A Multi-Source Data Feedback Collaboration Method and System Based on a Data Platform

Abstract

This invention discloses a multi-source data feedback collaboration method and system based on a data middle platform, belonging to the field of multi-platform collaboration technology. By coordinating data service commands from external platforms through the data middle platform, and utilizing the response status of data services fed back from the interface, a multi-source feedback status matrix is ​​constructed to capture response behavior characteristics at feedback time points. The consistency of response status codes is tracked and inspected. If inconsistencies in response status codes are found, the feedback latency of the data middle platform is iteratively tracked and analyzed, and an early warning signal is generated and broadcast to each external platform. This invention achieves full-process automation of data collaboration, response behavior capture and quantification, tracking and inspection, consistency analysis, and early warning processing. It can improve the response capability to multi-party services across platforms, enabling faster and more accurate responses to data needs and service requests from third parties, effectively improving the collaboration efficiency, accuracy, and consistency of multi-source data feedback.

Description

Technical Field

[0001] This invention relates to the field of multi-platform collaboration technology, specifically to a multi-source data feedback collaboration method and system based on a data middle platform. Background Technology

[0002] With the rapid development of information technology, the sources of enterprise data are becoming increasingly diversified, including internal systems, external partners, and third-party service providers. This multi-source data environment provides enterprises with abundant information resources, but it also brings challenges to data management and integration. In order to effectively manage and utilize this multi-source data, the concept of a data platform has emerged. As an enterprise-level data asset management platform, the data platform can centrally store, process, and analyze data from different channels, providing strong support for business decision-making.

[0003] In a multi-source data environment, the data platform needs to collaborate with various external platforms to ensure the accuracy and timeliness of the data. However, in practice, due to network latency, system errors, or data inconsistencies, data feedback between the data platform and external platforms may encounter problems. These problems can not only affect the accuracy of the data but may also lead to errors in business decisions.

[0004] Currently, although there are some data collaboration methods on the market, most of them are designed for a single data source or a specific scenario, making it difficult to adapt to the complex needs of multi-source data environments. These methods usually lack a unified data feedback mechanism and cannot effectively capture and respond to the feedback status of various external platforms. In addition, when dealing with data inconsistencies, existing data collaboration methods often adopt simple retry or alarm strategies, lacking in-depth analysis and early warning mechanisms for data platform feedback delays. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-source data feedback and collaboration method and system based on a data middle platform to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] A multi-source data feedback and collaboration system based on a data platform, comprising: a data service module, a response behavior log module, a tracking and inspection module, and an early warning processing module;

[0008] The data service module coordinates with external platforms to generate data service commands through the data middle platform and feeds back the response status of the data service through the interface.

[0009] The response behavior log module, through a triggering protocol mechanism, enables the interface to return a response status code and captures the response behavior characteristics of various external platforms at the feedback time point using a multi-source feedback status matrix.

[0010] The tracking and inspection module is used to quantify the multi-source feedback state matrix at different feedback time nodes by using 0 and 1 as response conditions when capturing response behavior characteristics, and to continuously track and inspect the consistency of the response status code between various external platforms through the interface.

[0011] The early warning processing module is used to lock the tracking representation matrix where the response status code is inconsistent, and analyze and calculate the feedback delay of the data platform through iterative tracking in order to generate an early warning signal and broadcast it to various external platforms.

[0012] Furthermore, the data service module includes an instruction configuration unit and a response status cache unit;

[0013] The instruction configuration unit configures data service instructions based on the data service protocol mechanism. The protocol mechanism is used to implement different data service functions. The data service instructions trigger the protocol mechanism through the interface and realize the data service response.

[0014] The response status caching unit is used to allocate data storage space, which is integrated into the data platform and used to cache the response status of data services from external platforms. The data storage space is connected to the interface configured in the data middle platform, which connects to external platforms and is used to realize data collaboration between external platforms.

[0015] Furthermore, the response behavior log module includes an encoding unit and a response behavior capture unit;

[0016] The encoding unit performs unified encoding on the response status of the interface, the data service, and the external platform through the data middle platform. Each interface corresponds to triggering a protocol mechanism and is used to feed back the response status of a data service. The response status of a data service has a response status code with unique encoding attributes.

[0017] The response behavior capture unit is used to initialize the feedback time node sequence, capture the response status code generated when each protocol mechanism is triggered at each feedback time node, and construct a multi-source feedback status matrix to record the captured response status codes; the row number of the multi-source feedback status matrix is ​​the encoding number of the external platform, and the column number of the multi-source feedback status matrix is ​​the encoding number of the interface end.

[0018] Furthermore, the tracking and inspection module includes a condition quantification unit and a consistency analysis unit;

[0019] The condition quantization unit is used to capture the response status code generated by the external platform fed back by the interface at the feedback time node, and to quantize the response conditions 0 and 1 to obtain the multi-source feedback status matrix at the feedback time node.

[0020] The consistency analysis unit is used to construct a tracking representation model and, through the dynamic flow of feedback time nodes, to represent the tracking behavior of the interface end across various external platforms, so as to determine the consistency of the response status codes fed back by the data platform across various external platforms.

[0021] Furthermore, the early warning processing module includes an iterative tracking unit and an early warning broadcasting unit;

[0022] The iterative tracing unit is used to lock the tracing representation matrix where the response status code is inconsistent, and to analyze and calculate the feedback latency of the data platform through iterative tracing.

[0023] The warning broadcast unit is used to preset a feedback delay threshold. If the feedback delay is greater than or equal to the feedback delay threshold, the data platform generates a warning signal and broadcasts it to each external platform.

[0024] A multi-source data feedback and collaboration method based on a data middle platform, comprising the following steps:

[0025] Step S1: Collaborate with external platforms to generate data service instructions through the data middle platform, and provide feedback on the response status of the data service through the interface.

[0026] Step S2: When the interface sends back a response status code through the trigger protocol mechanism, the response behavior characteristics of each external platform at the feedback time node are captured by the multi-source feedback status matrix.

[0027] Step S3: When capturing response behavior characteristics, 0 and 1 are used as response conditions to quantify the multi-source feedback state matrix under different feedback time nodes, and the consistency of the response status code is continuously tracked and inspected between various external platforms through the interface.

[0028] Step S4: Lock the tracking representation matrix where the response status code is inconsistent. Analyze and calculate the feedback latency of the data platform through iterative tracking to generate an early warning signal and broadcast it to various external platforms.

[0029] Furthermore, the specific implementation process of step S1 includes:

[0030] Based on the data service protocol mechanism, data service instructions are configured. The protocol mechanism is used to implement different data service functions. The data service instructions trigger the protocol mechanism through the interface and realize the data service response.

[0031] The interface is configured in the data platform and connects to external platforms to enable data collaboration between them. The interface also has an internal data storage space, which is integrated into the data platform and used to cache the response status of data services from external platforms.

[0032] Furthermore, the specific implementation process of step S2 includes:

[0033] The data middle platform uses unified encoding to encode the response status of the interface, data service and external platform. Each interface triggers a protocol mechanism and is used to feed back the response status of a data service. The response status of a data service has a unique encoding attribute response status code.

[0034] An initial feedback time node sequence is established. At each feedback time node, the response status codes generated when each protocol mechanism is triggered are captured, and a multi-source feedback status matrix is ​​constructed to record the captured response status codes. The row number of the multi-source feedback status matrix is ​​the encoding number of the external platform, and the column number of the multi-source feedback status matrix is ​​the encoding number of the interface end.

[0035] Furthermore, the specific implementation process of step S3 includes:

[0036] Let E be any i-th external platform. i Let P be any j-th interface. j , will the interface end P j The feedback response status code is denoted as C. j ; at the x-th feedback time node t x If the interface P is captured at that location... j External feedback platform E i The generated response status code C j Let the matrix position r of the i-th row and j-th column of the multi-source feedback state matrix be... ij =1, if interface P is not captured j External feedback platform E i The generated response status code C j Let the matrix position r of the i-th row and j-th column of the multi-source feedback state matrix be... ij =0, thus obtaining the feedback time node t x The multi-source feedback state matrix R(t) x );

[0037] By dynamically shifting the feedback time points, the tracking behavior of the interface across various external platforms is represented, and a tracking representation model is constructed: the dynamically shifting tracking representation matrix RR(t) x )=R(t x )∩R0, where R0 is a matrix of all 1s;

[0038] If RR(t) x If RR(t) = R0, it indicates that the response status codes fed back by the data platform across various external platforms are consistent. x If R0 is not equal to R0, it means that the response status codes fed back by the data platform to various external platforms are inconsistent.

[0039] Furthermore, the specific implementation process of step S4 includes:

[0040] Lock response status codes lack consistent tracking representation matrix RR(t) x The feedback latency of the data platform is analyzed and calculated through iterative tracing.

[0041] Let x = x + 1, return to the tracking representation model, and obtain the dynamically flowing tracking representation matrix RR(t). x+1 If RR(t) x+1 If ) = R0, then iterative tracking stops; if RR(t) = R0, then iterative tracking stops. x+1 If R≠R0, then continue iterative tracing;

[0042] When iterative tracing stops, obtain the y-th feedback time node t at which iterative tracing stops. y And y≠x;

[0043] Calculate the feedback latency of the data platform In the formula, Δt represents the fixed interval between adjacent feedback time nodes, and NUM[RR(t)] x )] represents the tracking representation matrix RR(t) x The number of zeros contained in the )

[0044] A preset feedback delay threshold is set. If the feedback delay is greater than or equal to the feedback delay threshold, the data platform will generate an early warning signal and broadcast it to all external platforms.

[0045] In the above method, the data platform needs to maintain the consistency of data services across various external platforms. The response status code is a concrete representation of consistency. At the current feedback time point, the data service status of each external platform is generated and captured. A value of 1 indicates that the generated data service meets the characteristics of consistency. The all-1 matrix is ​​a judgment matrix used to judge the consistency of the response. When there is 0, it indicates that the response has become inconsistent. The denominator of the feedback delay calculation formula is the number of inconsistencies, while the numerator is the duration of the feedback delay. The larger the feedback delay, the lower the efficiency of data consistency coordination.

[0046] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: This invention provides a multi-source data feedback collaboration method and system based on a data platform. By coordinating data service commands from external platforms through the data platform, and utilizing the response status of data services fed back from the interface, a multi-source feedback status matrix is ​​constructed to capture response behavior characteristics at feedback time points. The consistency of response status codes is tracked and inspected. If inconsistencies in response status codes are found, the feedback latency of the data platform is iteratively tracked and analyzed, and an early warning signal is generated and broadcast to each external platform. This invention achieves full-process automation of data collaboration, response behavior capture and quantification, tracking and inspection, consistency analysis, and early warning processing. It can improve the response capability to multi-party services across platforms, and can respond to data needs and service requests from third parties more quickly and accurately, effectively improving the collaboration efficiency, accuracy, and consistency of multi-source data feedback. Attached Figure Description

[0047] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0048] Figure 1 This is a schematic diagram illustrating the steps of a multi-source data feedback and collaboration method based on a data middle platform according to the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] In this first embodiment: a multi-source data feedback and collaboration system based on a data platform is provided. The system includes: a data service module, a response behavior log module, a tracking and inspection module, and an early warning processing module.

[0051] The data service module coordinates with external platforms to generate data service commands through the data middle platform and feeds back the response status of the data service through the interface.

[0052] The data service module includes an instruction configuration unit and a response status cache unit.

[0053] The instruction configuration unit configures data service instructions based on the data service protocol mechanism. The protocol mechanism is used to implement different data service functions. The data service instructions trigger the protocol mechanism through the interface and realize the data service response.

[0054] The response status caching unit is used to allocate data storage space, which is integrated into the data platform and used to cache the response status of data services from external platforms. The data storage space is connected to the interface configured in the data middle platform, which connects to external platforms and is used to realize data collaboration between external platforms.

[0055] The response behavior log module, through a triggering protocol mechanism, enables the interface to return a response status code and captures the response behavior characteristics of various external platforms at the feedback time point using a multi-source feedback status matrix.

[0056] The response behavior log module includes an encoding unit and a response behavior capture unit;

[0057] The encoding unit performs unified encoding on the response status of the interface, the data service, and the external platform through the data middle platform. Each interface corresponds to triggering a protocol mechanism and is used to feed back the response status of a data service. The response status of a data service has a response status code with unique encoding attributes.

[0058] The response behavior capture unit is used to initialize the feedback time node sequence, capture the response status code generated when each protocol mechanism is triggered at each feedback time node, and construct a multi-source feedback status matrix to record the captured response status codes; the row number of the multi-source feedback status matrix is ​​the encoding number of the external platform, and the column number of the multi-source feedback status matrix is ​​the encoding number of the interface end.

[0059] The tracking and inspection module is used to quantify the multi-source feedback state matrix at different feedback time nodes by using 0 and 1 as response conditions when capturing response behavior characteristics, and to continuously track and inspect the consistency of the response status code between various external platforms through the interface.

[0060] The tracking and inspection module includes a condition quantification unit and a consistency analysis unit.

[0061] The condition quantization unit is used to capture the response status code generated by the external platform fed back by the interface at the feedback time node, and to quantize the response conditions 0 and 1 to obtain the multi-source feedback status matrix at the feedback time node.

[0062] The consistency analysis unit is used to construct a tracking representation model and, through the dynamic flow of feedback time nodes, to represent the tracking behavior of the interface end across various external platforms, so as to determine the consistency of the response status codes fed back by the data platform across various external platforms.

[0063] The early warning processing module is used to lock the tracking representation matrix where the response status code is inconsistent, and analyze and calculate the feedback delay of the data platform through iterative tracking in order to generate an early warning signal and broadcast it to various external platforms.

[0064] The early warning processing module includes an iterative tracking unit and an early warning broadcasting unit;

[0065] The iterative tracing unit is used to lock the tracing representation matrix where the response status code is inconsistent, and to analyze and calculate the feedback latency of the data platform through iterative tracing.

[0066] The warning broadcast unit is used to preset a feedback delay threshold. If the feedback delay is greater than or equal to the feedback delay threshold, the data platform generates a warning signal and broadcasts it to each external platform.

[0067] Please see Figure 1 In this second embodiment: a multi-source data feedback collaboration method based on a data platform is provided for application in the first embodiment above. The method includes the following steps:

[0068] Step S1: Collaborate with external platforms to generate data service instructions through the data middle platform, and provide feedback on the response status of the data service through the interface.

[0069] For example, based on the protocol mechanism of the data service, a data service instruction is configured. The protocol mechanism is used to implement different data service functions. The data service instruction triggers the protocol mechanism through the interface and realizes the response of the data service.

[0070] The interface is configured in the data platform and connects to external platforms to enable data collaboration between them. The interface also has an internal data storage space, which is integrated into the data platform and used to cache the response status of data services from external platforms.

[0071] Step S2: When the interface sends back a response status code through the trigger protocol mechanism, the response behavior characteristics of each external platform at the feedback time node are captured by the multi-source feedback status matrix.

[0072] For example, the response status of the interface, the data service, and the external platform are uniformly encoded through the data middle platform. Each interface corresponds to triggering a protocol mechanism and is used to feed back the response status of a data service. The response status of a data service has a response status code with a unique encoding attribute.

[0073] An initial feedback time node sequence is established. At each feedback time node, the response status codes generated when each protocol mechanism is triggered are captured, and a multi-source feedback status matrix is ​​constructed to record the captured response status codes. The row number of the multi-source feedback status matrix is ​​the encoding number of the external platform, and the column number of the multi-source feedback status matrix is ​​the encoding number of the interface end.

[0074] Step S3: When capturing response behavior characteristics, 0 and 1 are used as response conditions to quantify the multi-source feedback state matrix under different feedback time nodes, and the consistency of the response status code is continuously tracked and inspected between various external platforms through the interface.

[0075] For example, let any i-th external platform be denoted as E. i Let P be any j-th interface. j , will the interface end P j The feedback response status code is denoted as C. j ; at the x-th feedback time node t x If the interface P is captured at that location... j External feedback platform E i The generated response status code C j Let the matrix position r of the i-th row and j-th column of the multi-source feedback state matrix be... ij =1, if interface P is not captured j External feedback platform E i The generated response status code C j Let the matrix position r of the i-th row and j-th column of the multi-source feedback state matrix be... ij =0, thus obtaining the feedback time node t x The multi-source feedback state matrix R(t) x );

[0076] By dynamically shifting the feedback time points, the tracking behavior of the interface across various external platforms is represented, and a tracking representation model is constructed: the dynamically shifting tracking representation matrix RR(t) x )=R(t x )∩R0, where R0 is a matrix of all 1s;

[0077] If RR(t) x If RR(t) = R0, it indicates that the response status codes fed back by the data platform across various external platforms are consistent. x If R0 is not equal to R0, it means that the response status codes fed back by the data platform to various external platforms are inconsistent.

[0078] Step S4: Lock the tracking representation matrix where the response status code is inconsistent, analyze and calculate the feedback latency of the data platform through iterative tracking, so as to generate an early warning signal and broadcast it to each external platform;

[0079] For example, the lock response status code does not have a consistent tracking representation matrix RR(t) x The feedback latency of the data platform is analyzed and calculated through iterative tracing.

[0080] Let x = x + 1, return to the tracking representation model, and obtain the dynamically flowing tracking representation matrix RR(t). x+1 If RR(t) x+1 If ) = R0, then iterative tracking stops; if RR(t) = R0, then iterative tracking stops. x+1 If R≠R0, then continue iterative tracing;

[0081] When iterative tracing stops, obtain the y-th feedback time node t at which iterative tracing stops. y And y≠x;

[0082] Calculate the feedback latency of the data platform In the formula, Δt represents the fixed interval between adjacent feedback time nodes, and NUM[RR(t)] x )] represents the tracking representation matrix RR(t) x The number of zeros contained in the )

[0083] A preset feedback delay threshold is set. If the feedback delay is greater than or equal to the feedback delay threshold, the data platform will generate an early warning signal and broadcast it to all external platforms.

[0084] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0085] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-source data feedback and collaboration method based on a data platform, characterized in that, The method includes the following steps: Step S1: Collaborate with external platforms to generate data service instructions through the data middle platform, and provide feedback on the response status of the data service through the interface. Step S2: When the interface sends back a response status code through the trigger protocol mechanism, the response behavior characteristics of each external platform at the feedback time node are captured by the multi-source feedback status matrix. Step S3: When capturing response behavior characteristics, 0 and 1 are used as response conditions to quantify the multi-source feedback state matrix under different feedback time nodes, and the consistency of the response status code is continuously tracked and inspected between various external platforms through the interface. Step S4: Lock the tracking representation matrix where the response status code is inconsistent, analyze and calculate the feedback latency of the data platform through iterative tracking, so as to generate an early warning signal and broadcast it to each external platform; The specific implementation process of step S2 includes: The data middle platform uses unified encoding to encode the response status of the interface, data service and external platform. Each interface triggers a protocol mechanism and is used to feed back the response status of a data service. The response status of a data service has a unique encoding attribute response status code. Initialize the feedback time node sequence, capture the response status code generated when each protocol mechanism is triggered at each feedback time node, and construct a multi-source feedback status matrix to record the captured response status codes; the row number of the multi-source feedback status matrix is ​​the encoding number of the external platform, and the column number of the multi-source feedback status matrix is ​​the encoding number of the interface end. The specific implementation process of step S3 includes: Let E be any i-th external platform. i Let P be any j-th interface. j , will the interface end P j The feedback response status code is denoted as C. j ; at the x-th feedback time node t x If the interface P is captured at that location... j External feedback platform E i The generated response status code C j Let the matrix position r of the i-th row and j-th column of the multi-source feedback state matrix be... ij =1, if interface P is not captured j External feedback platform E i The generated response status code C j Let the matrix position r of the i-th row and j-th column of the multi-source feedback state matrix be... ij =0, thus obtaining the feedback time node t x The multi-source feedback state matrix R(t) x ); By dynamically shifting the feedback time points, the tracking behavior of the interface across various external platforms is represented, and a tracking representation model is constructed: the dynamically shifting tracking representation matrix RR(t) x )=R(t x )∩R0, where R0 is a matrix of all 1s; If RR(t) x If RR(t) = R0, it indicates that the response status codes fed back by the data platform across various external platforms are consistent. x If R0 is not equal to R0, it means that the response status codes fed back by the data platform across various external platforms are inconsistent. The specific implementation process of step S4 includes: Lock response status codes lack consistent tracking representation matrix RR(t) x The feedback latency of the data platform is analyzed and calculated through iterative tracing. Let x = x + 1, return to the tracking representation model, and obtain the dynamically flowing tracking representation matrix RR(t). x+1 If RR(t) x+1 If ) = R0, then iterative tracking stops; if RR(t) = R0, then iterative tracking stops. x+1 If R≠R0, then continue iterative tracing; When iterative tracing stops, obtain the y-th feedback time node t at which iterative tracing stops. y And y≠x; Calculate the feedback latency of the data platform In the formula, Δt represents the fixed interval between adjacent feedback time nodes, and NUM[RR(t)] x )] represents the tracking representation matrix RR(t) x The number of zeros contained in the ) A preset feedback delay threshold is set. If the feedback delay is greater than or equal to the feedback delay threshold, the data platform will generate an early warning signal and broadcast it to all external platforms.

2. The multi-source data feedback and collaboration method based on a data platform according to claim 1, characterized in that, The specific implementation process of step S1 includes: Based on the data service protocol mechanism, data service instructions are configured. The protocol mechanism is used to implement different data service functions. The data service instructions trigger the protocol mechanism through the interface and realize the data service response. The interface is configured in the data platform and connects to external platforms to enable data collaboration between them. The interface also has an internal data storage space, which is integrated into the data platform and used to cache the response status of data services from external platforms.

3. A multi-source data feedback collaboration system based on a data platform, executing the multi-source data feedback collaboration method based on a data platform as described in any one of claims 1-2, characterized in that, The system includes: a data service module, a response behavior log module, a tracking and inspection module, and an early warning processing module; The data service module coordinates with external platforms to generate data service commands through the data middle platform and feeds back the response status of the data service through the interface. The response behavior log module, through a triggering protocol mechanism, enables the interface to return a response status code and captures the response behavior characteristics of various external platforms at the feedback time point using a multi-source feedback status matrix. The tracking and inspection module is used to quantify the multi-source feedback state matrix at different feedback time nodes by using 0 and 1 as response conditions when capturing response behavior characteristics, and to continuously track and inspect the consistency of the response status code between various external platforms through the interface. The early warning processing module is used to lock the tracking representation matrix where the response status code is inconsistent, and analyze and calculate the feedback delay of the data platform through iterative tracking in order to generate an early warning signal and broadcast it to various external platforms.

4. The multi-source data feedback and collaboration system based on a data platform according to claim 3, characterized in that, The data service module includes an instruction configuration unit and a response status cache unit; The instruction configuration unit configures data service instructions based on the data service protocol mechanism. The protocol mechanism is used to implement different data service functions. The data service instructions trigger the protocol mechanism through the interface and realize the data service response. The response status caching unit is used to allocate data storage space, which is integrated into the data platform and used to cache the response status of data services from external platforms. The data storage space is connected to the interface configured in the data middle platform, which connects to external platforms and is used to realize data collaboration between external platforms.

5. A multi-source data feedback and collaboration system based on a data platform according to claim 3, characterized in that, The response behavior log module includes an encoding unit and a response behavior capture unit; The encoding unit performs unified encoding on the response status of the interface, the data service, and the external platform through the data middle platform. Each interface corresponds to triggering a protocol mechanism and is used to feed back the response status of a data service. The response status of a data service has a response status code with unique encoding attributes. The response behavior capture unit is used to initialize the feedback time node sequence, capture the response status code generated when each protocol mechanism is triggered at each feedback time node, and construct a multi-source feedback status matrix to record the captured response status codes; the row number of the multi-source feedback status matrix is ​​the encoding number of the external platform, and the column number of the multi-source feedback status matrix is ​​the encoding number of the interface end.

6. A multi-source data feedback and collaboration system based on a data platform according to claim 3, characterized in that, The tracking and inspection module includes a condition quantification unit and a consistency analysis unit; The condition quantization unit is used to capture the response status code generated by the external platform fed back by the interface at the feedback time node, and to quantize the response conditions 0 and 1 to obtain the multi-source feedback status matrix at the feedback time node. The consistency analysis unit is used to construct a tracking representation model and, through the dynamic flow of feedback time nodes, to represent the tracking behavior of the interface end across various external platforms, so as to determine the consistency of the response status codes fed back by the data platform across various external platforms.

7. A multi-source data feedback and collaboration system based on a data platform according to claim 3, characterized in that, The early warning processing module includes an iterative tracking unit and an early warning broadcasting unit; The iterative tracing unit is used to lock the tracing representation matrix where the response status code is inconsistent, and to analyze and calculate the feedback latency of the data platform through iterative tracing. The warning broadcast unit is used to preset a feedback delay threshold. If the feedback delay is greater than or equal to the feedback delay threshold, the data platform generates a warning signal and broadcasts it to each external platform.

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