A multi-branch enterprise digital base and data integration method and system

Abstract

The present invention discloses a digital base for multi-branch enterprises and a data pulling method and system, which relate to the field of distributed ledger technology. Specifically disclosed is a digital base for multi-branch enterprises and a data pulling method, which adopts blockchain technology to build a decentralized data storage and transmission network of multiple branch nodes of an enterprise, integrates smart contracts in the blockchain network; uses asymmetric encryption algorithms to encrypt data end-to-end, and authenticates the data through digital signatures; designs the smart contracts according to business rules to automatically execute data exchange and business processes of each branch node; updates the data of each branch node of the blockchain network in real time through a data synchronization algorithm; conducts in-depth analysis of the updated data of each branch node, and optimizes the production cost of each branch node. The present invention realizes the real-time sharing, synchronization and analysis of data between branches, ensuring data authenticity, security and processing efficiency.

Description

Technical Field

[0001] The present invention relates to the field of distributed ledger technology, and in particular to a multi-branch enterprise digital base and data integration method and system. Background Art

[0002] The main challenge currently facing enterprises undergoing digital transformation is how to efficiently and securely share and synchronize data across multiple branches. Existing technologies, such as centralized databases, can process data, but they suffer from single points of failure, poor data security, and limited scalability. Distributed ledger technologies, such as blockchain, are becoming a leading approach to addressing this issue due to their immutable and decentralized nature. However, applying this technology within an enterprise, particularly in a multi-branch structure, still requires overcoming major challenges such as algorithmic complexity, system compatibility, and real-time performance optimization. Currently, there is a need to design a multi-branch enterprise digital foundation and data integration method that can achieve real-time sharing, synchronization, and analysis of data across branches, ensuring data authenticity, security, and processing efficiency, and supporting comprehensive data analysis and decision-making within the enterprise, thereby promoting the enterprise's digital transformation. Summary of the Invention

[0003] The technical problem to be solved by the present invention is how to realize real-time sharing, synchronization and analysis of data among branches, ensure data authenticity, security and processing efficiency, and support comprehensive data analysis and decision-making of enterprises, thereby promoting the digital transformation of enterprises. The purpose is to provide a digital base and data integration method for multi-branch enterprises to solve the above technical problems.

[0004] The present invention is achieved through the following technical solutions:

[0005] A multi-branch enterprise digital base and data integration method, comprising:

[0006] Using blockchain technology, we build a decentralized data storage and transmission network across multiple branch nodes of an enterprise;

[0007] Utilize asymmetric encryption algorithms to encrypt data end-to-end and authenticate with digital signatures;

[0008] Design smart contracts based on business rules to automate data exchange and business processes among branch nodes;

[0009] Update the node data of each branch of the blockchain network in real time through data synchronization algorithm;

[0010] Integrate advanced data analysis tools to conduct in-depth analysis of the updated branch node data and optimize the production branch costs of each branch node.

[0011] The above uses blockchain technology to build a decentralized data storage and transmission network for multiple branch nodes of the enterprise, including:

[0012] Deploy independent blockchain nodes in each branch, and connect the nodes through encrypted communication protocols to form a peer-to-peer network structure;

[0013] Design the data block structure for data storage;

[0014] Use a consensus algorithm suitable for the internal environment of the enterprise to process the node data of each branch;

[0015] Integrate smart contracts in the blockchain network to define and execute data exchange rules and business logic.

[0016] The above consensus algorithm suitable for the internal environment of the enterprise is used to process the node data of each branch, including:

[0017] When communication needs to be established between the source node and the target node, the source node searches for a first node that is closer to the target node based on the address information of the target node, and then sends a search request to it; the source node receives information about a second node that is closer to the target from the first node. If the second node is not the target, the source node continues the search process until it finds the target node.

[0018] The above uses asymmetric encryption algorithms to encrypt data end-to-end, including:

[0019] Each branch node generates its own public and private key pair when joining the blockchain network;

[0020] When data is sent between nodes in each branch, the node sending the data encrypts the data using the public key of the node receiving the data; the encrypted data is decrypted using the private key of the node receiving the data.

[0021] The smart contracts mentioned above are designed based on business rules to automate the data exchange and business processes of each branch node, including:

[0022] Extract and model the data exchange and business processes of each branch node based on the enterprise business process;

[0023] Write and test smart contracts based on the extracted data exchange and business processes of each branch node:

[0024] Deploy and monitor smart contracts.

[0025] The above extracts and models the data exchange and business processes of each branch node based on the enterprise business process, including:

[0026] Obtain the maximum duration and minimum duration of each intermediate business process between two target business processes, and the process sequence of multiple intermediate business processes from the log file; use the two target business processes and their multiple intermediate business processes to build a process model in a choreography diagram modeling tool, embed the maximum duration, the minimum duration and the process sequence into the business process, and generate a timed choreography diagram in the BPMN format; parse the BPMN diagram into a JSON metamodel through a translator, and parse each sequence flow element, including start and end events, gateways, and activities with time constraints; obtain a message structure from the process model message set in combination with the activity, associate it with the activity information of the metamodel, and process the time constraints of the activities at the same time; export the metamodel in JSON format, which includes a list of responsible roles, model messages, elements, decisions, and time constraints.

[0027] The above data synchronization algorithm updates the node data of each branch of the blockchain network in real time, including:

[0028] Develop a data synchronization strategy for each branch node, including:

[0029] Set appropriate synchronization cycles for different types of data based on the frequency of data changes; and set high priority for real-time updates of critical business data;

[0030] Design synchronization algorithms based on synchronization strategies, including:

[0031] Use data versions based on timestamps; design a synchronization algorithm based on timestamps to determine whether data is updated;

[0032] Implement the synchronization process according to the synchronization algorithm, including:

[0033] Each branch node broadcasts its data version information through the blockchain network;

[0034] Compare the data versions between nodes of each branch to obtain data differences;

[0035] Transmit the difference data to the target node through a secure channel;

[0036] After the receiving node updates the data, it sends a confirmation message to the node that sent the data.

[0037] The above-mentioned integrated advanced data analysis tools conduct in-depth analysis of the updated branch node data to optimize the production branch costs of each branch node, including:

[0038] integrated data analysis tools;

[0039] Pre-process the updated transaction data of each branch node;

[0040] Extract key features of transaction data to build a transaction forecasting model for predicting sales trends in the next quarter;

[0041] Use historical data to train the transaction prediction model and evaluate its performance using a validation set;

[0042] Use the performance-optimized transaction prediction model to predict the sales trend of the next quarter for the transaction data to be tested;

[0043] Deploy production operations across multiple branches of an enterprise based on the predicted sales trends for the next quarter.

[0044] The above extraction of key features of transaction data to build a transaction prediction model for predicting sales trends in the next quarter includes: obtaining sales records and attribute features of products in different regions, analyzing changes in product sales quantities in different regions, and collecting key attribute features of multiple products based on sales volume changes in each region to train machine learning models in all regions to generate a transaction prediction model that predicts the sales volume of products in each region in the next quarter;

[0045] The above deployment of production operations in multiple branches of the enterprise based on the predicted sales trend of the next quarter includes:

[0046] Utilize the sales volume of goods in each region in the next quarter to optimize the production time, production volume, purchase time, purchase volume, transportation time and transportation volume of goods and raw materials at branch nodes in each region.

[0047] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0048] The present invention provides a multi-branch enterprise digital base and data pulling method, adopts blockchain technology to build a decentralized data storage and transmission network of multiple branch nodes of an enterprise; uses asymmetric encryption algorithm to encrypt data end-to-end and authenticates the identity through digital signatures; designs smart contracts according to business rules to automate the data exchange and business processes of each branch node; updates the data of each branch node of the blockchain network in real time through a data synchronization algorithm; integrates advanced data analysis tools to conduct in-depth analysis of the updated branch node data, and optimizes the production branch costs of each branch node. The present invention realizes real-time sharing, synchronization and analysis of data between branches through distributed ledger technology, ensures data authenticity, security and processing efficiency, and supports comprehensive data analysis and decision-making of enterprises, thereby promoting the digital transformation of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the examples. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. In the drawings:

[0050] Figure 1 This is a flow chart of the multi-branch enterprise digital base and data integration method according to an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0052] Example

[0053] like Figure 1 As shown, the embodiment of the present application provides a multi-branch enterprise digital base and data integration method, including:

[0054] Using blockchain technology, we build a decentralized data storage and transmission network across multiple branch nodes of an enterprise;

[0055] Utilize asymmetric encryption algorithms to encrypt data end-to-end and authenticate with digital signatures;

[0056] Design smart contracts based on business rules to automate data exchange and business processes among branch nodes;

[0057] Update the node data of each branch of the blockchain network in real time through data synchronization algorithm;

[0058] Integrate advanced data analysis tools to conduct in-depth analysis of the updated branch node data and optimize the production branch costs of each branch node.

[0059] The above uses blockchain technology to build a decentralized data storage and transmission network for multiple branch nodes of the enterprise, including:

[0060] Deploy independent blockchain nodes in each branch, and connect the nodes through encrypted communication protocols to form a peer-to-peer network structure;

[0061] Design the data block structure for data storage;

[0062] Use a consensus algorithm suitable for the internal environment of the enterprise to process the node data of each branch;

[0063] Integrate smart contracts in the blockchain network to define and execute data exchange rules and business logic.

[0064] The above consensus algorithm suitable for the internal environment of the enterprise is used to process the node data of each branch, including:

[0065] When communication needs to be established between the source node and the target node, the source node searches for a first node that is closer to the target node based on the address information of the target node, and then sends a search request to it; the source node receives information about a second node that is closer to the target from the first node. If the second node is not the target, the source node continues the search process until it finds the target node.

[0066] This recursive search strategy, using a peer-to-peer network node communication method, ensures that proxies are set up in the returned nodes for communication between the source and destination. These proxy nodes act as relay stations for communication. This method enhances the reliability of inter-node communication without changing the network security framework. Even if the link is partially blocked, it can ensure smooth data transmission and improve the security of network nodes.

[0067] The above uses asymmetric encryption algorithms to encrypt data end-to-end, including:

[0068] Each branch node generates its own public and private key pair when joining the blockchain network;

[0069] When data is sent between nodes in each branch, the node sending the data encrypts the data using the public key of the node receiving the data; the encrypted data is decrypted using the private key of the node receiving the data.

[0070] The smart contracts mentioned above are designed based on business rules to automate the data exchange and business processes of each branch node, including:

[0071] Extract and model the data exchange and business processes of each branch node based on the enterprise business process;

[0072] Write and test smart contracts based on the extracted data exchange and business processes of each branch node:

[0073] Deploy and monitor smart contracts.

[0074] The above extracts and models the data exchange and business processes of each branch node based on the enterprise business process, including:

[0075] Obtain the maximum duration and minimum duration of each intermediate business process between two target business processes, and the process sequence of multiple intermediate business processes from the log file; use the two target business processes and their multiple intermediate business processes to build a process model in a choreography diagram modeling tool, embed the maximum duration, the minimum duration and the process sequence into the business process, and generate a timed choreography diagram in the BPMN format; parse the BPMN diagram into a JSON metamodel through a translator, and parse each sequence flow element, including start and end events, gateways, and activities with time constraints; obtain a message structure from the process model message set in combination with the activity, associate it with the activity information of the metamodel, and process the time constraints of the activities at the same time; export the metamodel in JSON format, which includes a list of responsible roles, model messages, elements, decisions, and time constraints.

[0076] This blockchain business process management approach, driven by a timed orchestration graph, resolves cross-organizational trust issues, effectively controls processes that violate time constraints, and reduces blockchain gas consumption through smart contract reuse, facilitating version control and increasing decentralization. In practical applications, it enables enterprises to efficiently model and test smart contracts, monitor their deployments, and ensure smooth data exchange and business process execution across all branch nodes.

[0077] Through the parser, the BPMN diagram is converted into a JSON metamodel, detailing the time-constrained activities and message structures. Furthermore, the metamodel's activities are linked to the message structures to address activity time constraints, ensuring improved process efficiency and service quality. Finally, the exported JSON metamodel includes a complete list of roles, messages, elements, decisions, and time constraints, significantly reducing model redundancy and improving program efficiency.

[0078] The above-mentioned two target business processes and multiple intermediate business processes are used to construct a process model in a choreography diagram modeling tool. The maximum duration, minimum duration, and process sequence are embedded into the business process to generate a timed choreography diagram in BPMN format. This includes applying business process optimization mining methods to replay the processed log sequences one by one, and constructing, adjusting, and selecting models based on the maximum duration and minimum duration constraints. This method can effectively extract log sequences from program execution trajectories, integrate time constraint information into the business process, and generate a BPMN timed choreography diagram with a clear structure and reasonable behavior.

[0079] The above data synchronization algorithm updates the node data of each branch of the blockchain network in real time, including:

[0080] Develop a data synchronization strategy for each branch node, including:

[0081] Set appropriate synchronization cycles for different types of data based on the frequency of data changes; and set high priority for real-time updates of critical business data;

[0082] Design synchronization algorithms based on synchronization strategies, including:

[0083] Use data versions based on timestamps; design a synchronization algorithm based on timestamps to determine whether data is updated;

[0084] Implement the synchronization process according to the synchronization algorithm, including:

[0085] Each branch node broadcasts its data version information through the blockchain network;

[0086] Compare the data versions between nodes of each branch to obtain data differences;

[0087] Transmit the difference data to the target node through a secure channel;

[0088] After the receiving node updates the data, it sends a confirmation message to the node that sent the data.

[0089] The above-mentioned integrated advanced data analysis tools conduct in-depth analysis of the updated branch node data to optimize the production branch costs of each branch node, including:

[0090] integrated data analysis tools;

[0091] Pre-process the updated transaction data of each branch node;

[0092] Extract key features of transaction data to build a transaction forecasting model for predicting sales trends in the next quarter;

[0093] Use historical data to train the transaction prediction model and evaluate its performance using a validation set;

[0094] Use the performance-optimized transaction prediction model to predict the sales trend of the next quarter for the transaction data to be tested;

[0095] Deploy production operations across multiple branches of an enterprise based on the predicted sales trends for the next quarter.

[0096] The above extraction of key features of transaction data to build a transaction prediction model for predicting sales trends in the next quarter includes: obtaining sales records and attribute features of products in different regions, analyzing changes in product sales quantities in different regions, and collecting key attribute features of multiple products based on sales volume changes in each region to train machine learning models in all regions to generate a transaction prediction model that predicts the sales volume of products in each region in the next quarter;

[0097] The above deployment of production operations in multiple branches of the enterprise based on the predicted sales trend of the next quarter includes:

[0098] Utilize the sales volume of goods in each region in the next quarter to optimize the production time, production volume, purchase time, purchase volume, transportation time and transportation volume of goods and raw materials at branch nodes in each region.

[0099] This effectively improves processing efficiency, reduces the complexity of feature engineering, and helps automatically build high-quality predictive models, effectively enhancing the accuracy of model predictions. This allows companies to more accurately predict sales trends for the next quarter, enabling timely adjustments to strategies and business layouts. This allows accurate adjustments to production line schedules and inventory levels, reducing overproduction or undersupply, thereby minimizing inventory costs across the entire supply chain and improving resource allocation efficiency.

[0100] In summary, the embodiments of the present application provide a multi-branch enterprise digital base and data integration method and system:

[0101] Using blockchain technology, a decentralized data storage and transmission network for multiple branch nodes of an enterprise is constructed; using asymmetric encryption algorithms, data is end-to-end encrypted and authenticated through digital signatures; smart contracts are designed according to business rules to automate the data exchange and business processes of each branch node; the data of each branch node of the blockchain network is updated in real time through a data synchronization algorithm; advanced data analysis tools are integrated to conduct in-depth analysis of the updated data of each branch node, and optimize the production branch costs of each branch node. The present invention realizes real-time sharing, synchronization and analysis of data between branches through distributed ledger technology, ensures data authenticity, security and processing efficiency, and supports comprehensive data analysis and decision-making of enterprises, thereby promoting the digital transformation of enterprises.

[0102] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-branch enterprise digital base and data integration method, characterized in that: include: Using blockchain technology, we build a decentralized data storage and transmission network across multiple branches of an enterprise, integrating smart contracts into the blockchain network. Using asymmetric encryption algorithms, data is encrypted end-to-end and authenticated through digital signatures; The smart contract is designed according to business rules to automatically execute data exchange and business processes of each branch node, including: extracting and modeling the data exchange and business processes of each branch node according to the enterprise business process, specifically including: obtaining the maximum duration and minimum duration of each intermediate business process between two target business processes and the process sequence of multiple intermediate business processes from the log file; using the two target business processes and their multiple intermediate business processes to build a process model in a choreography modeling tool, embedding the maximum duration, the minimum duration and the process sequence into the business process, and generating a timed choreography diagram in BPMN format; parsing the timed choreography diagram into a JSON metamodel through a translator, parsing each sequence flow element, including start and end events, gateways, and activities with time constraints; exporting the JSON metamodel; writing a smart contract based on the extracted data exchange and business processes of each branch node; deploying and monitoring the smart contract; and updating the data of each branch node in the blockchain network in real time through a data synchronization algorithm; Conduct in-depth analysis on the updated node data of each branch office to optimize the production cost of each branch office node.

2. A multi-branch enterprise digital base and data pulling method according to claim 1, characterized in that: The blockchain technology is used to build a decentralized data storage and transmission network for multiple branch nodes of an enterprise, including: Deploy independent blockchain nodes in each branch, and connect the nodes through encrypted communication protocols to form a point-to-point network structure; A consensus algorithm is used to process the node data of each branch.

3. A multi-branch enterprise digital base and data pulling method according to claim 2, characterized in that: The consensus algorithm is used to process the node data of each branch, including: When communication needs to be established between the source node and the target node, the source node searches for a first node that is closer to the target node based on the address information of the target node, and then sends a search request to it; the source node receives information about a second node that is closer to the target from the first node. If the second node is not the target, the source node continues the search process until it finds the target node.

4. A multi-branch enterprise digital base and data pulling method according to claim 1, characterized in that: The end-to-end encryption of data using an asymmetric encryption algorithm includes: Each branch node generates its own public and private key pair when joining the blockchain network; When data is sent between nodes in each branch, the node sending the data encrypts the data using the public key of the node receiving the data; the encrypted data is decrypted using the private key of the node receiving the data.

5. A multi-branch enterprise digital base and data pulling method according to claim 1, characterized in that: The real-time updating of the node data of each branch of the blockchain network through the data synchronization algorithm includes: Develop a data synchronization strategy for each branch node, including: Set synchronization cycles for different types of data based on the frequency of data changes; and set a high priority for real-time updates of critical business data; Design synchronization algorithms based on synchronization strategies, including: Use data versions based on timestamps; design a synchronization algorithm based on timestamps to determine whether data is updated; Implement the synchronization process according to the synchronization algorithm, including: Each branch node broadcasts its data version information through the blockchain network; Compare the data versions between nodes of each branch to obtain data differences; Transmit the difference data to the target node through a secure channel; After the receiving node updates the data, it sends a confirmation message to the node that sent the data.

6. A multi-branch enterprise digital base and data pulling method according to claim 1, characterized in that: The in-depth analysis of the updated branch node data to optimize the production cost of each branch node includes: Pre-process the updated transaction data of each branch node; Extract key features of transaction data to build a transaction forecasting model for predicting sales trends in the next quarter; Using the transaction prediction model to predict the sales trend of the transaction data to be tested in the next quarter; Deploy production operations across multiple branches of an enterprise based on the predicted sales trends for the next quarter.

7. A multi-branch enterprise digital base and data pulling method according to claim 6, characterized in that: Extracting key features of transaction data to build a transaction prediction model for predicting sales trends in the next quarter includes: obtaining sales records and attribute features of products in different regions, analyzing changes in product sales quantities in different regions, and collecting attribute features of multiple hot-selling products in different periods based on sales volume changes in each region to train machine learning models in all regions to generate a transaction prediction model that predicts changes in product sales volume in each region over the next period; The deployment of production operations in multiple branches of the enterprise based on the predicted sales trend for the next quarter includes: Utilize the sales volume of goods in each region in the next period to optimize the production or purchase volume of goods and raw materials at branch nodes in each region.

8. A multi-branch enterprise digital base and data integration system, characterized by: include: Blockchain network building module: Using blockchain technology, build a decentralized data storage and transmission network of multiple branch nodes of an enterprise, and integrate smart contracts into the blockchain network; Data encryption and verification module: uses asymmetric encryption algorithms to encrypt data end-to-end and authenticates the data through digital signatures; Node business execution module: Design the smart contract according to business rules to automatically execute data exchange and business processes of each branch node, including: extracting and modeling the data exchange and business processes of each branch node according to the enterprise business process, specifically including: obtaining the maximum duration and minimum duration of each intermediate business process between two target business processes, and the process sequence of multiple intermediate business processes from the log file; using the two target business processes and their multiple intermediate business processes to build a process model in a choreography modeling tool, embedding the maximum duration, the minimum duration and the process sequence into the business process, and generating a timed choreography diagram in BPMN format; parsing the timed choreography diagram into a JSON metamodel through a translator, parsing each sequence flow element, including start and end events, gateways, and activities with time constraints; exporting the JSON metamodel; writing a smart contract based on the extracted data exchange and business processes of each branch node; deploying and monitoring the smart contract; Node data update module: updates the node data of each branch of the blockchain network in real time through data synchronization algorithm; Data in-depth analysis module: conducts in-depth analysis on the updated branch node data to optimize the production costs of each branch node.

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