DATA SYSTEMS CONSULTING CO., LTD.

Disclosed are a data encapsulation device and a data encapsulation method. The data encapsulation device includes a storage device and a processor. The storage device is configured to store multiple modules. The processor is coupled to the storage device and is configured to execute multiple modules. A model building module obtains a corresponding encapsulated data and a compiler based on a dataset. A knowledge assembly module receives the encapsulated data to generate component data and associated data based on the encapsulated data. The knowledge assembly module assembles multiple component data into a component dataset based on a combination command. A compilation module executes a data compilation process through the corresponding compiler to generate executable data based on the component dataset.

A version updating system and a version updating method are provided. The version updating system includes a cloud server configured to execute a version updating tool, a version matching component, and a heterogeneous system management module that communicates with a heterogeneous system and a sub-business system. When the cloud server receives a version updating request for a cloud application, the version updating tool executes and prompts the version matching component to obtain version information of the heterogeneous system through the heterogeneous system management module. When the version information fails to meet version requirements, the version matching component records that the version information does not meet the version requirements and transmits a version updating notification to the sub-business system. After the sub-business system halts operation based on the version updating notification, the version matching component notifies the version updating tool of performing a version updating operation for the cloud application.

A display interface control system and a display interface control method are provided. The display interface control system includes a first server, a second server and a database. The first server communicates with a terminal device, and is configured to receive interface configuration information sent by the terminal device. The second server communicates with the first server and is configured to receive the interface configuration information. The second server generates a data request to the database according to the interface configuration information, and the database returns corresponding keyword data to the first server according to the data request. The first server constructs interface display data according to the keyword data, and provides the interface display data to the terminal device, so that a browser of the terminal device renders and displays a corresponding page according to the interface display data.

A data fusion system and a data fusion method that may effectively reduce redundancy and complexity after data amplification. The data fusion system includes a storage device and a processor. The storage device is configured to store a feature extraction module, a model building module, a model disassembly module and a data fusion module. The processor is electrically connected to the storage device. The processor is configured to execute the feature extraction module, the model building module, the model disassembly module and the data fusion module, and is configured to receive multiple form data. The feature extraction module extracts multiple feature data from the form data. The model building module performs a preprocessing operation on the feature data, and builds a prediction model. The model disassembly module disassembles the prediction model into multiple triples data. The data fusion module fuses the triples data into knowledge graph data.

An inventory optimization device and an inventory optimization method are provided. The inventory optimization device includes a memory and a processor. The processor executes a plurality of modules in the memory such that the plurality of modules execute genetic programming according to business data from an enterprise database to generate an objective function. The plurality of modules calculate the objective function according to an adjustment instruction from an electronic device to generate a fitness function. The plurality of modules execute a genetic algorithm according to the fitness function to generate a recommendation result, so that the electronic device manages the enterprise database according to the recommendation result, so as to improve operation efficiency of managing inventory.

The disclosure provides a large object processing system and large object processing method thereof. The large object processing system includes a storage device and a processor. The storage device stores a plurality of large object variable forms, a PV processing module, and a large object processing module. The PV processing module receives a request for processing and further searches for a storage device according to the request to obtain a PV form and a plurality of object values in the PV form. The large object processing module determines whether the plurality of object values include object-referencing character strings. Should the plurality of object values include the object-referencing character strings, the large object processing module obtains corresponding large object data according to the object-referencing character strings. The PV processing module replaces the object-referencing character strings in the PV form with the large object data and organizes the PV form.

A data processing system and a data processing method are provided. The data processing system includes a processor and a storage device. The storage device stores a data processing module, a feature processing module and a classification conversion module. The processor is electrically connected to the storage device, and executes the data processing module, the feature processing module and the classification conversion module. The data processing module generates summary data according to multiple form data. The data processing module performs feature index calculation on the summary data to generate feature index data. The data processing module preprocesses the feature index data to generate a sample label data set. The feature processing module generates a training data set based on the sample label data set. The classification conversion module builds a classification model based on the training data set, and builds a structured semantic knowledge base based on the classification model.

The disclosure provides a data simulation system and a data simulation method. The data simulation system includes an execution engine and a database. The execution engine includes a type matcher, an executor, and an analyzer. The type matcher receives a simulation command and generates a simulation logic group according to a simulation type in the simulation command. The executor executes simulation processing on data according to the simulation logic group to generate a simulation result. The analyzer determines a matching degree between the simulation result and a preset result according to the simulation type. When the matching degree is less than a threshold value, the analyzer adjusts the simulation logic group and commands the executor to execute the simulation processing repeatedly. When the matching degree is greater than the threshold value, the analyzer stores the simulation logic group.

A data-driven data management system and data management method are provided. The data-driven data management system includes a storage device and a processor. The storage device is configured to store multiple process models. The processor is coupled to the storage device and configured to receive a setting data set. The processor performs a second compilation on the multiple assembly data sets to combine the multiple assembly data sets into multiple process data sets. The data-driven data management system and data management method of the disclosure are adapted to automatically perform two compilations on the setting data set according to the multiple process models, and then combine assembly data corresponding to the setting data set into the multiple process data sets.

A data flow management system and a data flow management method are provided. The data flow management system includes a memory and a processor electrically connected to the memory and executing a data flow. The processor executes task nodes in the data flow, generates output data, and determines whether a data state of the output data reaches a target data state to decide whether to acquire a next task node in the data flow. When the processor determines the data state of the output data does not reach the target data state, the processor acquires the next task node and decides to execute the next task node in a data branching mode or a data shunting mode according to a data feature set and a branch identifier. When the processor determines the data state of the output data reaches the target data state, the processor ends the data flow.