources; and performing a validation that all traces of the application, the components, and the data sources have been removed as a result thereof.

The invention discloses a method and a system for performing natural language question answering directly according to dimension values. The method comprises the following steps: selecting a corresponding data view according to a subject domain of a user question in a natural language form proposed by a user; performing data replacement on the content of the user question based on data replacement configuration in the data view, and replacing the content of the user question with a standard index or dimension; based on the standard index or dimension, converting a user question into an SQL logical expression through a large model; translating the SQL logical expression into an SQL statement based on configuration information of a semantic model; and executing the SQL statement based on a physical data model, and returning a query result of the SQL statement. According to the invention, the user can use the natural language to carry out interactive dialogue analysis, and the working efficiency and the use experience of the user are improved.

The present application discloses a data difference comparison method, device, equipment and medium, which relates to the field of data comparison technology. The method includes obtaining a number of business metadata; standardizing the business metadata to obtain standardized metadata; wherein the standardized metadata includes standard Chinese name data, standard English name data, standard data type data, standard data length data and standard data decimal point data; constructing a physical data model based on business form data and the standardized metadata; structuring the data in the several entity tables in the physical data model to obtain a structured physical data model; and performing a difference comparison with the data in the actual database based on the structured physical data model. Through the above technical solution, a basis can be provided for the governance of data models, thereby making it easier to carry out data governance work.

The present application discloses an entity class file update system, method, and corresponding computer equipment and storage medium, wherein the system is used to parse a physical data model (PDM) file and an entity class file respectively, compare the parsing results of the physical data model (PDM) file and the parsing results of the entity class file, and determine a new field in the physical data model (PDM) file based on the comparison results, generate the attribute name of the new field according to the entity class attribute naming rule in a first rule file, generate the attribute data type of the new field according to a second rule file, generate a section of JAVA code based on the field name of the new field and the generated attribute name and attribute data type according to a preset template, and insert the generated JAVA code into the entity class file and save it to update the entity class file. The present invention can realize the automatic update of the entity class file based on the physical data model file, greatly reduce the chance of error, and greatly improve the efficiency of code development.

The invention relates to a concrete service life prediction method based on surface monitoring and a physical-data model, and the method achieves the correlation of an external environment dynamic state and an internal ion transport mechanism through a machine learning model, and enables environment time sequence data which is collected through a non-invasive surface sensor and is easy to obtain to be transmitted to the internal ion transport mechanism. The real-time correction values are intelligently converted into real-time correction values of target chloride ion transportation key parameters which are difficult to measure and dynamically change in a chloride ion diffusion physical model, so that the physical model is driven to carry out high-fidelity life prediction. According to the method, high-precision, lossless and dynamic prediction of the service life of the concrete structure is realized through a collaborative mechanism with a physical model as a framework and machine learning as an engine, and the method has both physical interpretability and intelligence and has important engineering application value.