Enterprise data management method and system, terminal and storage medium

Abstract

The invention relates to the technical field of block chains, and particularly provides an enterprise data management method and system, a terminal and a storage medium, and the method comprises the steps: obtaining business data through a data collection tool disposed in an enterprise business system; generating description data for the business data, wherein the description data comprises basic information and data elements of the business data; generating a unique identification code for the service data based on the description data, and registering the unique identification code to an identification analysis system; and issuing the encrypted service data and the corresponding plaintext description data to a block chain, and transacting the service data to a data application party through the block chain. According to the method, enterprise multi-source heterogeneous data are uniformly integrated and accessed, multiple enterprise data sources are compatible, and data consistency is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the field of blockchain technology, and specifically relates to an enterprise data management method, system, terminal and storage medium. Background Art

[0002] As a new production factor, data has been rapidly integrated into all aspects of production, distribution, circulation, consumption and social service management, becoming a key driving force for high-quality economic and social development. With the continuous advancement of technology, especially the breakthrough development of the Internet, big data, cloud computing, the Internet of Things and artificial intelligence, we have entered a new data-driven era. In this era, data is not only a carrier of information, but also a core element to promote innovation, optimize resource allocation and reshape business models.

[0003] However, in this era of surging data, effective data collection has become a crucial prerequisite. At present, most of the existing data collection systems on the market focus on the technical implementation and process of data collection, while the effectiveness, scalability and transferability of the collected data are relatively insufficient. This leads to a significant problem: despite the huge amount of data collected, the circulation rate of data is low, the correlation between data is weak, and it is difficult to fully explore and utilize the potential value of data, so that the multiplication effect of data cannot be fully exerted. In other words, the "rich mine" of data has not been effectively developed and utilized, and its huge role in promoting social and economic development has not yet been fully released. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides an enterprise data management method, system, terminal and storage medium to solve the above-mentioned technical problems.

[0005] In a first aspect, the present invention provides an enterprise data management method, comprising: Obtain business data through data collection tools deployed in enterprise business systems; Generate description data for the business data, wherein the description data includes basic information and data elements of the business data; Generate a unique identification code for the business data based on the description data, and register the unique identification code with an identification resolution system; The encrypted business data and the corresponding plaintext description data are published to the blockchain, and the business data is traded to the data application party through the blockchain.

[0006] In an optional implementation, description data is generated for the business data, and the description data includes basic information and data elements of the business data, including: Preprocessing the business data, wherein the preprocessing includes dirty data processing and privacy processing; Extracting basic information of the pre-processed business data, the basic information includes data owner, data name, data release time, data introduction information, number of data items and data format; Perform secondary calculation on the preprocessed business data to obtain data elements, which include average value, maximum value, minimum value, fluctuation trend and frequency of abnormal data occurrence; Integrate the basic information and the data elements into description data; The preprocessed business data is bound to the description data, and the bound data is converted into JSON data, and the JSON data is saved in the internal database of the enterprise.

[0007] In an optional implementation, generating a unique identification code for the business data based on the description data, and registering the unique identification code with an identification resolution system includes: Extracting data owner information from the description data, wherein the data owner information includes the business field and scale of the enterprise; Generate a type code based on the data owner information according to the pre-set field codes corresponding to the various business fields of the enterprise and the specification codes corresponding to the various specifications; Randomly generate a set of unique codes based on a preset identification code rule, and combine the type code and the unique code into an identification code; The identification code, the storage address of the business data in the internal database of the enterprise and the description data are registered in the identification resolution system.

[0008] In an optional embodiment, the method further comprises: Enterprises are grouped according to their business areas and sizes to obtain multiple enterprise category groups; Building a blockchain based on the internal database nodes of the same enterprise category group, and obtaining multiple blockchains corresponding to the enterprise categories; Use cross-chain routing to establish communication between multiple blockchains.

[0009] In an optional implementation, the method for a data application party to generate a data acquisition request based on the identity resolution system includes: The data application direction identification resolution system sends the target type code; The data application receives the identification code set including the target type code and the corresponding description data and storage address returned by the identification resolution system; The data application party filters out the target description data from the data returned by the identity resolution system, and sends a transaction request to the blockchain to which the storage address corresponding to the target description data belongs.

[0010] In a second aspect, the present invention provides an enterprise data management system, comprising: A data acquisition module is used to acquire business data through a data collection tool deployed in the enterprise business system; A data processing module, used to generate description data for the business data, wherein the description data includes basic information and data elements of the business data; An identification registration module, used to generate a unique identification code for the business data based on the description data, and register the unique identification code with an identification resolution system; The data transaction module is used to publish the encrypted business data and the corresponding plaintext description data to the blockchain, and trade the business data to the data application party through the blockchain.

[0011] In an optional embodiment, the data processing module includes: A preprocessing unit, used to preprocess the business data, wherein the preprocessing includes dirty data processing and privacy processing; An information extraction unit, used to extract basic information of the pre-processed business data, wherein the basic information includes data owner, data name, data release time, data introduction information, number of data items and data format; An element generation unit is used to perform secondary calculation on the preprocessed business data to obtain data elements, wherein the data elements include average value, maximum value, minimum value, fluctuation trend and frequency of occurrence of abnormal data; A description generating unit, used for integrating the basic information and the data elements into description data; The data storage unit is used to bind the preprocessed business data with the description data, convert the bound data into JSON data, and save the JSON data to the internal database of the enterprise.

[0012] In an optional implementation, the identification registration module includes: An information acquisition unit, used to extract data owner information from the description data, wherein the data owner information includes the business field and scale of the enterprise; A code generating unit, configured to generate a type code based on the data owner information according to the preset field codes corresponding to the various enterprise business fields and the specification codes corresponding to the various specifications; An identification generating unit, configured to randomly generate a set of unique codes based on a preset identification code rule, and combine the type code and the unique code into an identification code; The identification registration unit is used to register the identification code, the storage address of the business data in the internal database of the enterprise and the description data to the identification resolution system.

[0013] In a third aspect, a terminal is provided, including: processor, memory, wherein: The memory is used to store computer programs. The processor is used to call and run the computer program from the memory, so that the terminal executes the above-mentioned terminal method.

[0014] According to a fourth aspect, a computer storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the methods described in the above aspects.

[0015] The beneficial effects of the present invention are that the enterprise data management method, system, terminal and storage medium provided by the present invention integrate and access the multi-source heterogeneous data of the enterprise in a unified manner, are compatible with multiple data sources of the enterprise, and ensure data consistency; the accessed data is uniformly processed into secure, reliable, and highly usable factorized data, providing high-quality data support for industrial applications, large model calculations, data transactions, and subsequent data asset entry into tables.

[0016] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0019] Figure 2 It is a schematic architecture diagram of a method according to an embodiment of the present invention.

[0020] Figure 3 The figure is a schematic flow chart of data transaction of a method according to an embodiment of the present invention.

[0021] Figure 4 is a schematic block diagram of a system according to an embodiment of the present invention.

[0022] Figure 5 A schematic diagram of the structure of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0025] The enterprise data management method provided by the embodiment of the present invention is executed by a computer device, and accordingly, the enterprise data management system runs in the computer device.

[0026] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be an enterprise data management system. According to different requirements, the order of the steps in the flow chart may be changed, and some may be omitted.

[0027] like Figure 1 As shown, the method includes: Step 110, obtaining business data through a data collection tool deployed in the enterprise business system; Step 120, generating description data for the business data, wherein the description data includes basic information and data elements of the business data; Step 130, generating a unique identification code for the business data based on the description data, and registering the unique identification code with an identification resolution system; Step 140, publish the encrypted business data and the corresponding plain text description data to the blockchain, and trade the business data to the data application party through the blockchain.

[0028] To facilitate understanding of the present invention, the enterprise data management method provided by the present invention is further described below based on the principle of the enterprise data management method of the present invention and in combination with the process of managing enterprise data in the embodiment.

[0029] For details, please refer to Figure 2 , enterprise data management methods include: S1. Obtain business data through data collection tools deployed in the enterprise business system.

[0030] The sensing devices and gateways are generally connected to the data collection and processing system through MQTT, TCP, COAP, HTTP, etc., and the devices push data to the data collection platform on a regular basis and / or in real time; the edge nodes and application platforms are generally configured with APIs, databases, message queues and other data sources, and the platform extracts data to the data collection platform in full and / or incrementally on a regular basis.

[0031] S2. Generate description data for the business data, where the description data includes basic information and data elements of the business data.

[0032] S201. Preprocess the business data, where the preprocessing includes dirty data processing and privacy processing.

[0033] Dirty data processing: First, clean the business data to remove or correct incomplete, erroneous, duplicate or abnormal data. For example, for missing values, you can fill them according to the algorithm, such as using the mean, median or mode; for abnormal values, you can filter or correct them by setting a reasonable threshold.

[0034] Privacy processing: In the pre-processing stage, sensitive information in business data needs to be desensitized to protect personal privacy and corporate secrets. For example, for sensitive information such as ID card number and mobile phone number, encryption, replacement or anonymization can be used for processing.

[0035] S202. Extract basic information of the pre-processed business data, where the basic information includes data owner, data name, data release time, data introduction information, number of data items, and data format.

[0036] When extracting basic information, you need to ensure the accuracy and completeness of the information. The data owner refers to the individual or organization that owns the dataset; the data name is a concise description of the content of the dataset; the data release time records the release date of the dataset; the data introduction information provides a detailed description and background information of the dataset; the number of data items indicates the number of records in the dataset; and the data format describes how the data is stored and organized.

[0037] S203. Perform secondary calculation on the preprocessed business data to obtain data elements, which include average value, maximum value, minimum value, fluctuation trend and frequency of abnormal data occurrence.

[0038] Secondary calculation is to further analyze and process the preprocessed data to extract valuable data elements. The average value can reflect the central trend of the data; the maximum and minimum values ​​describe the range of the data; the fluctuation trend reveals the law of change of data over time or other factors; the frequency of abnormal data reflects the proportion and distribution of abnormal values ​​in the data.

[0039] S204: Integrate the basic information and the data elements into description data.

[0040] Descriptive data is a comprehensive summary of business data, which includes two aspects: basic information and data elements. By integrating this information, a complete, accurate and easy-to-understand data description can be formed, which facilitates subsequent data application and management.

[0041] S205: Bind the preprocessed business data to the description data, convert the bound data into JSON data, and save the JSON data to an internal database of the enterprise.

[0042] The binding operation is to associate the preprocessed business data with the description data to form a data set containing complete information. Then, this data set is converted into JSON format for efficient storage and transmission. Finally, the JSON data is saved to the company's internal database for subsequent data query, analysis and application.

[0043] S3. Generate a unique identification code for the business data based on the description data, and register the unique identification code with an identification resolution system.

[0044] Extract data owner information from the description data, the data owner information including the business field and scale of the enterprise; generate a type code based on the data owner information according to pre-set field codes corresponding to multiple business fields of the enterprise and specification codes corresponding to multiple specifications; randomly generate a set of unique codes based on pre-set identification code rules, and combine the type code and the unique code into an identification code; register the identification code, the storage address of the business data in the enterprise's internal database, and the description data in an identification resolution system.

[0045] The specific steps include: Extract data owner information from description data: First, it is necessary to extract relevant information about the data owner from the integrated description data. The data owner information specifically covers the business scope and scale of the enterprise. These two aspects can more comprehensively depict the basic background and strength of the data owner.

[0046] Generate type code: The system has a set of pre-set coding rules that correspond to a variety of different business areas and specifications. Based on the business area and scale information extracted from the description data, we can find the corresponding field code and specification code. Then, these two codes are combined to generate a type code representing the type and scale of the enterprise.

[0047] Generate a unique code and combine it into an identification code: In order to ensure that each data owner has a unique identification, the system will randomly generate a set of unique codes based on the pre-set identification code rules. This set of unique codes is combined with the previously generated type code to form a complete and unique identification code.

[0048] Register the identification code and related information to the identification resolution system: Finally, we need to register the generated identification code, the storage address of the business data in the internal database of the enterprise, and the original description data into the identity resolution system. The purpose of this is to achieve data traceability and easy management. When you need to query or use this data, you can quickly and accurately find its location and related information through the identity resolution system.

[0049] S4. Build blockchain.

[0050] In one embodiment of the present invention, in order to improve data transaction efficiency, enterprises of the same category are placed on the same blockchain, specifically including: Enterprises are grouped according to their business areas and scales to obtain multiple enterprise category groups; blockchains are established based on internal database nodes of enterprises in the same enterprise category group to obtain multiple blockchains corresponding to the enterprise categories; and cross-chain routing is used to establish communication between multiple blockchains.

[0051] Using the business scope and scale of enterprises as grouping criteria can efficiently organize enterprises and promote information sharing and collaboration. Furthermore, by combining blockchain technology with cross-chain routing, an independent yet interconnected enterprise ecosystem can be built. The following is a detailed description of the process: 1. Grouping by business area and size First, we grouped enterprises according to their business areas (such as technology, production, food processing, trade, services, etc.) and scales (large, medium, small, micro) to obtain multiple enterprise category groups. This grouping method helps to bring together enterprises with similar business models and needs, facilitating subsequent information sharing and cooperation.

[0052] 2. Building a blockchain based on the same enterprise category group In each enterprise category group, an internal database node network is constructed using blockchain technology. As a decentralized, tamper-proof database, blockchain can ensure data security and transparency. Each enterprise category group corresponds to a blockchain, and the nodes on the blockchain are composed of the database nodes of each enterprise in the group.

[0053] Data layer: Encapsulates underlying data blocks and related data encryption and timestamp technologies to ensure data security and traceability.

[0054] Network layer: includes distributed networking mechanism, data transmission mechanism and data verification mechanism to ensure effective communication and data consistency between nodes.

[0055] Consensus layer: encapsulates various consensus algorithms, such as proof of work (PoW), proof of stake (PoS), etc., to reach a consensus among network nodes.

[0056] Incentive layer (optional): In an economically incentivized blockchain, an economic incentive issuance and distribution mechanism is integrated to encourage node participation and contribution.

[0057] Contract layer: Encapsulates smart contracts, allowing enterprises to customize business logic and achieve automated processing and contract execution.

[0058] Application layer: Encapsulates various application scenarios and cases, such as supply chain management, financial management, auditing, etc., to meet the actual business needs of the enterprise.

[0059] 3. Use cross-chain routing to establish communication between multiple blockchains In order to break the information silos between different enterprise category groups, cross-chain routing technology is used to establish communication between multiple blockchains. Cross-chain routing allows data exchange and asset transfer between different blockchain systems, realizing cross-chain interaction.

[0060] Isomorphic cross-chain: For enterprise category group blockchains that use the same consensus algorithm and security mechanism, cross-chain interaction is relatively simple, and cross-chain protocols can be directly designed for data transmission.

[0061] Heterogeneous cross-chain: For enterprise-class group blockchains that use different consensus algorithms and security mechanisms, cross-chain interactions are more complicated and require the introduction of third-party auxiliary services (such as relayers) or the use of specialized cross-chain protocols (such as Cosmos' IBC protocol) to achieve cross-chain communication.

[0062] 4. Implementation steps of cross-chain communication Registration and certification: The blockchains of each enterprise category group are registered and mutually authenticated in the cross-chain network to ensure trust between chains.

[0063] Cross-chain protocol formulation: formulate cross-chain communication protocols based on actual needs, and clarify data formats, transmission methods and verification mechanisms.

[0064] Repeater or cross-chain bridge deployment: Deploy repeaters or cross-chain bridges in the cross-chain network to be responsible for forwarding and verifying cross-chain messages.

[0065] Cross-chain transaction execution: Enterprises can exchange data and transfer assets between different blockchains through cross-chain transactions, and the transaction process is automatically executed through cross-chain protocols and smart contracts.

[0066] Monitoring and Auditing: Establish a cross-chain monitoring and auditing mechanism to ensure the authenticity and legality of cross-chain transactions and prevent data tampering and fraud.

[0067] S5. The method for a data application party to generate a data acquisition request based on the identification resolution system includes: Please refer to Figure 3 , the data application sends the target type code to the identification resolution system; the data application receives the identification code set containing the target type code and the corresponding description data and storage address returned by the identification resolution system; the data application filters out the target description data from the data returned by the identification resolution system, and sends a transaction request to the blockchain to which the storage address corresponding to the target description data belongs.

[0068] The specific steps include: 1. Technical implementation and preparation Data application party preparation: Data application parties must first clarify their needs, that is, the target type code that needs to be queried or operated. This usually involves an in-depth understanding of the business logic to ensure that the target type code requested is accurate.

[0069] Interface definition: The data application party needs to agree on the interactive interface protocol with the identity resolution system, including the request format (such as JSON or XML), request parameters (such as target type encoding), response format, etc., to ensure that both parties can communicate smoothly.

[0070] Authority verification: Before sending a request, the data application party may need to go through an identity authentication and authorization mechanism to ensure that it has the authority to initiate a request to the identity resolution system.

[0071] 2. Send a request Constructing a request: The data application party constructs a query request containing the target type code according to the predefined interface protocol.

[0072] Send a request: Send the request to the identity resolution system through HTTP, RESTful API, or other agreed communication protocols.

[0073] 3. Identity resolution system processing Receiving requests: The identity resolution system receives requests from data application parties and performs preliminary verification, such as request format, permissions, etc.

[0074] Parsing target type code: The system searches for the corresponding identification code set in the internal database or index based on the received target type code.

[0075] Prepare response data: For each identification code queried, the system also needs to prepare corresponding description data and storage address.

[0076] Return response: Return the response data including the identification code set, description data and storage address to the data application party.

[0077] 4. The data application receives and processes the response Parsing response: The data application receives and parses the response data from the identity resolution system.

[0078] Filter target description data: Filter specific target description data from the response data based on business needs.

[0079] Constructing a transaction request: Based on the filtered target description data, especially its corresponding storage address, the data application party constructs a transaction request and prepares to interact with the storage node.

[0080] 5. Send a transaction request to the storage node or the blockchain where the storage node is located Determine the storage node: Determine the specific enterprise node based on the storage address in the target description data.

[0081] Send transaction request: Send data transaction request to the blockchain where the enterprise node is located through appropriate protocols (such as HTTP, RPC, etc.).

[0082] S5. Publish the encrypted business data and the corresponding plain text description data to the blockchain, and trade the business data to the data application party through the blockchain.

[0083] After receiving the data, the data application party performs signature authentication. If the authentication is passed, the transaction is successful and the trusted flow of data is completed.

[0084] Specifically include: Before publishing business data to the blockchain, use a strong encryption algorithm (such as AES, RSA, etc.) to encrypt the business data. The encryption process should ensure the confidentiality and integrity of the data and prevent the data from being illegally accessed or tampered with during transmission and storage. The encrypted data exists in ciphertext form, and only the data application party holding the corresponding decryption key can decrypt and access the original data.

[0085] Publish encrypted data to the blockchain. Publish the encrypted business data and its unique identifier to the blockchain network as part of the transaction. The nodes in the blockchain network will verify the validity of the transaction and add it to the blockchain's distributed ledger. The immutability and decentralization of the blockchain ensure the security and credibility of the transaction data.

[0086] Blockchain transaction processing. Miners or verification nodes in the blockchain network are responsible for processing transactions, including verifying the legitimacy of transactions, resolving potential conflicts, and updating the status of the blockchain. Once a transaction is confirmed and added to the blockchain, the data application party can obtain encrypted business data by querying the blockchain network or using the API interface provided by the blockchain.

[0087] The data application receives the data. After obtaining the encrypted business data, the data application uses its own decryption key or a decryption mechanism negotiated with the data provider to decrypt the data. The decrypted raw data will be used in business analysis, decision support, product optimization and other scenarios of the data application.

[0088] In some embodiments, the enterprise data management system may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the enterprise data management system may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 1 Description) Functionality of enterprise data management.

[0089] In this embodiment, the enterprise data management system can be divided into multiple functional modules according to the functions it performs, such as Figure 4 As shown. The functional modules of the system 400 may include: a data acquisition module 410, a data processing module 420, an identification registration module 430 and a data transaction module 440. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0090] A data acquisition module is used to acquire business data through a data collection tool deployed in the enterprise business system; A data processing module, used to generate description data for the business data, wherein the description data includes basic information and data elements of the business data; An identification registration module, used to generate a unique identification code for the business data based on the description data, and register the unique identification code with an identification resolution system; The data transaction module is used to publish the encrypted business data and the corresponding plaintext description data to the blockchain, and trade the business data to the data application party through the blockchain.

[0091] Optionally, as an embodiment of the present invention, the data processing module includes: A preprocessing unit, used to preprocess the business data, wherein the preprocessing includes dirty data processing and privacy processing; An information extraction unit, used to extract basic information of the pre-processed business data, wherein the basic information includes data owner, data name, data release time, data introduction information, number of data items and data format; An element generation unit is used to perform secondary calculation on the preprocessed business data to obtain data elements, wherein the data elements include average value, maximum value, minimum value, fluctuation trend and frequency of occurrence of abnormal data; A description generating unit, used for integrating the basic information and the data elements into description data; The data storage unit is used to bind the preprocessed business data with the description data, convert the bound data into JSON data, and save the JSON data into an internal database of the enterprise.

[0092] Optionally, as an embodiment of the present invention, the identification registration module includes: An information acquisition unit, used to extract data owner information from the description data, wherein the data owner information includes the business field and scale of the enterprise; A code generating unit, configured to generate a type code based on the data owner information according to the preset field codes corresponding to the various enterprise business fields and the specification codes corresponding to the various specifications; An identification generating unit, configured to randomly generate a set of unique codes based on a preset identification code rule, and combine the type code and the unique code into an identification code; The identification registration unit is used to register the identification code, the storage address of the business data in the internal database of the enterprise and the description data to the identification resolution system.

[0093] Figure 5 This is a schematic diagram of the structure of a terminal 500 provided in an embodiment of the present invention. The terminal 500 can be used to execute the enterprise data management method provided in an embodiment of the present invention.

[0094] The terminal 500 may include: a processor 510, a memory 520 and a communication unit 530. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0095] The memory 520 can be used to store the execution instructions of the processor 510, and the memory 520 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 520 are executed by the processor 510, the terminal 500 can execute some or all of the steps in the following method embodiments.

[0096] The processor 510 is the control center of the storage terminal, and uses various interfaces and lines to connect various parts of the entire electronic terminal. It runs or executes software programs and / or modules stored in the memory 520, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 510 can only include a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0097] The communication unit 530 is used to establish a communication channel so that the storage terminal can communicate with other terminals, receive user data sent by other terminals or send user data to other terminals.

[0098] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0099] Therefore, the present invention integrates and accesses multi-source heterogeneous data of an enterprise in a unified manner, is compatible with multiple data sources of the enterprise, and ensures data consistency; the accessed data is uniformly processed into secure, reliable, and highly usable factorized data, providing high-quality data support for industrial applications, large model calculations, data transactions, and subsequent data asset entry into tables. The technical effects that can be achieved by this embodiment can be found in the description above and will not be repeated here.

[0100] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0101] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0102] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0103] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0104] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0105] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. An enterprise data management method, characterized in that: include: Obtain business data through data collection tools deployed in enterprise business systems; Generating description data for the business data, wherein the description data includes basic information and data elements of the business data; generating a unique identification code for the business data based on the description data, and registering the unique identification code with an identification resolution system; The encrypted business data and the corresponding plaintext description data are published to the blockchain, and the business data is traded to the data application party through the blockchain.

2. The method according to claim 1, characterized in that Generate description data for the business data, the description data including basic information and data elements of the business data, including: Preprocessing the business data, wherein the preprocessing includes dirty data processing and privacy processing; Extracting basic information of the pre-processed business data, including data owner, data name, data release time, data introduction information, number of data items, and data format; Perform secondary calculations on the pre-processed business data to obtain data elements, including average value, maximum value, minimum value, fluctuation trend and frequency of abnormal data occurrence; Integrating the basic information and the data elements into description data; The pre-processed business data is bound to the description data, and the bound data is converted into JSON data, and the JSON data is saved in the enterprise internal database.

3. The method according to claim 2, characterized in that Generating a unique identification code for the business data based on the description data, and registering the unique identification code with an identification resolution system, including: Extracting data owner information from the description data, wherein the data owner information includes the business field and scale of the enterprise; Generate a type code based on the data owner information according to the pre-set field codes corresponding to the various business fields of enterprises and the specification codes corresponding to the various specifications; Randomly generate a set of unique codes based on a preset identification code rule, and combine the type code and the unique code into an identification code; The identification code, the storage address of the business data in the enterprise's internal database and the description data are registered in the identification resolution system.

4. The method according to claim 3, characterized in that The method further comprises: Enterprises are grouped according to their business areas and sizes to obtain multiple enterprise category groups; Building a blockchain based on the internal database nodes of the same enterprise category group to obtain multiple blockchains corresponding to the enterprise category; Use cross-chain routing to establish communication between multiple blockchains.

5. The method according to claim 4, characterized in that The method for a data application party to generate a data acquisition request based on the identity resolution system includes: The data application direction identification resolution system sends the target type code; The data application receives the identification code set containing the target type code and the corresponding description data and storage address returned by the identification resolution system; The data application party filters out the target description data from the data returned by the identity resolution system and sends a transaction request to the blockchain to which the storage address corresponding to the target description data belongs.

6. An enterprise data management system, characterized in that: include: The data acquisition module is used to obtain business data through data collection tools deployed in the enterprise business system; A data processing module, configured to generate description data for the business data, wherein the description data includes basic information and data elements of the business data; an identification registration module, configured to generate a unique identification code for the business data based on the description data, and register the unique identification code with an identification resolution system; The data transaction module is used to publish encrypted business data and corresponding plaintext description data to the blockchain, and trade the business data to the data application party through the blockchain.

7. The system according to claim 6, characterized in that The data processing module includes: A preprocessing unit, configured to preprocess the business data, wherein the preprocessing includes dirty data processing and privacy processing; An information extraction unit is used to extract basic information of the pre-processed business data, wherein the basic information includes the data owner, data name, data release time, data introduction information, number of data items, and data format; An element generation unit is used to perform secondary calculations on the pre-processed business data to obtain data elements, which include average value, maximum value, minimum value, fluctuation trend and frequency of abnormal data occurrence; a description generating unit, configured to integrate the basic information and the data elements into description data; The data storage unit is used to bind the pre-processed business data with the description data, convert the bound data into JSON data, and save the JSON data to the enterprise's internal database.

8. The system according to claim 7, characterized in that The identification registration module includes: An information acquisition unit, configured to extract data owner information from the description data, wherein the data owner information includes the business field and scale of the enterprise; a code generating unit, configured to generate a type code based on the data owner information according to pre-set field codes corresponding to multiple business fields and specification codes corresponding to multiple specifications; an identification generating unit, configured to randomly generate a set of unique codes based on a preset identification code rule, and combine the type code and the unique code into an identification code; The identification registration unit is used to register the identification code, the storage address of the business data in the enterprise internal database and the description data to the identification resolution system.

9. A terminal, characterized in that: include: memory for storing enterprise data management programs; A processor, configured to implement the steps of the enterprise data management method according to any one of claims 1 to 5 when executing the enterprise data management program.

10. A computer-readable storage medium storing a computer program, characterized in that: The readable storage medium stores an enterprise data management program, which, when executed by a processor, implements the steps of the enterprise data management method according to any one of claims 1 to 5.

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