A peer-to-peer benchmarking information management method and system

Abstract

The application discloses a kind of peer benchmarking information management method and system, it is related to data processing technical field, the method includes: respectively obtaining the direct sampling data and offline data about peer benchmarking information collected by business service layer, receives the inspection result for direct sampling data and offline data;After the inspection result of direct sampling data and offline data meets the inspection passing condition, direct sampling data and offline data are stored in data storage layer according to preset rule;After receiving the display instruction sent by data access layer, the overall score of each relevant enterprise corresponding to the stored direct sampling data and offline data is calculated according to preset rule, and the overall score of relevant enterprise is displayed.The application solves the problem that existing technology cannot be accurately evaluated when managing peer benchmarking information, the data timeliness is not enough and the management is lacking.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a same industry benchmarking information management method and system. BACKGROUND

[0002] As a management method of finding one's own gap and optimizing operation strategy by comparing and analyzing the operating data, business processes, technical innovation, etc. of competitors or industry benchmarking enterprises, same industry benchmarking has become an important strategic tool for enterprises.

[0003] For example, in the financial field, banks adjust risk control strategies and business layouts by benchmarking the loan size, non-performing loan ratio, and intermediate business income proportion of competitors; in the manufacturing industry, enterprises improve production processes and reduce costs by comparing the production efficiency, product quality, and supply chain cost data of competitors.

[0004] However, the current enterprise benchmarking work is still in the stage of manual statistics and comparison of indicators, and it is difficult to accurately evaluate each enterprise, the data timeliness is not enough, and the management standardization needs to be improved. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a same industry benchmarking information management method and system, which aims to solve the problem of inaccurate evaluation, insufficient data timeliness, and poor management in the prior art.

[0006] One purpose of the present application is to provide a same industry benchmarking information management method applied to a same industry benchmarking information management platform, which includes a business service layer, a data access layer, and a data storage layer in communication connection with the business service layer, the method comprising:

[0007] Respectively acquiring direct sampling data and offline data about same industry benchmarking information collected by the business service layer, and receiving inspection results for the direct sampling data and offline data;

[0008] After the inspection results of the direct sampling data and offline data meet the inspection pass condition, storing the direct sampling data and offline data in the data storage layer according to a preset rule;

[0009] After receiving a display instruction sent by the data access layer, calculating the overall score of each related enterprise for the stored direct sampling data and offline data according to a preset rule, and displaying the overall score of the related enterprise.

[0010] Further, the same industry benchmarking information management method, wherein the step of storing the direct sampling data and offline data in the data storage layer according to a preset rule comprises:

[0011] A direct-sampling database, an offline database and an intermediate score database are respectively established in a data storage layer for storing direct-sampling data and offline data;

[0012] According to the enterprise unique identifier corresponding to the direct-sampling data and the offline data, score data for calculating the overall score is extracted from the direct-sampling data and the offline data;

[0013] The direct-sampling data, the offline data and the score data are respectively stored in the corresponding database, the offline database and the intermediate score database.

[0014] Further, the above-mentioned peer benchmarking information management method, wherein the step of storing the direct-sampling data, the offline data and the score data in the corresponding database, the offline database and the intermediate score database further comprises:

[0015] According to the enterprise unique identifier, the direct-sampling data and the offline data and the score data, a query data chain is constructed, and the query data chain is stored in the intermediate score database;

[0016] When the overall score of the enterprise needs to be calculated, the score data corresponding to the calculation of the overall score is determined according to the query data chain, and the overall score of the enterprise is determined according to the score data.

[0017] Further, the above-mentioned peer benchmarking information management method, wherein the step of constructing the query data chain according to the enterprise unique identifier, the direct-sampling data and the offline data and the score data and storing the query data chain in the intermediate score database comprises:

[0018] First and second hash values are obtained by performing hash operations on the information content of the direct-sampling data and the offline data, respectively, a target hash value is obtained according to the first and second hash values according to a predetermined rule, and a corresponding target data chain is obtained;

[0019] The target data chain is divided into equal parts according to a predetermined rule, the data ratio between the direct-sampling data and the offline data is obtained, the corresponding elements are selected from the corresponding chain positions in the target sub-data chain according to the data ratio, and the initial data chain is obtained by combining the selected elements and the positions of the target sub-data chain.

[0020] The enterprise unique identifier is used as a chain head to form a query data chain with the initial data chain, and the query data chain is left in the intermediate score database, wherein the query data chain and the data chain composed of the elements selected from the corresponding chain positions are mutually linked.

[0021] Further, the above-mentioned peer benchmarking information management method, wherein the step of obtaining the data ratio between the direct-sampling data and the offline data and selecting the corresponding elements from the corresponding chain positions in the target sub-data chain according to the data ratio comprises:

[0022] determining a target value with a larger value according to the data proportion, and segmenting the target sub-data chain according to the proportion corresponding to the target value, or determining a target value with a smaller value according to the data proportion, and segmenting the target sub-data chain according to the proportion corresponding to the target value;

[0023] segmenting the segmented target sub-data chain again according to the proportion corresponding to another target value, obtaining the segmentation position of each segmentation, and selecting the corresponding element from the segmentation position of each segmentation.

[0024] Further, the same industry benchmarking information management method, wherein the step of determining a target value with a larger value according to the data proportion, and segmenting the target sub-data chain according to the proportion corresponding to the target value, or determining a target value with a smaller value according to the data proportion, and segmenting the target sub-data chain according to the proportion corresponding to the target value includes:

[0025] When one of the target sub-data chains is initially segmented according to one of the target values in the data proportion, the adjacent target sub-data chain is initially segmented according to another target value in the data proportion.

[0026] Further, the same industry benchmarking information management method, wherein the step of obtaining the first hash value and the second hash value by performing hash operation on the information content of the online data and the offline data respectively, and obtaining the target hash value according to the first hash value and the second hash value according to the preset rule to obtain the corresponding target data chain includes:

[0027] performing bitwise XOR operation on the binary representation of the first hash value and the second hash value to obtain a new binary value, and performing hash calculation on the binary value after the XOR operation using the same hash algorithm to obtain the target hash value.

[0028] Another object of the present application is to provide a same industry benchmarking information management system applied to a same industry benchmarking information management platform, the same industry benchmarking information management platform including a business service layer and a data access layer and a data storage layer in communication connection with the business service layer respectively, the system including:

[0029] an acquisition module for acquiring online data and offline data about same industry benchmarking information collected by the business service layer respectively, and receiving inspection results for the online data and the offline data;

[0030] a storage module for storing the online data and the offline data in the data storage layer according to the preset rule after the inspection results of the online data and the offline data meet the inspection passing condition;

[0031] The display module is configured to calculate the overall scores of each related enterprise according to the preset rules based on the stored direct-sampling data and offline data after receiving the display instruction sent by the data access layer, and display the overall scores of the related enterprises.

[0032] Another object of the present application is to provide a computer program product, which comprises a computer program stored on a readable storage medium, the program being executable by a processor to implement the steps of the method described above.

[0033] Another object of the present application is to provide an electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor being configured to implement the steps of the method described above when executing the program.

[0034] The present application can ensure the comprehensiveness and integrity of the data by acquiring the direct-sampling data and offline data about the peer benchmarking information collected by the business service layer and receiving the inspection results of the direct-sampling data and offline data, and can more accurately reflect the real situation of each related enterprise by calculating the overall scores of each related enterprise based on the stored direct-sampling data and offline data according to the preset rules after receiving the display instruction sent by the data access layer, displaying the overall scores of the related enterprises, and acquiring the direct-sampling data and offline data. The accuracy and reliability of the data are improved by inspecting the direct-sampling data and offline data and only performing subsequent processing when the inspection results meet the inspection passing condition. The orderliness and standardization of data storage are ensured by storing the direct-sampling data and offline data that pass the inspection according to the preset rules, calculating the overall scores of each related enterprise based on the stored direct-sampling data and offline data, facilitating subsequent query and analysis, and providing a unified and objective scoring standard. The problems of inaccurate evaluation, insufficient data timeliness, and poor management in the prior art are solved. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 A flowchart of a peer benchmarking information management method according to an embodiment of the present application is shown in FIG. 1.

[0036] Figure 2 A block diagram of a peer benchmarking information management system according to a third embodiment of the present application is shown in FIG. 4.

[0037] The following detailed description will further illustrate the present application in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0038] For the purposes of promoting an understanding of the principles of the application, reference will now be made to the embodiments illustrated in the drawings. The embodiments shown are intended to be illustrative only and not limiting of the present application. The present application will become more fully understood from the detailed description and embodiments provided below and the appended claims.

[0039] It should be noted that when an element as a "set" in another element, it can be directly on another element or there can be a middle element. When an element is considered to be "connected" to another element, it can be directly connected to another element or there can be a middle element. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0041] Embodiment one

[0042] Please refer to Figure 1 , the first embodiment of the application is shown in the same industry benchmarking information management method, applied to a same industry benchmarking information management platform, the same industry benchmarking information management platform includes business service layer and data access layer and data storage layer are respectively connected with business service layer, the method comprises steps S10~S12.

[0043] Step S10, respectively, the business service layer to collect the same industry benchmarking information about the direct sampling data and offline data, receive the inspection results for direct sampling data and offline data.

[0044] In which, the business service layer for realizing the relevant business functions, such as data collection, data access layer for providing data access interface, data storage layer for storing the relevant data collected, such as direct sampling data and offline data.

[0045] In the business service layer, two types of data will be collected: one is direct acquisition data related to peer benchmarking information obtained through direct means. These data come from automatic collection, interface docking and other direct data acquisition channels, with characteristics of real-time and automation. The other is offline data, which cannot be directly collected from the system. This type of data is collected through manual input, paper file digitization, external data import and other non-automated methods. After collecting these two types of data, the system will receive the test results for direct acquisition data and offline data. These test results are used to determine whether the collected data meets the pre-set standards and requirements, such as data integrity, accuracy, consistency, etc. Through this link, it can ensure that the data for subsequent processing is reliable and effective, providing a basis for subsequent data storage, calculation and display operations.

[0046] Step S11, after the test results of the direct acquisition data and offline data meet the test pass conditions, the direct acquisition data and offline data are stored in the data storage layer according to the pre-set rules.

[0047] Among them, when the direct acquisition data and offline data collected by the business service layer pass the test, the test results meet the pre-set pass standard, and the system will store these data into the data storage layer according to the established rules. The pre-set rules here can include data classification, storage location allocation, etc., the purpose is to ensure that the data can be stored in an orderly and standardized manner, which is convenient for subsequent query, analysis and processing.

[0048] Step S12, after receiving the display instruction sent by the data access layer, the overall score of each related enterprise is calculated according to the pre-set rules for the stored direct acquisition data and offline data, and the overall score of the related enterprise is displayed.

[0049] Specifically, after receiving the display instruction sent by the data access layer, the system will calculate the overall score of each related enterprise according to the pre-set calculation rules for these stored data, where these pre-set rules cover multiple aspects of indicators and weights, such as safety production indicators, management indicators, service quality indicators, etc. Each indicator has its corresponding deduction standard and calculation method. By calculating the deduction of each enterprise according to the rules, the performance of each enterprise in peer benchmarking can be objectively reflected. After obtaining the deduction of each enterprise, the system will further aggregate and calculate to obtain the overall score of each related enterprise.

[0050] Finally, these overall scores are displayed, and the display methods may include but are not limited to presenting in the form of list, chart, etc. on the system interface, so that relevant personnel can intuitively understand the ranking and performance of each enterprise in peer benchmarking, providing strong data support for subsequent decision-making, evaluation and improvement.

[0051] In summary, the same industry benchmark information management method in the above embodiments of the present application, by respectively acquiring the direct collection data and offline data about the same industry benchmark information collected by the business service layer, receiving the test results for the direct collection data and offline data; after the test results of the direct collection data and offline data meet the test pass condition, storing the direct collection data and offline data according to the preset rule in the data storage layer; after receiving the display instruction sent by the data access layer, calculating the overall score of each related enterprise corresponding to the stored direct collection data and offline data according to the preset rule, and displaying the overall score of the related enterprise, and obtaining the direct collection data and offline data, ensuring the comprehensiveness and integrity of the data, which can more accurately reflect the true situation of each related enterprise, and the direct collection data and offline data are tested, only after the test result meets the test pass condition, subsequent processing is performed, which improves the accuracy and reliability of the data, the direct collection data and offline data that pass the test are stored according to the preset rule, the overall score of each related enterprise corresponding to the stored direct collection data and offline data is calculated, the orderliness and standardization of data storage are ensured, which is convenient for subsequent query and analysis, and a unified and objective scoring standard is provided. The problems of being unable to accurately evaluate, insufficient data timeliness and poor management in the prior art when managing the same industry benchmark information are solved.

[0052] Embodiment two

[0053] The same industry benchmark information management method in this embodiment is different from the same industry benchmark information management method in Embodiment One in that:

[0054] The step of storing the direct collection data and offline data according to the preset rule in the data storage layer comprises:

[0055] The direct collection database, the offline database and the intermediate score database for storing the direct collection data and offline data are respectively established in the data storage layer;

[0056] According to the unique identification of the enterprise corresponding to the direct collection data and offline data, the score data for calculating the overall score is extracted from the direct collection data and offline data;

[0057] The direct collection data, offline data and score data are respectively stored in the corresponding collection database, offline database and intermediate score database.

[0058] Firstly, a special database is constructed, which is a direct collection database, an offline database and an intermediate score database, independent storage positions are planned for different types of data to facilitate management and subsequent operation. Specifically, the direct collection database is used to store directly collected direct collection data, the offline database is used to store offline collected offline data, and the intermediate score database is used to store key data information selected from the direct collection data and the offline data, or score information corresponding to each index calculated after the key data information is selected. Thus, subsequent rapid overall score calculation can be realized. After obtaining the corresponding data, different types of data are accurately and orderly stored in the corresponding databases.

[0059] Further, in some optional embodiments of the present application, the step of storing the direct collection data, the offline data and the score data into the corresponding database, the offline database and the intermediate score database respectively further comprises:

[0060] According to the enterprise unique identifier, the direct collection data and the offline data and the score data, a query data chain is constructed, and the query data chain is stored in the intermediate score database;

[0061] When the overall score of the enterprise needs to be calculated, the score data corresponding to the overall score calculation is determined according to the query data chain, and the overall score of the enterprise is determined according to the score data.

[0062] Wherein, after the direct collection data, the offline data and the score data are stored in the corresponding database, the next step is to integrate the direct collection data, the offline data and the score data of the same enterprise to construct a query data chain by using the enterprise unique identifier. After the construction is completed, the query data chain is stored in the intermediate score database. On the one hand, the query data chain is like an index. When the overall score of the enterprise needs to be calculated, the query data chain can be located according to the unique identifier of the enterprise, and then the corresponding score data in the intermediate score database can be located, and the final overall score can be calculated according to the score data. On the other hand, in order to improve the efficiency of score calculation, the intermediate score database is proposed in the embodiment of the present application. Some basic score data is stored in the intermediate score database by filtering and calculating the data, so that the corresponding overall score can be obtained directly by the score data when the score calculation is performed. However, this method improves the calculation efficiency, but also faces a problem, that is, when the data in the intermediate score database is tampered, it is difficult to find that the data has been tampered.

[0063] Therefore, in some optional embodiments of the present application, the step of constructing a query data chain according to the enterprise unique identifier, the direct-sampling data and the offline data, and the score data, and storing the query data chain in the intermediate score database comprises:

[0064] The first hash value and the second hash value are obtained by performing hash operations on the information content of the direct-sampling data and the offline data respectively, and the target hash value is obtained according to the first hash value and the second hash value according to a preset rule, so as to obtain the corresponding target data chain;

[0065] The target data chain is divided into equal parts of target sub-data chains according to a preset rule, and the data ratio between the direct-sampling data and the offline data is obtained, the corresponding elements are selected from the corresponding chain positions of the target sub-data chains according to the data ratio, and the initial data chain is obtained by combining the selected elements and the positions of the target sub-data chains;

[0066] The enterprise unique identifier is used as the chain head to form a query data chain with the initial data chain, and the query data chain is left in the intermediate score database, wherein the query data chain and the data chain composed of the selected elements of the corresponding chain positions are mutually keyed.

[0067] When the query data chain is formed, a data chain that can be mutually keyed with the query data chain is also formed, and when the score query is performed, a latest data chain is generated using the current data according to the same rule, and the data chain and the query data chain are keyed and matched, and only when the keyed and matched is passed, the queried score data is determined to be accurate.

[0068] Specifically, the information content of the direct-sampling data and the offline data is first subjected to hash operation to obtain the first hash value and the second hash value, and then the two hash values are processed according to a specific preset rule to obtain a target hash value, and a corresponding target data chain is generated. Hash operation is an algorithm for converting data of arbitrary length into fixed length value, which is used here to generate a feature identifier for data to ensure data integrity and traceability. For example, the first hash value and the second hash value can be subjected to bitwise XOR operation respectively. Bitwise XOR operation is a kind of logical operation, when the values of two binary bits are different, the result is 1, and when they are the same, the result is 0, a new binary value is obtained through this operation. Then, the same hash algorithm as that used to generate the first and second hash values is used to perform hash calculation on the new binary value again, and finally the target hash value is obtained. Or the first hash value and the second hash value are subjected to confusion splicing and then subjected to hash operation to obtain the target hash value.

[0069] After obtaining the target data chain, the target data chain is divided into equal parts according to a preset rule to obtain a target sub-data chain, and the data ratio between the online data and the offline data is calculated. For example, the data ratio can be obtained according to the ratio of the data amount (such as the number of bytes) of the online data and the offline data, or the ratio of the sum of the values of the indexes contained in the online data and the offline data. In actual implementation, the elements are selected from the corresponding chain positions of the target sub-data chain according to the ratio, and the selected elements are combined to form an initial data chain after the positions of the selected elements are vacated. The unique identifier of the enterprise is taken as the chain head to form a query data chain with the initial data chain, and the query data chain is left in the intermediate scoring database. The query data chain and the data chain composed of the elements selected from the corresponding chain positions are mutually keyed. This is done to reasonably select data segments according to the data ratio, and to vacate positions for subsequent data accuracy and integrity verification.

[0070] The step of obtaining the data ratio between the online data and the offline data and selecting the corresponding elements from the corresponding chain positions of the target sub-data chain according to the data ratio includes:

[0071] According to the data ratio, the target value with a larger value is determined, and the target sub-data chain is segmented according to the ratio corresponding to the target value, or the target value with a smaller value is determined according to the data ratio, and the target sub-data chain is segmented according to the ratio corresponding to the target value.

[0072] The segmented target sub-data chain is segmented again according to the ratio corresponding to another target value, and the segmentation position of each segmentation is obtained, and the corresponding elements are selected from the segmentation position of each segmentation.

[0073] Specifically, assuming that the ratio of the online data and the offline data is 70%:30%, the target sub-data chain can be segmented according to the "70%" or the "30%". When the target sub-data chain is segmented according to the ratio corresponding to the "target value with a larger value (70%)", the target sub-data chain is divided into two parts, and the part with a larger proportion accounts for 70% of the chain length, and the remaining 30% is another part. For example, if the total length of the target sub-data chain is 100 elements, the first 70 elements are divided according to the ratio of 70%, and the last 30 elements are another part. The first 70 elements are used as the target for the next segmentation, and the ratio of 30% is used for segmentation. The segmentation position is recorded after each segmentation, and the corresponding elements are selected from the segmentation positions.

[0074] In addition, in order to further improve the security of the query data chain, when one of the target sub-data chains is initially divided according to one of the target values in the data ratio, the adjacent target sub-data chain is initially divided according to another target value in the data ratio, that is, different division strategies are adopted for multiple target sub-data chains.

[0075] In summary, the same industry benchmark information management method in the above embodiments of the present application, by respectively acquiring the direct collection data and offline data about the same industry benchmark information collected by the business service layer, receiving the test results for the direct collection data and offline data; after the test results of the direct collection data and offline data meet the test pass condition, the direct collection data and offline data are stored in the data storage layer according to the preset rule; after receiving the display instruction sent by the data access layer, the overall score of each related enterprise corresponding to the stored direct collection data and offline data is calculated according to the preset rule, and the overall score of the related enterprise is displayed, and the direct collection data and offline data are acquired, ensuring the comprehensiveness and integrity of the data, which can more accurately reflect the true situation of each related enterprise. The direct collection data and offline data are tested, and only after the test result meets the test pass condition, subsequent processing is performed, which improves the accuracy and reliability of the data. The direct collection data and offline data that pass the test are stored according to the preset rule, and the overall score of each related enterprise corresponding to the stored direct collection data and offline data is calculated, ensuring the orderliness and standardization of data storage, facilitating subsequent query and analysis, and providing a unified and objective scoring standard. The problems of inaccurate evaluation, insufficient data timeliness and lack of management in the prior art are solved.

[0076] Embodiment three

[0077] Please refer to Figure 2 , which is a same industry benchmark information management system proposed in the third embodiment of the present application, applied to a same industry benchmark information management platform, the same industry benchmark information management platform includes a business service layer and a data access layer and a data storage layer which are respectively in communication connection with the business service layer, the system includes:

[0078] The acquisition module 100 is used for respectively acquiring the direct collection data and offline data about the same industry benchmark information collected by the business service layer, and receiving the test results for the direct collection data and offline data;

[0079] The storage module 200 is used for storing the direct collection data and offline data in the data storage layer according to the preset rule after the test results of the direct collection data and offline data meet the test pass condition;

[0080] The display module 300 is used to calculate the overall scores of the corresponding relevant enterprises according to preset rules for the stored direct-purchased data and offline data after receiving the display instruction sent by the data access layer, and to display the overall scores of the relevant enterprises.

[0081] The functions or operation steps implemented when the above modules are executed are substantially the same as those in the above method embodiments and will not be repeated here.

[0082] Example 4

[0083] Another aspect of the present invention further provides a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any one of the above-mentioned embodiments 1 to 2.

[0084] Example 5

[0085] On the other hand, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the program, the steps of the method described in any one of the above-mentioned embodiments 1 to 2 are implemented.

[0086] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0087] Those skilled in the art will appreciate that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device), or for use in conjunction with such instruction execution system, apparatus, or device. For purposes of this specification, a "computer-readable storage medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, apparatus, or device, or in conjunction with such instruction execution system, apparatus, or device.

[0088] More specific examples (a non-exhaustive list) of the computer-readable storage medium include the following: an electrical connection having one or more wires (electrical device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable storage medium can also be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that is then reproducible in a computer.

[0089] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the embodiments described above, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following techniques, which are well known in the art, can be used to implement the application: a hybrid of the techniques mentioned above; a combination of one or more of the techniques mentioned above; or one or more other techniques suitable for use in the computer hardware devices described above.

[0090] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples.

[0091] The above-described embodiments only express several implementation manners of the application, and the description is more specific and detailed, but it should not be understood as a limitation on the patent scope of the application. It should be noted that for those skilled in the art, without departing from the concept of the application, a number of modifications and improvements can be made, which are all within the protection scope of the application. Therefore, the patent protection scope of the application should be subject to the appended claims.

Claims

1. A method for managing peer-to-peer benchmarking information, characterized by, The method is applied to a peer benchmarking information management platform, the peer benchmarking information management platform comprises a business service layer, and a data access layer and a data storage layer which are in communication connection with the business service layer, and the method comprises the following steps: Respectively acquiring straight-sampling data and offline data about peer benchmarking information collected by the business service layer, and receiving inspection results for the straight-sampling data and the offline data; After the inspection results of the straight-sampling data and the offline data meet the inspection passing condition, storing the straight-sampling data and the offline data in the data storage layer according to a preset rule; After receiving a display instruction sent by the data access layer, calculating overall scores of each related enterprise from the stored straight-sampling data and offline data according to a preset rule, and displaying the overall scores of the related enterprises; The step of storing the straight-sampling data and the offline data in the data storage layer according to a preset rule comprises the following steps: Establishing a straight-sampling database, an offline database and an intermediate score database in the data storage layer for respectively storing the straight-sampling data and the offline data; According to the unique identification of the enterprise corresponding to the straight-sampling data and the offline data, extracting score data used for calculating the overall score from the straight-sampling data and the offline data; Storing the straight-sampling data, the offline data and the score data into the corresponding straight-sampling database, offline database and intermediate score database respectively; According to the unique identification of the enterprise, the straight-sampling data and the offline data and the score data, constructing a query data chain, and storing the query data chain into the intermediate score database; When the overall score of the enterprise needs to be calculated, determining the score data used for calculating the overall score according to the query data chain, and determining the overall score of the enterprise according to the score data; The step of constructing a query data chain according to the unique identification of the enterprise, the straight-sampling data and the offline data and the score data, and storing the query data chain into the intermediate score database comprises the following steps: Respectively performing hash operation on the information content of the straight-sampling data and the offline data to obtain a first hash value and a second hash value, obtaining a target hash value according to the first hash value and the second hash value according to a preset rule, so as to obtain a corresponding target data chain; According to a preset rule, the target data chain is divided into equal parts of target sub-data chains, and the data proportion between the straight-sampling data and the offline data is obtained, the corresponding elements are selected from the corresponding chain positions in the target sub-data chains according to the data proportion, and the initial data chain is obtained by combining the positions of the selected elements in the target sub-data chains; The unique identification of the enterprise is taken as the chain head to form a query data chain with the initial data chain, and the query data chain is left in the intermediate score database, wherein the query data chain and the data chain composed of the elements selected from the corresponding chain positions are mutually linked; The step of obtaining the data proportion between the straight-sampling data and the offline data, and selecting the corresponding elements from the corresponding chain positions in the target sub-data chains according to the data proportion comprises the following steps: According to the data proportion, a target value with a larger value is determined, the target sub-data chain is segmented according to the proportion corresponding to the target value, or according to the data proportion, a target value with a smaller value is determined, and the target sub-data chain is segmented according to the proportion corresponding to the target value. According to the proportion corresponding to the target value, the segmented target sub-data chain is segmented again, the segmentation position of each segmentation is obtained, and the corresponding element is selected from the segmentation position of each segmentation; The step of determining the target value with a larger value according to the data proportion, or determining the target value with a smaller value according to the data proportion, and segmenting the target sub-data chain according to the proportion corresponding to the target value, comprises: When one of the target sub-data chains is initially segmented according to one of the target values in the data proportion, the adjacent target sub-data chain is initially segmented according to another target value in the data proportion.

2. The method according to claim 1, wherein The step of obtaining the target hash value according to the first hash value and the second hash value according to the preset rule, to obtain the corresponding target data chain, comprises: The binary representations of the first hash value and the second hash value are subjected to bitwise XOR operation to obtain a new binary value, and the same hash algorithm is used for hash calculation on the binary value after XOR operation to obtain the target hash value.

3. A peer-to-peer benchmarking information management system, characterized by, The system is applied to a peer benchmarking information management platform, the peer benchmarking information management platform comprises a business service layer, a data access layer and a data storage layer which are in communication connection with the business service layer, and is used for realizing the peer benchmarking information management method in any one of claims 1 to 2, and the system comprises: An acquisition module is configured to acquire the direct collection data and the offline data about the peer benchmarking information collected by the business service layer, and receive the inspection results of the direct collection data and the offline data; A storage module is configured to store the direct collection data and the offline data in the data storage layer according to the preset rule when the inspection results of the direct collection data and the offline data meet the inspection passing condition; A display module is configured to calculate the overall scores of the related enterprises according to the preset rule after receiving the display instruction sent by the data access layer, and display the overall scores of the related enterprises.

4. A readable storage medium, having stored thereon a computer program, characterized in that, The program is executed by the processor to realize the steps of the method in any one of claims 1 to 2.

5. An electronic device, comprising: The computer program is stored in the memory and run on the processor, and the processor realizes the steps of the method in any one of claims 1 to 2 when executing the program. The computer program is stored in the memory and run on the processor, and the processor realizes the steps of the method in any one of claims 1 to 2 when executing the program.

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