Data processing method and device

Abstract

The data processing method comprises the steps that a client detects that a user triggers a target event; and the client sends a first message to the server, the first message comprises total user behavior data which is dotted by the client and is related to the target event, and the first message is used for indicating the server to carry out data analysis based on the user behavior data. Therefore, due to the fact that the client reports full data, the client does not need to be used for development in the data analysis process, complete data is reported before, the problem of compatibility of new and old versions of the client does not need to be worried about with zero development cost, and meanwhile dotting reporting logic does not need to be modified.

Description

Technical Field

[0001] This application relates to the field of information technology (IT), and particularly to a data processing method and apparatus. Background Art

[0002] Currently, there are more and more scenarios based on client logging and reporting and using big data systems for analysis. Big data analysis can support refined user operation management, discover key growth points of business, and improve enterprise efficiency. Currently, data analysis and logging and reporting have strong requirements for data formats. When a specific event that requires data reporting occurs on the client, the data reporting must be in the key-value format. After reporting the event, it must be registered in the management console of the big data system before it can be recognized by the system and finally used for data analysis. The process follows the way of "event reporting" - "event registration" - "data analysis" to complete. Among them, the specific information in the key-value format reported by the client mainly needs to include: event name and meaning, meaning of the key, and type of the value (integer, double, string). In this mode, if you want to add a new logging or data embedding logic on the client, you must modify the logic to report a new field, which involves code development and requires a long time cycle. At the same time, the client will involve the issues of old versions and new versions. The old version will not contain the newly reported field because the requirements for data embedding are generally submitted after the business requirements. Usually, a long time after a business feature is implemented, big data statistics will be performed on this feature. At this time, the old version client cannot collect the fields of the new version client, which will cause the problem that the data of the old version client cannot be collected all the time and the data statistics are inaccurate. Therefore, how to reduce the logic modification of client logging and reporting in the data analysis system is a technical problem that needs to be solved urgently at present. Summary of the Invention

[0003] This application provides a data processing method, apparatus, computing device cluster, computer storage medium, and computer product, which can reduce the logic modification of client logging and reporting in the data analysis system.

[0004] In a first aspect, the present application provides a data processing method, including: the client detects that the user triggers a target event; the client sends a first message to the server, and the first message includes: all user behavior data related to the target event marked by the client, and the first message is used to instruct the server to perform data analysis based on the user behavior data. In this way, since the client reports all data, during the data analysis process, there is no need to rely on client development anymore, because the complete data has been reported before, there is no development cost, and there is no need to worry about compatibility issues between new and old versions of the client. At the same time, there is no need to modify the marking and reporting logic.

[0005] In a possible implementation, the message format of the first message is JSON format.

[0006] In a second aspect, the present application provides a data processing method, including: the server receives the first message sent by the client, and the first message includes: all user behavior data related to the target event marked by the client; the server uses the configuration data of the metadata in the data dashboard on the data management platform as a query statement to query in the user behavior data to obtain a query result; the server sends a second message to the data management platform, and the second message includes: the query result, and the second message is used to instruct the data management platform to display the query result on the data dashboard.

[0007] In this way, since the client reports all data, during the data analysis process, there is no need to rely on client development anymore, because the complete data has been reported before, there is no development cost, and there is no need to worry about compatibility issues between new and old versions of the client. At the same time, the data analysis is automatically calculated based on the metadata of the data dashboard on the data management platform and the data reported by the client. Therefore, there is no need for customized development, and the analysis result can be generated immediately, improving the data analysis efficiency. In addition, when it is necessary to view a newly added event, only the metadata of the newly added event needs to be added to the data dashboard on the data management platform. After that, the server can quickly return the analysis result related to the newly added event without the need for developers to customize and develop again.

[0008] In a possible implementation, before the server uses the configuration data of the metadata in the data dashboard on the data management platform as a query statement to query in the user behavior data, it further includes: the server receives a third message sent by the data management platform, and the third message includes: the configuration data of the metadata in the data dashboard. In this way, the configuration data of the metadata in the data dashboard can be obtained, which is convenient for subsequent data query.

[0009] In a possible implementation, the third message is sent when the metadata in the data dashboard is modified. In this way, the server can perform data query with the latest configuration data, improving the accuracy of data query.

[0010] In a possible implementation, the metadata includes: events, attributes, and metrics.

[0011] In a third aspect, the present application provides a data processing device. The data processing device can be deployed on a client. The data processing device includes: a detection module and a communication module. Among them, the detection module is used to detect that a user triggers a target event. The communication module is used to send a first message to the server. The first message includes: all user behavior data related to the target event and captured by the client. The first message is used to instruct the server to perform data analysis based on the user behavior data.

[0012] In a possible implementation, the message format of the first message is JSON format.

[0013] In a fourth aspect, the present application provides a data processing device. The data processing device can be deployed on a server. The data processing device includes: a communication module and a processing module. Among them, the communication module is used to receive the first message sent by the client. The first message includes: all user behavior data related to the target event and captured by the client. The processing module is used to use the configuration data of the metadata in the data dashboard on the data management platform as a query statement to query in the user behavior data to obtain a query result. The communication module is further used to send a second message to the data management platform. The second message includes: the query result. The second message is used to instruct the data management platform to display the query result on the data dashboard.

[0014] In a possible implementation, before the processing module uses the configuration data of the metadata in the data dashboard on the data management platform as a query statement to query in the user behavior data, the communication module is further used to: receive a third message sent by the data management platform. The third message includes: the configuration data of the metadata in the data dashboard.

[0015] In a possible implementation, the third message is sent when the metadata in the data dashboard is modified.

[0016] In a possible implementation, the metadata includes: events, attributes, and metrics.

[0017] In a fourth aspect, the present application provides a data processing device, including: at least one memory for storing a program; at least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or the second aspect.

[0018] In a fifth aspect, the present application provides a computer storage medium. Instructions are stored in the computer storage medium. When the instructions run on a computing device, the computing device is caused to execute the method described in the first aspect or the second aspect.

[0019] In a sixth aspect, the present application provides a computer program product which, when running on a computing device, causes the computing device to execute the method described in the first aspect or the second aspect.

[0020] It can be understood that for the beneficial effects of the above third aspect to the sixth aspect, reference can be made to the relevant descriptions in the first aspect above, and details are not elaborated herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a schematic structural diagram of a data analysis system provided by an embodiment of the present application;

[0022] Figure 2 is a schematic diagram of the working process of a data analysis system provided by an embodiment of the present application;

[0023] Figure 3 is a schematic flowchart of a data processing method provided by an embodiment of the present application;

[0024] Figure 4 is a schematic structural diagram of a data processing device provided by an embodiment of the present application;

[0025] Figure 5 is a schematic structural diagram of a data processing device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] As used herein, the term "and / or" describes the association relationship between associated objects and indicates that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The symbol " / " herein represents an "or" relationship between associated objects. For example, A / B represents A or B.

[0027] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish different objects, rather than to describe a specific order of the objects. For example, the first response message and the second response message are used to distinguish different response messages, rather than to describe the specific order of the response messages.

[0028] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0029] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality of" refers to two or more. For example, a plurality of processing units refers to two or more processing units, etc.; a plurality of components refers to two or more components, etc.

[0030] Exemplarily, Figure 1 The schematic diagram of the architecture of a data analysis system provided by an embodiment of the present application is shown. As Figure 1 shown, the data analysis system may include: a user device 100, a management device 200, and a server 300. Both the user device 100 and the management device 200 are communicatively connected to the server 300 through a network.

[0031] A client 110 is configured in the user device 100. The client 110 may be a desktop application, a mobile application, a Web application, or a Web-based application, etc. The user may use the client 110 on the user device 100. During the process of the user using the client 110, when the user triggers an event corresponding to a certain data point in the client 110, such as clicking on a certain advertisement, etc., with the permission of the user and the law, the client 110 may collect the user's behavior data and perform data patching on the collected behavior events to obtain all the behavior data related to this event. Exemplarily, a software development kit (SDK) may be configured in the client 110. The client 110 may call the SDK to patch all the user behavior data collected by the client 110 in a specific format (such as Json format, etc.) to obtain the behavior data related to the event and in full quantity. Among them, the patching behavior of the client 110 may be, but is not limited to, understood as calling the application programming interface (API) provided by the SDK to pass the data in a specific format into the API. After the client 110 patches the behavior data related to a specific event and in full quantity, these data may be transmitted to the server 300 so that the server 300 can obtain all the detailed data when a certain event is triggered. In some embodiments, for performance considerations, the client 110 may first cache the behavior data related to a specific event and in full quantity locally and periodically transmit these behavior data to the server 300 to reduce the frequency of interface calls on the server 300 side. Exemplarily, the user device 100 may be one or more. When there are multiple user devices 100, different users may use the client 110 on different user devices 100.

[0032] The management device 200 is configured with a data management platform 210. The data management platform 210 can also be a desktop application, a mobile application, a web application, or a web-based application, etc. The manager can log in to the data management platform 210 on the management device 200 and configure the metadata on the data dashboard of the data management platform 210. Among them, the data dashboard is a visualization tool used to present and monitor key business indicators and other important data indicators. The purpose of the data dashboard is to present complex data in an easy-to-understand and analyze form through charts, graphs, tables, etc. The metadata on the data dashboard can include: events, attributes, and metrics. An attribute is a specific description of an event. A metric is a measurement under a certain event behavior, which is an indivisible metric in the business definition, generally a business process + measurement, and also includes derivative atomic metrics, supporting the addition of derivative words before the measurement; such as: payment amount, number of songs played, etc. Through the metadata on the data dashboard, the name, description, number, etc. of an event can be defined, and also, which specific attributes are included in an event can be defined. For example, in the play event, there can be the name of the played movie, play time, user name of the play, etc. At the same time, the metrics for analyzing an event are defined. It should be understood that the metadata configured by the manager should be mapped to one or more fields in the behavior data reported by the client 110 so that the server 300 can analyze the behavior data based on the metadata. After the manager completes the configuration of the metadata on the data dashboard of the data management platform 210, the data management platform 210 can reassemble the page elements based on the metadata configured by the manager, drag the metadata to form cards, and assemble the cards into a data dashboard, and report the configuration information on the data dashboard to the server 300. In addition, the data management platform 210 can also receive the data calculation results transmitted by the server 300 and present the data calculation results on the data dashboard thereon. In this way, the manager or other personnel can understand the statistical analysis results through the data dashboard, and thus can guide subsequent operation activities.

[0033] The server 300 is mainly responsible for receiving the full amount of behavior data related to specific events reported by the client 110, and aggregating the behavior data of the same category reported by different clients 110 to complete the classification of the behavior data for subsequent data analysis. Exemplarily, the server 300 can be, but is not limited to, a cloud server. Additionally, the server 300 can also receive the configuration data of the data dashboard of the data management platform 310 reported by the management device 200. Further, the server 300 can use the configuration data as a query statement to query in the user behavior data it stores and return the query results to the data management platform 310 to display the query results on the data dashboard of the data management platform 310. For example, it can display the trend of a specific event, the details of a certain metric, etc.

[0034] The above is the introduction to the data analysis system provided in this embodiment. For ease of understanding, the working process of this data analysis system will be introduced below.

[0035] Exemplarily, as Figure 2 shown, the working process of this data analysis system mainly involves the end - side, the cloud - side, and the data management platform side. Among them, the end - side is the data logging and reporting process, the cloud - side is the data processing process, and the data management platform side is the data management configuration and viewing process. These processes will be introduced separately below.

[0036] a) Data logging and reporting process

[0037] 1.1. The user logs in on the client.

[0038] 1.2. The user performs various actual behaviors using the client. For example, after the user logs in to a certain video client, the user may play a certain movie, may click on a certain promotional poster or advertisement, and may purchase a one - month video membership. Such behaviors are all individual events.

[0039] 1.3. When a specific event occurs, the client calls the SDK to log the data in Json format with all the information that the client can collect. Among them, the logging behavior is to call the API provided by the SDK to pass the Json - formatted data into the API.

[0040] 1.4. For performance considerations, the data logging behavior directly generated by the user can be cached locally on the client first and then reported to the cloud - side once every minute to reduce the frequency of calling the cloud - side interface.

[0041] b) Data processing process

[0042] 2.1. The cloud side aggregates the behavior data of the same category reported by different clients. The aggregation is divided into real-time aggregation and offline aggregation. Real-time aggregation requires higher timeliness but consumes more performance, and performs operations in real time at all times; offline aggregation has lower requirements for timeliness and can be calculated during the idle time of the system at 0:00 every day, consuming less performance.

[0043] 2.2. After the data aggregated on the cloud side meets the security and privacy requirements, it can be stored separately according to different services. Among them, the data can be stored in the big data database on the cloud side (such as: Clickhouse database).

[0044] 2.3. After the cloud side obtains the configuration data reported by the data management platform, it can use the configuration data as a query statement to query in the user behavior data it stores and return the query results to the data management platform.

[0045] c) Data management configuration and viewing process

[0046] 3.1. The administrator can log in to the data analysis system provided by the data management platform using a username and password. Among them, the administrator has the permission to configure the metadata of the data dashboard in the data management platform, such as: can add or delete the content in the data dashboard.

[0047] 3.2. The administrator configures the events, attributes, and metrics of the metadata in the data dashboard according to the requirements of the product manager or operation manager. Among them, when configuring, it needs to be mapped to one or more fields in the Json structure reported by the client.

[0048] 3.3. The data management platform reassembles the page elements based on the above metadata, drags the metadata to form cards, and assembles the cards into a data dashboard.

[0049] 3.4. The data management platform reports the configuration data in the data dashboard to the cloud side.

[0050] 3.5. After the data management platform obtains the query results returned by the cloud side, it can display these results on the page shown in the data dashboard. In this way, the operator or administrator can log in to the data management platform to view the query results and perform statistical analysis and viewing of the data to guide subsequent operation activities.

[0051] The above is the introduction to the data analysis system provided in this embodiment and the working process of this system. Based on the above content, the embodiment of the present application also provides a data processing method.

[0052] Exemplarily, Figure 3 shows a schematic flowchart of a data processing method provided by an embodiment of the present application. As Figure 3As shown in the figure, the data processing method may include the following steps:

[0053] S301. The data management platform obtains the configuration operation of the metadata of the data dashboard on the platform by the administrator. Among them, the administrator can log in to the data management platform through the username and password and configure the metadata in the data dashboard. The metadata may include: events, attributes, and metrics. In addition, the user can choose to add or delete metadata. Exemplarily, the configuration operation may be, but is not limited to, understood as an operation for registering events.

[0054] S302. The data management platform reassembles the data dashboard based on the administrator's configuration of the metadata. After the administrator completes the configuration, the data management platform can reassemble the data dashboard. For example, when the administrator adds a piece of metadata, the data management platform can insert the display area corresponding to the metadata on the data dashboard, or when the administrator deletes a piece of metadata, the data management platform can delete the display area corresponding to the metadata on the data dashboard.

[0055] S303. The data management platform sends a first message to the server, and the first message includes the configuration data of the metadata in the data dashboard.

[0056] S304. The client detects that the user triggers a target event. During the user's use of the client, when an event corresponding to a certain data point on the client is triggered, the client can determine that it has detected that the user has triggered a target event. Exemplarily, the target event may be, but is not limited to, any event corresponding to a data point.

[0057] S305. The client sends a second message to the server, and the second message includes all the user behavior data related to the target event. Exemplarily, when the target event is triggered, the client can, with the permission of the user and the law, record all the detailed data of the user's behavior when the target event is triggered and send the recorded detailed data to the server.

[0058] S306. The server uses the configuration data of the metadata in the data dashboard on the data management platform as a query statement to query the user behavior data it has obtained to obtain a query result.

[0059] S307. The server sends a third message to the data management platform, and the third message includes the query result.

[0060] S308. The data management platform displays the query result in the data dashboard.

[0061] In this way, since the client reports all data, there is no need to rely on client development during the data analysis process because the complete data has been reported previously, and there is no need to worry about the compatibility issues between new and old versions of the client with zero development cost. At the same time, the data analysis is automatically calculated based on the metadata of the data dashboard on the data management platform and the data reported by the client. Therefore, there is no need for custom development, and the analysis results can be generated immediately, improving the data analysis efficiency. In addition, when it is necessary to view a newly added event, only the metadata of the newly added event needs to be added to the data dashboard on the data management platform. After that, the server can quickly return the analysis results related to the newly added event without the need for developers to perform custom development again.

[0062] It can be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not indicate the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. In addition, the various embodiments described above can be combined according to actual situations, and the combined solutions are still within the protection scope of the present application.

[0063] Based on the method in the above embodiments, the embodiments of the present application further provide a data processing device.

[0064] Exemplarily, Figure 4 FIG. shows a schematic structural diagram of a data processing device provided by an embodiment of the present application. The data processing device may be but is not limited to being deployed in the aforementioned client. As Figure 4 shown, the data processing device 400 includes: a detection module 401 and a communication module 402. Among them, the detection module 401 is used to detect that the user triggers a target event. The communication module 402 is used to send a first message to the server. The first message includes: all user behavior data related to the target event logged by the client. The first message is used to instruct the server to perform data analysis based on the user behavior data.

[0065] In some embodiments, the message format of the first message is the JSON format.

[0066] It should be understood that the above device is used to execute the method in the above embodiments. For the corresponding program modules in the device, their implementation principles and technical effects are similar to those described in the above method. The working process of the device can refer to the corresponding process in the above method, which will not be elaborated here.

[0067] Exemplarily, Figure 5 FIG. shows a schematic structural diagram of a data processing device provided by an embodiment of the present application. The data processing device may be but is not limited to being deployed in the aforementioned server. As Figure 5As shown in the figure, the data processing device 500 includes: a communication module 501 and a processing module 502. Among them, the communication module 501 is used to receive a first message sent by a client, and the first message includes: all user behavior data related to a target event and marked by the client. The processing module 502 is used to query in the user behavior data with the configuration data of the metadata on the data dashboard of the data management platform as a query statement to obtain a query result. The communication module 501 is also used to send a second message to the data management platform, and the second message includes: the query result, and the second message is used to instruct the data management platform to display the query result on the data dashboard. Exemplarily, the message format of the first message may be JSON format.

[0068] In some embodiments, before the processing module queries in the user behavior data with the configuration data of the metadata on the data dashboard of the data management platform as a query statement, the communication module 501 is also used to: receive a third message sent by the data management platform, and the third message includes: the configuration data of the metadata on the data dashboard.

[0069] In some embodiments, the third message is sent when the metadata on the data dashboard is modified.

[0070] In some embodiments, the metadata includes: events, attributes, and metrics.

[0071] It should be understood that the above device is used to execute the method in the above embodiments. For the corresponding program modules in the device, their implementation principles and technical effects are similar to those described in the above method. The working process of the device can refer to the corresponding process in the above method, which will not be elaborated here.

[0072] Based on the method in the above embodiments, an embodiment of the present application provides a data processing device. The data processing device may include: at least one memory for storing a program; at least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method executed by the client or the server described in the above embodiments.

[0073] Based on the method in the above embodiments, an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program runs on a computing device, it causes the computing device to execute the method executed by the client or the server described in the above embodiments. Exemplarily, the computer-readable storage medium may be any available medium that the computing device can store or a data storage device such as a data center containing one or more available media. The available medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state drive), etc.

[0074] Based on the method in the above embodiments, an embodiment of the present application provides a computer program product including instructions. When the computer program product runs on a computing device, it causes the computing device cluster to execute the methods performed by the client or the server described in the above embodiments.

[0075] It can be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0076] The method steps in the embodiments of the present application may be implemented in a hardware manner or by a processor executing software instructions. The software instructions may be composed of corresponding software modules, and the software modules may be stored in a random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, removable hard disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may be located in an ASIC.

[0077] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0078] It can be understood that the various numerical numbers involved in the embodiments of the present application are only for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or equivalently replace some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A data processing method, characterized in that, it includes: The client detects that the user triggers a target event; The client sends a first message to the server, and the first message includes: all user behavior data related to the target event and marked by the client, and the first message is used to instruct the server to perform data analysis based on the user behavior data.

2. The method according to claim 1, characterized in that, The message format of the first message is JSON format.

3. A data processing method, characterized in that, it includes: The server receives the first message sent by the client, and the first message includes: all user behavior data related to the target event and marked by the client; The server queries in the user behavior data using the configuration data of the metadata in the data dashboard on the data management platform as a query statement to obtain a query result; The server sends a second message to the data management platform, and the second message includes: the query result, and the second message is used to instruct the data management platform to display the query result on the data dashboard.

4. The method according to claim 3, characterized in that, Before the server queries in the user behavior data using the configuration data of the metadata in the data dashboard on the data management platform as a query statement, it further includes: The server receives a third message sent by the data management platform, and the third message includes: the configuration data of the metadata in the data dashboard.

5. The method according to claim 4, characterized in that, The third message is sent when the metadata in the data dashboard is modified.

6. The method according to any one of claims 3-5, characterized in that, The metadata includes: events, attributes, and metrics.

7. A data processing device, characterized in that, Deployed on the client, it includes: A detection module for detecting that the user triggers a target event; A communication module for sending a first message to the server, and the first message includes: all user behavior data related to the target event and marked by the client, and the first message is used to instruct the server to perform data analysis based on the user behavior data.

8. The device according to claim 7, characterized in that, The message format of the first message is JSON format.

9. A data processing device, characterized in that, Deployed on the server, it includes: A communication module for receiving the first message sent by the client, and the first message includes: all user behavior data related to the target event and marked by the client; A processing module for querying in the user behavior data using the configuration data of the metadata in the data dashboard on the data management platform as a query statement to obtain a query result; The communication module is further used to send a second message to the data management platform, and the second message includes: the query result, and the second message is used to instruct the data management platform to display the query result on the data dashboard.

10. The device according to claim 9, characterized in that, Before the processing module queries the user behavior data using the configuration data of the metadata in the data dashboard on the data management platform, the communication module is further configured to: Receive a third message sent by the data management platform, where the third message includes the configuration data of the metadata in the data dashboard.

11. The apparatus according to claim 10, wherein, The third message is sent when the metadata in the data dashboard is modified.

12. The apparatus according to any one of claims 9-11, wherein, The metadata includes events, attributes, and metrics.

13. A data processing apparatus, wherein, comprises: At least one memory for storing programs; At least one processor for executing the programs stored in the memory. When the programs stored in the memory are executed, the processor is configured to execute the method according to claim 1 or 2, or to execute the method according to any one of claims 3-6.

14. A computer storage medium storing instructions that, when run on a computing device, cause the computing device to execute the method according to claim 1 or 2, or to execute the method according to any one of claims 3-6.

15. A computer program product, wherein, When the computer program product runs on a computing device, it causes the computing device to execute the method according to claim 1 or 2, or to execute the method according to any one of claims 3-6.

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