Multi-branch enterprise digital base and data connection method and system

Abstract

The invention discloses a multi-branch enterprise digital base and a data pull-through method and system, and relates to the technical field of distributed account books. According to the multi-branch enterprise digital base and the data connection method, a block chain technology is adopted, a decentralized data storage and transmission network of multiple branch mechanism nodes of an enterprise is constructed, and an intelligent contract is integrated in the block chain network; performing end-to-end encryption on the data by using an asymmetric encryption algorithm, and performing identity verification through a digital signature; the intelligent contract is designed according to a business rule so as to automatically execute data exchange and business processes of each branch mechanism node; node data of each branch mechanism of the block chain network is updated in real time through a data synchronization algorithm; and performing deep analysis on the updated data of each branch mechanism node, and optimizing the production cost of each branch mechanism node. According to the invention, real-time sharing, synchronization and analysis of data among branch mechanisms are realized, and data authenticity, security and processing efficiency are ensured.

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 pulling method and system. Background Art

[0002] The main challenge currently faced by enterprises in digital transformation is how to efficiently and securely share and synchronize data among multiple branches. Existing technologies such as centralized databases can process data, but they have problems such as single point failure, poor data security and limited scalability. Distributed ledger technology, such as blockchain, has gradually become a cutting-edge direction for solving this problem due to its data immutability and decentralized characteristics. However, applying this technology within the enterprise, especially in a multi-branch structure, still needs to overcome major problems such as algorithm complexity, system compatibility and real-time performance optimization. At present, it is necessary to design a multi-branch enterprise digital base and data pulling method, which can 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. 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, so as to promote 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-mentioned technical problems.

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

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

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

[0007] Using asymmetric encryption algorithms, data is encrypted end-to-end and authenticated through digital signatures;

[0008] Design smart contracts based on business rules to automate data exchange and business processes at each branch node;

[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 of 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 point-to-point 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 the target node is found.

[0018] The above uses an asymmetric encryption algorithm 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 office, 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 above smart contracts are designed according to business rules to automate the data exchange and business processes of each branch node, including:

[0022] Extract the data exchange and business processes of each branch node according to the enterprise business process and model them;

[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] 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 are obtained from the log file; a process model is constructed in a choreography diagram modeling tool using the two target business processes and the multiple intermediate business processes, and the maximum duration, the minimum duration and the process sequence are embedded into the business process to generate a timed choreography diagram in the BPMN format; the BPMN diagram is parsed into a JSON metamodel through a translator, and each sequence flow element is parsed, including start and end events, gateways, and activities with time constraints; a message structure is obtained from the process model message set in combination with the activity, and is associated with the activity information of the metamodel, while processing the time constraints of the activity; the metamodel in JSON format is exported, including a list of responsible person roles, model messages, elements, decisions, and time constraints.

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

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

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

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

[0031] Use a timestamp-based data version; design a synchronization algorithm based on the timestamp to determine whether the 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 integrated advanced data analysis tools conduct in-depth analysis of the updated branch node data to optimize the production branch cost of each branch node, including:

[0038] Integrated data analysis tools;

[0039] Preprocessing updated transaction data of each branch node;

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

[0041] Use historical data to train the transaction prediction model and evaluate the performance of the transaction prediction model through the 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 in 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 the sales trend of the next quarter includes: obtaining sales records and attribute features of commodities in different regions, analyzing changes in the sales quantity of commodities in different regions, collecting key attribute features of multiple commodities through sales volume changes in various regions to train machine learning models in all regions, so as to generate a transaction prediction model for predicting the sales volume of commodities in each region in the next quarter;

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

[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 the 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 algorithms to encrypt data end-to-end, and authenticates identity through digital signatures; designs 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; integrates advanced data analysis tools to conduct in-depth analysis of the updated branch node data, and optimizes the production branch cost 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 embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. 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 embodiments and drawings. The exemplary embodiments of the present invention and their description 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 pulling method, including:

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

[0055] Using asymmetric encryption algorithms, data is encrypted end-to-end and authenticated through digital signatures;

[0056] Design smart contracts based on business rules to automate data exchange and business processes at each branch node;

[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 of 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 point-to-point 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 the target node is found.

[0066] This recursive search strategy ensures that proxies are set up in the returned nodes for communication between the source and the target, and these proxy nodes act as a communication relay station. This method enhances the reliability of communication between nodes without changing the network security framework, ensuring smooth data transmission even if the link is partially blocked, while improving the security of network nodes.

[0067] The above uses an asymmetric encryption algorithm 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 office, 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 above smart contracts are designed according to business rules to automate the data exchange and business processes of each branch node, including:

[0071] Extract the data exchange and business processes of each branch node according to the enterprise business process and model them;

[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] 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 are obtained from the log file; a process model is constructed in a choreography diagram modeling tool using the two target business processes and the multiple intermediate business processes, and the maximum duration, the minimum duration and the process sequence are embedded into the business process to generate a timed choreography diagram in the BPMN format; the BPMN diagram is parsed into a JSON metamodel through a translator, and each sequence flow element is parsed, including start and end events, gateways, and activities with time constraints; a message structure is obtained from the process model message set in combination with the activity, and is associated with the activity information of the metamodel, while processing the time constraints of the activity; the metamodel in JSON format is exported, including a list of responsible person roles, model messages, elements, decisions, and time constraints.

[0076] The blockchain business process management method driven by the timed orchestration graph can solve the trust problem across organizations, effectively control the process that violates the time constraint, and reduce the blockchain gas consumption through the reuse of smart contracts, facilitate version control, and improve the degree of decentralization. In practical applications, it enables enterprises to efficiently model and test smart contracts, monitor them after deployment, and ensure the smooth operation of data exchange and business processes of nodes in each branch.

[0077] Through the parser, the BPMN diagram is converted into a JSON metamodel, which contains detailed time-constrained activities and message structures. Furthermore, the activities of the metamodel are associated with the message structure to handle the time constraints of the activities, ensuring the improvement of process operation efficiency and service quality. Finally, the exported JSON format metamodel contains a complete list of roles, messages, elements, decisions and time constraints, which significantly reduces model redundancy and improves program operation efficiency.

[0078] The above-mentioned two target business processes and multiple intermediate business processes are used to construct a process model in the orchestration diagram modeling tool, and the above-mentioned maximum duration, the above-mentioned minimum duration and the above-mentioned process sequence are embedded into the business process to generate a timed orchestration diagram in BPMN format, including: using the optimization mining method of the business process to replay the processed log sequences one by one, and construct, adjust and select models according to the constraint indicators of the above-mentioned maximum duration and the above-mentioned minimum duration. It can effectively extract log sequences from the program running trajectory, integrate time constraint information into the business process, and generate a BPMN timed orchestration diagram with clear structure and reasonable behavior.

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

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

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

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

[0083] Use a timestamp-based data version; design a synchronization algorithm based on the timestamp to determine whether the 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 integrated advanced data analysis tools conduct in-depth analysis of the updated branch node data to optimize the production branch cost of each branch node, including:

[0090] Integrated data analysis tools;

[0091] Preprocessing updated transaction data of each branch node;

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

[0093] Use historical data to train the transaction prediction model and evaluate the performance of the transaction prediction model through the 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 in 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 the sales trend of the next quarter includes: obtaining sales records and attribute features of commodities in different regions, analyzing changes in the sales quantity of commodities in different regions, collecting key attribute features of multiple commodities through sales volume changes in various regions to train machine learning models in all regions, so as to generate a transaction prediction model for predicting the sales volume of commodities in each region in the next quarter;

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

[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 the branch nodes in each region.

[0099] It can effectively improve processing efficiency, reduce the complexity of feature engineering, help automatically build high-quality prediction models, and effectively improve the accuracy of model predictions. In this way, companies can more accurately predict sales trends for the next quarter, so as to adjust strategies and business layouts in a timely manner. Accurately adjust production line schedules and inventory to reduce overproduction or undersupply, thereby minimizing inventory costs across the entire supply chain and improving resource allocation efficiency.

[0100] In summary, the present application embodiment provides a multi-branch enterprise digital base and data pulling method and system:

[0101] Blockchain technology is used to build a decentralized data storage and transmission network for multiple branch nodes of an enterprise; an asymmetric encryption algorithm is used to encrypt data end-to-end, and identity authentication is performed through digital signatures; smart contracts are designed according to business rules to automate data exchange and business processes of each branch node; data synchronization algorithms are used to update the data of each branch node of the blockchain network in real time; advanced data analysis tools are integrated to conduct in-depth analysis of the updated data of each branch node, and optimize the production branch cost 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 pulling method, characterized in that: include: Adopt blockchain technology to build a decentralized data storage and transmission network of multiple branch nodes of the enterprise, and integrate smart contracts in the blockchain network; Using asymmetric encryption algorithms, data is encrypted end-to-end and authenticated through digital signatures; Design the smart contract according to business rules to automate data exchange and business processes of each branch node; Update the node data of each branch of the blockchain network in real time through 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 of 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 the target node is found.

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 office, 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 smart contract is designed according to the business rules to automatically execute the data exchange and business processes of each branch node, including: Extract the data exchange and business processes of each branch node according to the enterprise business process and model them; Write smart contracts based on the extracted data exchange and business processes of each branch node: Deploy and monitor smart contracts.

6. A multi-branch enterprise digital base and data pulling method according to claim 5, characterized in that: The data exchange and business process of each branch node is extracted and modeled according to the enterprise business process, including: 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 are obtained from the log file; a process model is constructed in a choreography diagram modeling tool using the two target business processes and their multiple intermediate business processes, and the maximum duration, the minimum duration and the process sequence are embedded into the business process to generate a timed choreography diagram in BPMN format; the timed choreography diagram is parsed into a JSON metamodel through a translator, and each sequence flow element, including start and end events, gateways, and activities with time constraints, is parsed; and the JSON metamodel is exported.

7. 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: Formulate a synchronization strategy for node data in each branch, including: Set corresponding synchronization cycles for different types of data according to the frequency of data changes; and set high priority for real-time data updates for key business data; Design synchronization algorithms based on synchronization strategies, including: Use a timestamp-based data version; design a synchronization algorithm based on the timestamp to determine whether the 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.

8. A multi-branch enterprise digital base and data pulling method according to claim 1, characterized in that: The in-depth analysis of the updated node data of each branch office to optimize the production cost of each branch office node includes: Preprocessing updated transaction data of each branch node; Extract key features of transaction data to build a transaction prediction 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 in multiple branches of an enterprise based on the predicted sales trends for the next quarter.

9. A multi-branch enterprise digital base and data pulling method according to claim 8, characterized in that: The extracting key features of transaction data to construct a transaction prediction model for predicting the sales trend of the next quarter includes: obtaining sales records and attribute features of commodities in different regions, analyzing changes in the sales quantity of commodities in different regions, collecting attribute features of multiple hot-selling commodities in different periods through sales volume changes in each region, training machine learning models in all regions, and generating a transaction prediction model for predicting the sales volume changes of commodities in each region in the next period; The deployment of production services of multiple branches of the enterprise based on the predicted sales trend of the next quarter includes: Utilize the sales volume of goods in each region in the next period to optimize the production or purchase of goods and raw materials at the branch nodes in each region.

10. A multi-branch enterprise digital base and data pulling system, characterized in that: include: Blockchain network building module: Using blockchain technology, build a decentralized data storage and transmission network of multiple branch nodes of the enterprise, and integrate smart contracts in the blockchain network; Data encryption and verification module: uses asymmetric encryption algorithms to encrypt data end-to-end and authenticates identity through digital signatures; Node business execution module: design the smart contract according to business rules to automatically execute data exchange and business processes of nodes in each branch; 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: conduct in-depth analysis on the updated node data of each branch office to optimize the production cost of each branch office node.

Images