Data processing method, system, apparatus, device, medium, and program product

Abstract

This specification discloses a data processing method, system, apparatus, device, medium, and program product. The method, applied to a server, includes: receiving embedded data from a first terminal; any embedded data point being sent by the first terminal when it detects any user behavior event that meets preset reporting conditions; each user behavior event being triggered by a target operation behavior in a target client; constructing user behavior link data based on the embedded data point; the user behavior link data describing the user's behavior trajectory in a target business scenario; storing the user behavior link data in a structured database; responding to a data query request sent by a second terminal, querying the target behavior link data from the structured database; and sending the target behavior link data to the second terminal for display.

Description

Technical Field

[0001] This specification relates to the field of data processing technology, and in particular to a data processing method, apparatus, device, medium, and program product. Background Technology

[0002] Enterprises need to track user behavior data on client devices to optimize operations, improve user retention, and iterate product features. Among related technologies, methods such as full-domain event tracking and instant event recording to obtain user behavior data not only lack effective correlation of continuous user actions but also easily lead to excessive noise in the obtained user behavior data. A more reliable data processing method is needed to improve the usability of the tracked user behavior data. Summary of the Invention

[0003] This specification provides a data processing method, system, apparatus, device, medium, and program product that can improve the usability of tracked user behavior data.

[0004] Firstly, embodiments of this specification provide a data processing method applied to a server, comprising: Receive data from each embedded point sent by the first terminal; any data from any embedded point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; each user behavior event is triggered by each target operation behavior in the target client; Behavioral link data for each user is constructed based on the data from each tracking point; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario; Store each user's behavioral data in a structured database; In response to a data query request sent by the second terminal, the target behavior link data is queried from the structured database; The target behavior link data is sent to the second terminal so that the second terminal can display it based on the target behavior link data.

[0005] In one possible implementation, the data at each tracking point includes each user identifier and the timestamp of each user behavior event; Based on the data from each tracking point, construct behavioral link data for each user, including: Based on each user identifier, the data from each tracking point is grouped to obtain a set of data from each tracking point. Based on the timestamps of each user's behavior events, the data at each tracking point in each tracking point dataset is sorted to obtain the behavior sequence data for each user. Based on preset session segmentation rules, the behavioral sequence data of each user is segmented to obtain the behavioral link data of each user; The preset session segmentation rules are pre-configured based on the target business scenario.

[0006] In one possible implementation, the behavioral link data for each user includes the start date of each user's behavior; The behavioral data of each user is stored in a structured database, including: Use the start date of each user's activity as the first-level partition key; Use the scenario identifier of the target business scenario as the second-level partition key; Based on the first-level partition key and the second-level partition key, the behavioral data of each user is stored in the corresponding partition of the structured database.

[0007] In one possible implementation, the above method also includes: A multi-level index is built based on the behavior link identifier of each user, the behavior chain status corresponding to each user's behavior link, the user identifier of each user, the start date of each user's behavior, and at least one behavior node data. The behavior node data includes the timestamp of each user's behavior event, the page identifier corresponding to each user's behavior event, and the target operation behavior corresponding to each user's behavior event. Based on the start date of the behavior, a hot and cold data separation strategy is implemented for the behavior link data of each user in the structured database.

[0008] In one possible implementation, in response to a data query request sent by the second terminal, target behavior link data is queried from a structured database, including: In response to a data query request sent by the second terminal, the target partition in the structured database is located based on the target query time range and target scene identifier in the data query request. Based on the target user identifier in the data query request, query the target behavior link data from the target partition.

[0009] Secondly, embodiments of this specification provide a data processing method applied to a first terminal, the first terminal having a target client installed, the method comprising: Listen for user behavior events; each user behavior event is triggered by a target operation in the target client. In response to any user behavior event detected, determine whether any user behavior event meets the preset reporting conditions; When any user behavior event meets the preset reporting conditions, the corresponding data point of any user behavior event is sent to the server, so that the server: receives the data point sent by the first terminal; constructs the behavior link data of each user based on the data point; the behavior link data of each user is used to describe the behavior trajectory of each user in the target business scenario; stores the behavior link data of each user in a structured database; responds to the data query request sent by the second terminal and queries the target behavior link data from the structured database; and sends the target behavior link data to the second terminal so that the second terminal can display the data based on the target behavior link data.

[0010] In one possible implementation, in response to detecting any user behavior event, it is determined whether the user behavior event meets the preset reporting conditions, including: In response to any user behavior event detected, determine whether the target client's runtime environment meets the first preset condition; If the target client's runtime environment meets the first preset condition, determine whether the behavioral attributes associated with any user behavior event meet the second preset condition. If the behavioral attributes associated with any user behavior event meet the second preset condition, then any user behavior event is determined to meet the preset reporting condition.

[0011] Thirdly, embodiments of this specification provide a data processing method applied to a second terminal, comprising: In response to a data query operation, a data query request is generated; Send the data query request to the server; The system receives target behavior link data sent by the server. The target behavior link data is obtained by the server from a structured database based on a data query request. The structured database includes behavior link data for each user. The behavior link data for each user is used to describe the behavioral trajectory of each user in the target business scenario. The behavior link data for each user is constructed based on the data from each tracking point. Any tracking point data is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions. Each user behavior event is triggered by each target operation behavior in the target client. Based on at least one target behavior node data in the target behavior link data, render the user behavior storyline; the user behavior storyline is presented in the form of a timeline, on which each target interaction node corresponding to each target behavior node data is marked in chronological order. In response to a trigger operation on any target interaction node, the data of the target behavior node corresponding to that target interaction node is displayed.

[0012] Fourthly, embodiments of this specification provide a data processing system, including: a server, a first terminal, and a second terminal; wherein, The first terminal is used to listen to each user behavior event, which is triggered by each target operation behavior in the target client. In response to listening to any user behavior event, it determines whether any user behavior event meets the preset reporting conditions. If any user behavior event meets the preset reporting conditions, it sends any data point corresponding to any user behavior event to the server. The server is used to receive the data from each tracking point sent by the first terminal; construct the behavioral link data of each user based on the data from each tracking point; the behavioral link data of each user is used to describe the behavioral trajectory of each user in the target business scenario; and store the behavioral link data of each user in a structured database. The second terminal is used to respond to data query operations, generate data query requests, and send the data query requests to the server. The server is also used to respond to data query requests sent by the second terminal, query target behavior link data from the structured database, and send the target behavior link data to the second terminal; The second terminal is also used to receive target behavior link data sent by the server; render a user behavior storyline based on at least one target behavior node data in the target behavior link data; the user behavior storyline is presented in the form of a timeline, on which each target interaction node corresponding to each target behavior node data is marked in chronological order; in response to a trigger operation on any target interaction node, the terminal displays the target behavior node data corresponding to any target interaction node.

[0013] Fifthly, embodiments of this specification provide a data processing apparatus applied to a server, comprising: The first receiving module is used to receive the data from each embedded point sent by the first terminal; any data from each embedded point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; each user behavior event is triggered by each target operation behavior in the target client. The building module is used to construct behavioral link data for each user based on the data from each tracking point; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario; The storage module is used to store the behavioral data of each user into a structured database; The query module is used to respond to data query requests sent by the second terminal and query target behavior link data from the structured database. The first sending module is used to send the target behavior link data to the second terminal so that the second terminal can display the target behavior link data.

[0014] Sixthly, embodiments of this specification provide a data processing apparatus applied to a first terminal, the first terminal having a target client installed, the apparatus comprising: The listening module is used to listen for user behavior events; each user behavior event is triggered by a target operation in the target client. The judgment module is used to respond to any user behavior event detected by listening to determine whether any user behavior event meets the preset reporting conditions. The second sending module is used to send any data point corresponding to any user behavior event to the server when any user behavior event meets the preset reporting conditions, so that the server: receives the data point data sent by the first terminal; constructs the behavior link data of each user based on the data point data; the behavior link data of each user is used to describe the behavior trajectory of each user in the target business scenario; stores the behavior link data of each user in a structured database; in response to the data query request sent by the second terminal, queries the target behavior link data from the structured database; and sends the target behavior link data to the second terminal so that the second terminal can display the data based on the target behavior link data.

[0015] Sixthly, embodiments of this specification provide a data processing apparatus applied to a second terminal, the apparatus comprising: The generation module is used to generate data query requests in response to data query operations; The sending module is used to send data query requests to the server; The second receiving module is used to receive target behavior link data sent by the server. The target behavior link data is obtained by the server from a structured database based on a data query request. The structured database includes behavior link data for each user. The behavior link data for each user is used to describe the behavioral trajectory of each user in the target business scenario. The behavior link data for each user is constructed based on the data from each tracking point. Any tracking point data is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions. Each user behavior event is triggered by each target operation behavior in the target client. The rendering module is used to render the user behavior storyline based on at least one target behavior node data in the target behavior link data. The user behavior storyline is presented in the form of a timeline, on which each target interaction node corresponding to each target behavior node data is marked in chronological order. The display module is used to respond to the trigger operation of any target interaction node and display the target behavior node data corresponding to any target interaction node.

[0016] In a seventh aspect, embodiments of this specification provide an electronic device, including: a processor and a memory; the memory stores a computer program, which, when executed by the processor, implements the method steps provided in the first, second, or third aspects of the embodiments of this specification.

[0017] Eighthly, embodiments of this specification provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the method steps provided in the first, second, or third aspects of embodiments of this specification.

[0018] Ninthly, embodiments of this specification provide a computer program product, including a computer program; when the computer program is executed by a processor, it implements the method steps provided in the first, second, or third aspects of the embodiments of this specification.

[0019] The aforementioned data processing methods, devices, equipment, media, and program products, in the data acquisition phase, involve the first terminal selectively monitoring user behavior events triggered by various target operations on the target client. Only when any user behavior event meets preset reporting conditions is the corresponding data point data sent to the server. This effectively avoids the problems of excessive noise in user behavior data obtained from full-domain data point coverage and instant data point reporting, thus improving the accuracy of the tracked user behavior data. In the data construction phase, the server receives the data points sent by the first terminal and constructs user behavior link data based on these data points to describe the user's behavioral trajectory in the target business scenario. This effectively connects continuous operations of the same user, facilitating subsequent reproduction of the user's interaction storyline on the target client, and improving the completeness of the tracked user behavior data. In the data storage phase, the server stores the constructed user behavior link data in a structured database. This allows for subsequent analysis of user behavior data and enables the server to respond to data query requests sent by the second terminal, retrieving target behavior link data from the structured database, thus improving the accessibility of the tracked user behavior data. During the data visualization phase, the server sends the target behavior chain data to the second terminal, enabling the second terminal to display the data based on this information. This facilitates visualization through the front end, enhancing the displayability of the tracked user behavior data. Throughout the process, more reliable data processing methods effectively improve the accuracy, completeness, accessibility, and displayability of the tracked user behavior data, thereby increasing its usability. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A schematic diagram illustrating the application environment of a data processing method provided as an exemplary embodiment of this specification; Figure 2 A flowchart illustrating a data processing method provided for an exemplary embodiment of this specification; Figure 3 A flowchart illustrating another data processing method provided as an exemplary embodiment of this specification; Figure 4 A flowchart illustrating yet another data processing method provided as an exemplary embodiment of this specification; Figure 5 A schematic diagram of the structure of a data processing apparatus provided for an exemplary embodiment of this specification; Figure 6 A schematic diagram of the structure of another data processing apparatus provided in an exemplary embodiment of this specification; Figure 7 A schematic diagram of the structure of yet another data processing apparatus provided as an exemplary embodiment of this specification; Figure 8 A schematic diagram of the structure of an electronic device provided as an exemplary embodiment of this specification; Figure 9 This is a schematic diagram of the structure of another electronic device provided as an exemplary embodiment of this specification. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this specification clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this specification.

[0023] In the description of this specification, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of these terms in this specification based on the specific circumstances. Furthermore, in the description of this specification, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0024] The data processing methods provided in the embodiments of this specification can be applied to, for example... Figure 1 The application environment shown is illustrated. In this environment, the first terminal 10 and the second terminal 20 communicate with the server 30 via a network. The first terminal 10 has the target client installed. The structured database can store the data that the server 30 needs to process. The structured database can be integrated onto the server 30, or it can be located on the cloud or other network servers.

[0025] In some possible implementations, the above data processing method includes a data acquisition stage, a data construction stage, a data storage stage, and a data presentation stage, specifically: During the data collection phase, the first terminal 10 listens to each user behavior event, which is triggered by each target operation behavior in the target client. In response to listening to any user behavior event, it determines whether any user behavior event meets the preset reporting conditions. If any user behavior event meets the preset reporting conditions, it sends any data point data corresponding to any user behavior event to the server 30.

[0026] During the data construction phase, server 30 receives data from each tracking point sent by first terminal 10; constructs behavioral link data for each user based on the tracking point data; and uses the behavioral link data for each user to describe the behavioral trajectory of each user in the target business scenario.

[0027] During the data storage and retrieval phase, server 30 stores the behavioral data of each user in a structured database. Second terminal 20, in response to the data query operation, generates a data query request and sends it to server 30. Server 30, in response to the data query request from second terminal 20, retrieves the target behavioral data from the structured database and sends the target behavioral data back to second terminal 20.

[0028] During the data display phase, the second terminal 20 receives target behavior link data sent by the server 30; based on at least one target behavior node data in the target behavior link data, it renders a user behavior storyline; the user behavior storyline is presented in the form of a timeline, on which each target interaction node corresponding to each target behavior node data is marked in chronological order; in response to a trigger operation on any target interaction node, it displays the target behavior node data corresponding to any target interaction node.

[0029] It should be understood that both the first terminal 10 and the second terminal 20 can be, but are not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. Both the first terminal 10 and the second terminal 20 can be implemented using independent terminals or a cluster of multiple terminals. The server 30 can be implemented using an independent server or a cluster of multiple servers (such as application servers and database servers).

[0030] In one embodiment, such as Figure 2 As shown, a data processing method is provided, which can be applied to... Figure 1 Taking the application environment in [the document] as an example, the following steps are included: S202: The first terminal 10 listens to each user behavior event, which is triggered by each target operation behavior in the target client.

[0031] The first terminal 10 has the target client installed. The target client can be a web client or an app client.

[0032] Optionally, front-end developers first identify the functional components of the target client and assign a universally unique identifier (UUID) to each target operation and each target page element that requires event tracking. Then, they extend the event listening mechanism in the front-end code to capture user behavior events triggered by each target operation. Understandably, each target operation can be, but is not limited to, clicking, swiping, or hovering, and each target page element can be, but is not limited to, selection controls, search controls, links, and icons. Each user behavior event can be associated with both a target operation and a target page element simultaneously, or it can be associated with only one target operation. For example, the user behavior event "clicking the search control" is associated with both the target operation "clicking" and the target page element "search control"; while the user behavior event "swiping the entire page" is associated only with the target operation "swiping".

[0033] S204: Upon detecting any user behavior event, the first terminal 10 determines whether the user behavior event meets the preset reporting conditions. If yes, proceed to S206; otherwise, end the process.

[0034] The preset reporting conditions include a first preset condition for the target client's operating environment and a second preset condition for the behavioral attributes associated with any user behavior event. The first preset condition for the target client's operating environment includes at least one of the following: the target client's user agent is a preset user agent; the target client's client version is a preset client version; and the target client's operating system type is a preset operating system type. The second preset condition for the behavioral attributes associated with any user behavior event includes at least one of the following: the user account status corresponding to any user behavior event is a preset account status (such as login account status); the page address where the behavior occurred corresponding to any user behavior event is a preset page address; and the business module to which the behavior belongs corresponding to any user behavior event is a preset business module.

[0035] Optionally, in response to detecting any user behavior event in the target client, the first terminal 10 determines whether the target client's operating environment meets a first preset condition, such as whether the target client's user agent is a preset user agent. If the target client's operating environment meets the first preset condition, it determines whether the behavioral attributes associated with any user behavior event meet a second preset condition, such as whether the account status corresponding to any user behavior event is a logged-in account status, whether the page address corresponding to any user behavior event is a preset page address, and whether the business module corresponding to any user behavior event is a preset business module. If the behavioral attributes associated with any user behavior event meet the second preset condition, it determines that any user behavior event meets the preset reporting condition.

[0036] S206: The first terminal 10 sends any data point data corresponding to any user behavior event to the server 30.

[0037] Each data point includes user identifier, event identifier, event timestamp, page identifier, and business function module identifier.

[0038] Optionally, the first terminal 10 sends any data point data corresponding to any user behavior event, such as user identifier, event identifier, event timestamp, page identifier, and business function module identifier, to the server's dedicated API gateway via the HTTPS protocol to ensure data security and low latency.

[0039] In this embodiment, the first terminal 10 selectively listens to each user behavior event triggered by each target operation behavior in the target client. Only when any user behavior event meets the preset reporting conditions will the data of any tracking point corresponding to any user behavior event be sent to the server 30. This can effectively avoid the problem of excessive noise in the user behavior data obtained by full-domain tracking point coverage and instant reporting and storage of tracking points, and help improve the accuracy of the tracked user behavior data.

[0040] S208: Server 30 receives data from various embedded points sent by the first terminal 10.

[0041] Optionally, after receiving any data point data sent by the first terminal 10, the API gateway of server 30 does not directly perform complex data processing, but publishes the data point data as a message to a message middleware (such as a Kafka message queue) to achieve traffic shaving, data buffering and production-consumption decoupling in high-concurrency scenarios, improve the stability of data processing, and thus improve the integrity and accuracy of the tracked user behavior data.

[0042] In this embodiment, the server 30 receives the data from each tracking point sent by the first terminal 10, and constructs the behavioral link data of each user based on the data from each tracking point to describe the behavioral trajectory of each user in the target business scenario. This can effectively connect the continuous operation behavior of the same user, making it easier to reproduce the user's interaction storyline on the target client and helping to improve the integrity of the tracked user behavior data.

[0043] S210: Server 30 constructs behavioral link data for each user based on the data from each tracking point; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario.

[0044] Understandably, each data point includes corresponding user identifiers, event identifiers, event timestamps, page identifiers, and business function module identifiers. Target business scenarios may include, but are not limited to, online service application scenarios and online shopping scenarios. Online service application scenarios may include, but are not limited to, loan application scenarios. Online shopping scenarios may include, but are not limited to, e-commerce shopping scenarios.

[0045] Optionally, server 30 subscribes to and pulls data from each tracking point from the message middleware through the PySpark stream processing service deployed on the backend; then it performs data cleaning, data grouping and data sorting on the pulled tracking point data; finally, it constructs complete user behavior chain data and writes it into a structured offline data table.

[0046] Specifically, after subscribing to and pulling data from each tracking point from the message middleware, server 20 groups the tracking point data based on the user identifier in each tracking point data to obtain a set of tracking point data; based on the timestamp of each user behavior event, it sorts the tracking point data in each tracking point data set to obtain the behavior sequence data of each user; and through the window function of Spark SQL, based on the preset session partitioning rules, it partitions the behavior sequence data of each user to obtain the behavior link data of each user.

[0047] S212: Server 30 stores the behavioral data of each user in a structured database.

[0048] The user's behavior chain data includes the user's behavior chain identifier, the behavior chain status corresponding to the user's behavior chain (such as whether the conversion has been completed), the user's user identifier, the user's behavior start date, and at least one behavior node data. Each behavior node data includes the timestamp of the user's behavior event, the page identifier corresponding to the user's behavior event, and the target operation behavior corresponding to the user's behavior event.

[0049] Optionally, server 30 employs a dual-partition, multi-level indexing, and hot / cold data separation strategy to store the behavioral data of each user in a structured database, thereby providing a highly available and easily queryable data foundation for subsequent user behavior data analysis.

[0050] Specifically, server 30 uses the start date of each user's behavior as the first-level partition key and the scenario identifier corresponding to the target business scenario as the second-level partition key. Based on the first-level and second-level partition keys, it determines the corresponding partition of each user's behavior link data in the structured database. Then, server 30 builds a multi-level index based on each user's behavior link identifier, user identifier, behavior start date, and at least one behavior node data in each user's behavior link data. At preset time intervals, based on the behavior start date, it performs a hot and cold data separation strategy on each user's behavior link data in the structured database, storing frequently used behavior link data in a high-performance solid-state drive storage layer and periodically transferring historical archived data to low-frequency storage to control costs.

[0051] S214: The second terminal 20 responds to the data query operation and generates a data query request.

[0052] Optionally, in response to the user's data query operation, the second terminal 20 generates a query request including the target user identifier, the target scene identifier, and the target query time range.

[0053] S216: The second terminal 20 sends a data query request to the server 30.

[0054] Optionally, the second terminal 20 sends a data query request to the server 30 via a network interface.

[0055] S218: Server 30 responds to the data query request sent by the second terminal 20 by querying the target behavior link data from the structured database.

[0056] Optionally, server 30 receives a data query request sent by second terminal 20 via a network interface (such as a RESTful API), parses the data query request to obtain fixed interface parameters, which at least include the target user identifier, the target scenario identifier, and the target query time range. Then, based on the interface parameters, server 30 uses data sharding query technology combined with pre-aggregation caching to query the target behavior link data that matches the interface parameters from the structured data table.

[0057] In this embodiment, the server 30 stores the constructed user behavior link data in a structured database, which facilitates the subsequent analysis of user behavior data. It can respond to the data query request sent by the second terminal 20 and query the target behavior link data from the structured database, thereby improving the accessibility of the tracked user behavior data.

[0058] S220: Server 30 sends the target behavior link data to the second terminal 20.

[0059] Optionally, server 30 sends the target behavior link data to second terminal 20 via network interface.

[0060] S222: The second terminal 20 receives the target behavior link data sent by the server 30.

[0061] Optionally, the second terminal 20 receives target behavior link data sent by the server 30 through a network interface.

[0062] S224: The second terminal 20 displays the target behavior link data.

[0063] Optionally, the second terminal 20 generates and renders a user behavior storyline based on the target behavior link data through its internal visualization component; wherein, the visualization component is built based on a modern web framework (such as React, Vue).

[0064] For example, the second terminal 20 renders a user behavior storyline presented in the form of a timeline through its internal visualization component, based on at least one target behavior node data in the target behavior link data. The timeline is marked with each target interaction node corresponding to each target behavior node data in chronological order. The second terminal 20 can then respond to a trigger operation on any target interaction node and display the target behavior node data corresponding to that target interaction node.

[0065] In this embodiment, the server 30 sends the target behavior link data to the second terminal 20 so that the second terminal 20 can display it based on the target behavior link data, which helps to improve the displayability of the tracked user behavior data through front-end visualization.

[0066] In the aforementioned data processing method, during the data acquisition phase, the first terminal selectively listens to user behavior events triggered by various target operations on the target client. Only when any user behavior event meets the preset reporting conditions is the corresponding data point data sent to the server. This effectively avoids the problem of excessive noise in user behavior data obtained from full-domain data point coverage and instant data point reporting, thus improving the accuracy of the tracked user behavior data. During the data construction phase, the server receives the data points sent by the first terminal and constructs user behavior chain data based on these data points to describe the user's behavioral trajectory in the target business scenario. This effectively connects the continuous operations of the same user, facilitating the subsequent reproduction of the user's interaction storyline on the target client, and improving the completeness of the tracked user behavior data. During the data storage phase, the server stores the constructed user behavior chain data in a structured database. This allows for subsequent analysis of the user behavior data and enables the server to respond to data query requests sent by the second terminal, retrieving target behavior chain data from the structured database, thus improving the accessibility of the tracked user behavior data. During the data visualization phase, the server sends the target behavior chain data to the second terminal, enabling the second terminal to display the data based on this information. This facilitates visualization through the front end, enhancing the displayability of the tracked user behavior data. Throughout the process, more reliable data processing methods effectively improve the accuracy, completeness, accessibility, and displayability of the tracked user behavior data, thereby increasing its usability and analytical value.

[0067] In one embodiment, such as Figure 3 As shown, another data processing method is provided, which can be applied to... Figure 1 The following steps are used as an example to illustrate the application environment shown: S302: The first terminal 10 listens to each user behavior event, which is triggered by each target operation behavior in the target client.

[0068] Specifically, S302 is the same as S202, and will not be repeated here.

[0069] S304: Upon detecting any user behavior event, the first terminal 10 determines whether the target client's operating environment meets the first preset condition. If yes, then execute S306; otherwise, end.

[0070] The first preset condition is a preset condition for the target client's operating environment. The first preset condition includes at least one of the following: the target client's user agent is a preset user agent, the target client's client version is a preset client version, and the target client's operating system type is a preset operating system type.

[0071] Optionally, in response to listening to any user behavior event, the first terminal 10 determines whether the user agent of the target client is a preset user agent, whether the client version of the target client is a preset client version, and whether the operating system type of the target client is a preset operating system type.

[0072] S306: The first terminal 10 determines whether the behavioral attribute associated with any user behavior event meets the second preset condition. If yes, then execute S308; otherwise, end.

[0073] The second preset condition is a preset condition for the behavioral attributes associated with any user behavior event. The second preset condition includes at least one of the following: the user account status corresponding to any user behavior event is a logged-in account status; the page address where the behavior corresponding to any user behavior event occurs is a preset page address; and the business module to which the behavior corresponding to any user behavior event belongs is a preset business module.

[0074] Optionally, when the target client's operating environment meets the first preset conditions, the first terminal 10 determines whether the user account status corresponding to any user behavior event is a logged-in account status, whether the page address where the behavior occurs corresponding to any user behavior event is a preset page address, and whether the business module to which the behavior belongs corresponding to any user behavior event is a preset business module.

[0075] S308: The first terminal 10 determines that any user behavior event meets the preset reporting conditions.

[0076] Optionally, if the target client's operating environment meets the first preset condition and the behavioral attribute associated with any user behavior event meets the second preset condition, the first terminal 10 determines that any user behavior event meets the preset reporting condition.

[0077] In this embodiment, the first terminal selectively listens to user behavior events triggered by various target operation behaviors in the target client. Only when any user behavior event is listened to and simultaneously meets the first preset condition for the target client's operating environment and the second preset condition for the behavior attribute associated with any user behavior event, will any tracking data corresponding to any user behavior event be sent to the server. This can effectively avoid the problem of excessive noise in user behavior data obtained by full-domain tracking coverage and instant reporting and storage of tracking data, and helps to improve the accuracy of the tracked user behavior data.

[0078] S310: The first terminal 10 sends any data point data corresponding to any user behavior event to the server 30.

[0079] Each data point includes a user identifier, an event identifier, an event timestamp, a page identifier, and a business function module identifier. The first terminal 10 is a terminal cluster composed of multiple data collection terminals. After each data collection terminal detects any user behavior event and determines that the user behavior event meets the preset reporting conditions, it can send any data point corresponding to the user behavior event to the server 30.

[0080] Optionally, the first terminal 10 sends any data point data corresponding to any user behavior event to the dedicated API gateway of the server 30 via the HTTPS protocol to ensure data security and low latency.

[0081] S312: Server 30 receives data from various embedded points sent by the first terminal 10.

[0082] Understandably, any data point in each data point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; each user behavior event is triggered by the target operation behavior in the target client.

[0083] Optionally, after receiving any data point data sent by any data collection terminal, the API gateway of server 30 does not directly perform complex data processing. Instead, it publishes the data point data as a message to a message middleware (such as a Kafka message queue) to achieve traffic shaving, data buffering and production-consumption decoupling in high-concurrency scenarios, improve the stability of data processing, and thus improve the completeness and accuracy of the tracked user behavior data.

[0084] S314: Server 30 groups the data of each tracking point based on each user identifier to obtain a set of tracking point data.

[0085] Optionally, after receiving the raw event tracking data transmitted via the Kafka message queue, server 30 uses a Python script combined with the PySpark framework for structured processing. First, server 30 performs data cleaning on each event tracking data point, specifically removing duplicate records and validating the validity of each event timestamp. Then, based on the user identifiers in each event tracking data point, server 30 groups event tracking data points with the same user identifier together, obtaining a set of event tracking data points.

[0086] S316: Based on the timestamps of each user's behavior events, sort the data of each tracking point in each tracking point data set to obtain the behavior sequence data of each user.

[0087] Optionally, the server 30 sorts each set of event data based on the timestamp of each user behavior event in each event data set to obtain the behavior sequence data of each user.

[0088] S318: Based on preset session segmentation rules, the behavioral sequence data of each user is segmented to obtain the behavioral link data of each user.

[0089] The preset session segmentation rules are pre-configured based on target business scenarios, which may include, but are not limited to, online service application scenarios and online shopping scenarios. Online service application scenarios may include, but are not limited to, loan application scenarios. Online shopping scenarios may include, but are not limited to, e-commerce shopping scenarios. Each user's behavioral data is used to describe their behavioral trajectory within the target business scenario.

[0090] Specifically, the aforementioned preset session segmentation rules include session start rules and session end rules. For example, a session start rule could be: if any user behavior event corresponding to any tracking data point is detected as visiting the homepage or searching for products, then a segmentation is triggered, and that tracking data point is taken as the starting point of the user behavior chain. A session end rule could be: if any user behavior event corresponding to any tracking data point is detected as paying for products or returning to the homepage, then a segmentation is triggered, and that tracking data point is taken as the ending point of the user behavior chain. In addition, the preset session segmentation rules also include timeout rules. For example, a timeout rule could be: if the time interval between two adjacent tracking data point corresponding to user behavior events exceeds a preset time threshold, then a segmentation is triggered, with the preceding tracking data point among the two adjacent tracking data point points taken as the ending point of the previous user behavior chain, and the following tracking data point among the two adjacent tracking data point points taken as the starting point of the next user behavior chain.

[0091] For example, server 30 uses Spark SQL window functions (such as LEAD / LAG) and session segmentation rules to identify the temporal relationship of each user's behavior events corresponding to each embedded data point in each user's behavior sequence data, thereby segmenting the behavior sequence data of each user and obtaining the behavior link data of each user.

[0092] In this embodiment, the server receives the data from each tracking point sent by the first terminal, performs data cleaning, data grouping and data sorting on each tracking point data to construct complete user behavior link data that describes the behavioral trajectory of each user in the target business scenario. This can effectively link the continuous operation behavior of the same user, making it easier to reproduce the user's interaction storyline on the target client and helping to improve the integrity of the tracked user behavior data.

[0093] S320: Server 30 stores the behavioral data of each user in a structured database.

[0094] The user behavior chain data includes the user's behavior chain identifier, the behavior chain status corresponding to the user's behavior chain (such as whether the conversion has been completed), the user's user identifier, the start date of the user's behavior, and at least one behavior node data. The behavior node data includes the timestamp of the user's behavior event, the page identifier corresponding to the user's behavior event, and the target operation behavior corresponding to the user's behavior event.

[0095] Optionally, server 30 employs a dual-partitioning, multi-level indexing, and hot / cold data separation strategy to provide a highly available and easily queryable data foundation for subsequent user behavior data analysis. Specifically, server 30 uses the start date of each user's behavior as the first-level partition key and the scenario identifier corresponding to the target business scenario as the second-level partition key. Based on the first-level and second-level partition keys, it determines the corresponding partition of each user's behavior chain data in the structured database.

[0096] Then, server 30 establishes a multi-level index based on the behavior link identifier of each user, the behavior chain status corresponding to each user's behavior link, the user identifier of each user, the behavior start date of each user, and at least one behavior node data in each user's behavior link data; and according to a preset time interval, based on the behavior start date, it performs a hot and cold data separation strategy on the behavior link data of each user in the structured database, storing the behavior link data whose behavior start date is within a preset time range from the current date to the solid-state drive storage layer, and periodically and automatically transferring the behavior link data whose behavior start date is outside the preset time range of the current date to the low-frequency storage layer to control costs.

[0097] In one embodiment, such as Figure 4 As shown, another data processing method is provided, which can be applied to... Figure 1 The following steps are used as an example to illustrate the application environment shown: S402: The second terminal 20 responds to the data query operation by generating a data query request.

[0098] Optionally, in response to the user's data query operation, the second terminal 20 generates a query request including the target user identifier, the target scene identifier, and the target query time range.

[0099] S404: The second terminal 20 sends a data query request to the server 30.

[0100] Optionally, the second terminal 20 sends a data query request to the server 30 via a network interface.

[0101] S406: Server 30 responds to the data query request sent by the second terminal 20 by querying the target behavior link data from the structured database.

[0102] Optionally, server 30 receives a data query request sent by second terminal 20 via a network interface (such as a RESTful API), parses the data query request to obtain fixed interface parameters, which at least include the target user identifier, the target scenario identifier, and the target query time range. Then, based on the interface parameters, server 30 uses data sharding query technology combined with pre-aggregation caching to query the target behavior link data that matches the interface parameters from the structured data table.

[0103] Specifically, in response to the data query request sent by the second terminal, the server 30 locates the target partition in the structured database based on the target query time range and target scenario identifier in the data query request; and queries the target behavior link data from the target partition based on the target user identifier in the data query request.

[0104] S408: Server 30 sends the target behavior link data to the second terminal 20.

[0105] Optionally, server 30 sends the target behavior link data to second terminal 20 via network interface.

[0106] S410: The second terminal 20 receives the target behavior link data sent by the server 30.

[0107] Optionally, the second terminal 20 receives target behavior link data sent by the server 30 through a network interface.

[0108] S412: The second terminal 20 renders the user behavior storyline based on at least one target behavior node data in the target behavior link data.

[0109] The user behavior storyline is presented in the form of a timeline, with each target interaction node corresponding to the target behavior node data marked in chronological order.

[0110] Optionally, after receiving the target behavior link data sent by the server 30, the front-end application of the second terminal 20 generates and renders a user behavior storyline through its internal visualization component. This visualization component is built on a modern web framework (such as React or Vue).

[0111] Specifically, the user behavior storyline can be presented in the form of a timeline. The second terminal 20 uses a visualization component to traverse the behavior node data in each user's behavior chain data. Based on the timestamp of the user behavior event in each behavior node data, the behavior chain data of each user is sorted, and a horizontal or vertical layout timeline is generated on the interface based on this. On the generated timeline, each behavior node data is rendered as a visual interactive node, which can be displayed in the form of video cards. These interactive nodes are arranged strictly in chronological order and can expand to include rich content such as the user's specific operation details and context.

[0112] It's worth noting that user behavior storylines can also be displayed in tabular form, supporting behavior chain filtering, tag highlighting, and conversion step breakdown. For example, operations personnel can select user behavior chains whose start time falls within the target time range in the corresponding table of the user behavior storyline. In this case, the second terminal 20 will hide chains that do not meet the criteria, making the analysis more focused. Furthermore, in complex storylines, the second terminal 20 can also highlight specific types of behavioral events or break down a complete user behavior chain into conversion steps, calculating the user churn rate at each step. This visually demonstrates which stage is the bottleneck in conversion, improving the efficiency of user behavior data analysis.

[0113] S414: The second terminal 20 responds to the trigger operation of any target interaction node and displays the target behavior node data corresponding to any target interaction node.

[0114] Understandably, the target behavior node data corresponding to any target interaction node includes the timestamp of the target user behavior event, the page identifier corresponding to the target user behavior event, and the target operation behavior corresponding to the target user behavior event.

[0115] Optionally, the second terminal 20 responds to the user's click operation on the interactive node in the user behavior storyline in the form of a timeline, and displays rich content such as the user's specific operation details and context based on the target behavior node data corresponding to any target interactive node.

[0116] In this embodiment, the second terminal displays an interactive user behavior storyline based on the target behavior link data. This allows operators to intuitively understand the user's specific operational details, context, and other rich content through the interactive user behavior storyline. It also helps to improve the displayability of the tracked user behavior data through front-end visualization.

[0117] Figure 3 and Figure 4 In the data processing method shown, during the data acquisition phase, the first terminal selectively listens to user behavior events triggered by various target operations in the target client. Only when any user behavior event simultaneously meets a first preset condition for the target client's operating environment and a second preset condition for the associated behavioral attributes of that user behavior event, is the corresponding data point data sent to the server. This effectively avoids the problem of excessive noise in user behavior data obtained from full-domain data point coverage and instant data point reporting and storage, thus improving the accuracy of the tracked user behavior data. During the data construction phase, the server receives the data points sent by the first terminal and performs data cleaning, grouping, and sorting to construct complete user behavior chain data describing the behavioral trajectory of each user in the target business scenario. This effectively connects the continuous operations of the same user, facilitating subsequent reproduction of the user's interaction storyline on the target client and improving the completeness of the tracked user behavior data. During the data storage phase, the server employs a dual-partitioning, multi-level indexing, and hot / cold data separation strategy to provide a highly available and easily queryable data foundation for subsequent user behavior data analysis, improving the accessibility of the tracked user behavior data. During the data visualization phase, the second terminal displays interactive user behavior storylines based on the target behavior chain. This allows operations personnel to intuitively understand the specific operational details and contextual environment of users through these interactive storylines, enhancing the displayability of the tracked user behavior data through front-end visualization. Throughout the process, more reliable data processing methods effectively improve the accuracy, completeness, accessibility, and usability of the tracked user behavior data, thereby increasing its analytical value.

[0118] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0119] Based on the inventive concept of the above data processing method, such as Figure 5 As shown in the embodiments of this specification, a data processing apparatus 500 for implementing the data processing method applied to a server as described above is also provided. The data processing apparatus 500 includes: The first receiving module 501 is used to receive the data from each embedded point sent by the first terminal; any data from each embedded point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; each user behavior event is triggered by each target operation behavior in the target client; Module 502 is used to build behavioral link data for each user based on the data from each tracking point; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario. Storage module 503 is used to store the behavioral data of each user into a structured database; The query module 504 is used to query target behavior link data from the structured database in response to a data query request sent by the second terminal. The first sending module 505 is used to send the target behavior link data to the second terminal so that the second terminal can display the target behavior link data.

[0120] In one possible implementation, each data point includes a user identifier and a timestamp of each user behavior event. The construction module 502 is specifically used to: group the data points based on each user identifier to obtain a data set; sort the data points in each data set based on the timestamp of each user behavior event to obtain the behavior sequence data of each user; and divide the behavior sequence data of each user based on a preset session segmentation rule to obtain the behavior link data of each user. The preset session segmentation rule is pre-configured based on the target business scenario.

[0121] In one possible implementation, the behavior link data of each user includes the start date of each user's behavior; the storage module 503 is specifically used to: use the start date of each user's behavior as the first-level partition key; use the scenario identifier of the target business scenario as the second-level partition key; and store the behavior link data of each user in the corresponding partition of the structured database based on the first-level partition key and the second-level partition key.

[0122] In one possible implementation, the storage module 503 is further configured to: establish a multi-level index based on the behavior link identifier of each user, the behavior chain status corresponding to each user's behavior link, the user identifier of each user, the behavior start date of each user, and at least one behavior node data in the behavior link data of each user; each behavior node data includes the timestamp of each user's behavior event, the page identifier corresponding to each user's behavior event, and the target operation behavior corresponding to each user's behavior event; and execute a hot and cold data separation strategy on the behavior link data of each user in the structured database based on the behavior start date.

[0123] In one possible implementation, the query module 504 is specifically used to: respond to a data query request sent by the second terminal, locate the target partition in the structured database according to the target query time range and target scenario identifier in the data query request; and query the target behavior link data from the target partition according to the target user identifier in the data query request.

[0124] like Figure 6 As shown in the embodiments of this specification, a data processing apparatus 600 is also provided for implementing the data processing method applied to a first terminal as described above. The first terminal has a target client installed. The data processing apparatus 600 includes: The listening module 601 is used to listen for various user behavior events; each user behavior event is triggered by a target operation behavior in the target client. The judgment module 602 is used to respond to any user behavior event detected by listening to determine whether any user behavior event meets the preset reporting conditions. The second sending module 603 is used to send any data point corresponding to any user behavior event to the server when any user behavior event meets the preset reporting conditions, so that the server: receives the data point data sent by the first terminal; constructs the behavior link data of each user based on the data point data; the behavior link data of each user is used to describe the behavior trajectory of each user in the target business scenario; stores the behavior link data of each user in a structured database; queries the target behavior link data from the structured database in response to the data query request sent by the second terminal; and sends the target behavior link data to the second terminal so that the second terminal can display the target behavior link data.

[0125] In one possible implementation, the judgment module 602 is specifically used to: in response to listening to any user behavior event, determine whether the target client's operating environment meets a first preset condition; if the target client's operating environment meets the first preset condition, determine whether the behavior attribute associated with any user behavior event meets a second preset condition; if the behavior attribute associated with any user behavior event meets the second preset condition, determine that any user behavior event meets a preset reporting condition.

[0126] like Figure 7 As shown in the embodiments of this specification, a data processing apparatus 700 for implementing the data processing method applied to a second terminal as described above is also provided. The data processing apparatus 700 includes: The generation module 701 is used to generate a data query request in response to a data query operation; Sending module 702 is used to send data query requests to the server; The second receiving module 703 is used to receive target behavior link data sent by the server. The target behavior link data is obtained by the server from a structured database based on a data query request. The structured database includes behavior link data of each user. The behavior link data of each user is used to describe the behavior trajectory of each user in the target business scenario. The behavior link data of each user is constructed based on each embedded data point. Any embedded data point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions. Each user behavior event is triggered by each target operation behavior in the target client. Rendering module 704 is used to render a user behavior storyline based on at least one target behavior node data in the target behavior link data; the user behavior storyline is presented in the form of a timeline, on which each target interaction node corresponding to each target behavior node data is marked in chronological order. The display module 705 is used to respond to a trigger operation on any target interaction node and display the target behavior node data corresponding to any target interaction node.

[0127] Each module in the aforementioned data processing devices 500, 600, and 700 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0128] This specification also provides an electronic device, which may be a server, and its internal structure diagram may be as follows: Figure 8As shown, this electronic device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The application database stores user behavior data, etc. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. The processor executes computer programs to implement a data processing method.

[0129] It is worth noting that this electronic device can also be a terminal, and its internal structure diagram can be as follows: Figure 9 As shown, this electronic device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a data processing method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the electronic device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the electronic device, or external keyboards, touchpads, or mice, etc.

[0130] Those skilled in the art will understand that Figure 8 and Figure 9The structures shown are merely block diagrams of a portion of the structure related to the scheme described in this specification, and do not constitute a limitation on the electronic devices to which the scheme described in this specification is applied. Specific electronic devices may include more or fewer components than those shown in the figures, or may combine certain components, or may have different component arrangements.

[0131] This specification also provides a computer storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps in the above embodiments. If the constituent modules of the above-described electronic device are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer storage medium.

[0132] This specification also provides a computer program product, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0133] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as 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, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a 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 via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0134] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. Unless otherwise specified, the technical features of this embodiment and its implementation can be combined arbitrarily.

[0135] The embodiments described above are merely preferred embodiments of this specification and are not intended to limit the scope of this specification. Any modifications and improvements made by those skilled in the art to the technical solutions of this specification without departing from the spirit of this specification should fall within the protection scope defined by the claims.

[0136] It should be noted that the information, data and signals involved in the embodiments of this specification are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0137] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

Claims

1. A data processing method applied to a server, the method comprising: Receive data from various embedded points sent by the first terminal; Any data point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; Each user behavior event is triggered by a target operation behavior in the target client; Based on the data from each tracking point, behavioral link data for each user is constructed; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario. The behavioral data of each user is stored in a structured database; In response to a data query request sent by the second terminal, target behavior link data is queried from the structured database; The target behavior link data is sent to the second terminal so that the second terminal can display the data based on the target behavior link data.

2. The method as described in claim 1, wherein each data point includes a user identifier and a timestamp of each user behavior event; The construction of behavioral link data for each user based on the data from each tracking point includes: Based on each user identifier, the data at each tracking point is grouped to obtain a set of data at each tracking point; Based on the timestamps of each user behavior event, the data at each tracking point in each tracking point data set is sorted to obtain the behavior sequence data of each user. Based on preset session segmentation rules, the behavioral sequence data of each user is segmented to obtain the behavioral link data of each user; The preset session segmentation rules are pre-configured based on the target business scenario.

3. The method as described in claim 1, wherein the behavioral link data of each user includes the start date of each user's behavior; The step of storing the behavioral data of each user in a structured database includes: Use the start date of each user's behavior as the first-level partition key; Use the scenario identifier of the target business scenario as the second-level partition key; Based on the first-level partition key and the second-level partition key, the behavioral data of each user is stored in the corresponding partition of the structured database.

4. The method of claim 3, further comprising: A multi-level index is established based on the behavior link identifier of each user, the behavior chain status corresponding to each user's behavior link, the user identifier of each user, the behavior start date of each user, and at least one behavior node data in the behavior link data of each user; each behavior node data includes the timestamp of each user's behavior event, the page identifier corresponding to each user's behavior event, and the target operation behavior corresponding to each user's behavior event. Based on the start date of the behavior, a hot and cold data separation strategy is implemented on the behavior link data of each user in the structured database.

5. The method as described in claim 1, wherein querying target behavior link data from the structured database in response to a data query request sent by the second terminal includes: In response to a data query request sent by the second terminal, the target partition in the structured database is located based on the target query time range and target scene identifier in the data query request. Based on the target user identifier in the data query request, query the target behavior link data from the target partition.

6. A data processing method applied to a first terminal, the first terminal having a target client installed, the method comprising: Monitor user behavior events; Each user behavior event is triggered by a target operation behavior in the target client; In response to the detection of any user behavior event, determine whether the user behavior event meets the preset reporting conditions; If any user behavior event meets the preset reporting conditions, any data point data corresponding to any user behavior event will be sent to the server, so that the server can receive the data point data sent by the first terminal. Based on the data from each tracking point, behavioral link data for each user is constructed; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario. The behavioral data of each user is stored in a structured database; In response to a data query request sent by the second terminal, target behavior link data is queried from the structured database; the target behavior link data is then sent to the second terminal so that the second terminal can display the data based on the target behavior link data.

7. The method as described in claim 6, wherein the step of determining whether the user behavior event meets a preset reporting condition in response to detecting any user behavior event includes: In response to the detection of any user behavior event, determine whether the target client's operating environment meets the first preset condition; If the target client's operating environment meets the first preset condition, determine whether the behavioral attribute associated with any user behavior event meets the second preset condition. If the behavioral attributes associated with any user behavior event satisfy the second preset condition, then the user behavior event is determined to satisfy the preset reporting condition.

8. A data processing method applied to a second terminal, the method comprising: In response to a data query operation, a data query request is generated; Send the data query request to the server; Receive target behavior link data sent by the server; the target behavior link data is obtained by the server from a structured database based on the data query request; The structured database includes behavioral link data for each user; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario; the behavioral link data for each user is constructed based on the data from each tracking point. Any data point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; Each user behavior event is triggered by a target operation behavior in the target client; Render the user behavior storyline based on at least one target behavior node data in the target behavior link data; The user behavior storyline is presented in the form of a timeline, on which each target interaction node is marked in chronological order with the data of each target behavior node. In response to a trigger operation on any target interaction node, the target behavior node data corresponding to that target interaction node is displayed.

9. A data processing system, characterized in that, The data processing system includes: a server, a first terminal, and a second terminal; wherein... The first terminal is used to listen to various user behavior events, which are triggered by various target operation behaviors in the target client; in response to listening to any user behavior event, it determines whether the user behavior event meets the preset reporting conditions; if the user behavior event meets the preset reporting conditions, it sends any data point data corresponding to the user behavior event to the server. The server is used to receive data from various tracking points sent by the first terminal; construct behavioral link data for each user based on the data from various tracking points; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario; and store the behavioral link data for each user in a structured database. The second terminal is used to generate a data query request in response to a data query operation and send the data query request to the server. The server is further configured to respond to a data query request sent by the second terminal by querying target behavior link data from the structured database and sending the target behavior link data to the second terminal; The second terminal is further configured to receive target behavior link data sent by the server; render a user behavior storyline based on at least one target behavior node data in the target behavior link data; the user behavior storyline is presented in the form of a timeline, on which target interaction nodes corresponding to each target behavior node data are marked in chronological order; and in response to a trigger operation on any target interaction node, display is performed based on the target behavior node data corresponding to any target interaction node.

10. A data processing apparatus, applied to a server, the apparatus comprising: The first receiving module is used to receive data from various embedded points sent by the first terminal; Any data point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; Each user behavior event is triggered by a target operation behavior in the target client; The construction module is used to construct the behavior link data of each user based on the data from each tracking point; the behavior link data of each user is used to describe the behavior trajectory of each user in the target business scenario; The storage module is used to store the behavioral data of each user into a structured database; The query module is used to query target behavior link data from the structured database in response to a data query request sent by the second terminal. The first sending module is used to send the target behavior link data to the second terminal so that the second terminal can display based on the target behavior link data.

11. A data processing apparatus, applied to a first terminal, the first terminal having a target client installed, the apparatus comprising: The listening module is used to monitor various user behavior events; Each user behavior event is triggered by a target operation behavior in the target client; The judgment module is used to respond to any user behavior event detected by listening to determine whether the user behavior event meets the preset reporting conditions. The second sending module is used to send any data point data corresponding to any user behavior event to the server when any user behavior event meets the preset reporting conditions, so that the server receives the data point data sent by the first terminal. Based on the data from each tracking point, behavioral link data for each user is constructed; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario. The behavioral data of each user is stored in a structured database; In response to a data query request sent by the second terminal, target behavior link data is queried from the structured database; the target behavior link data is then sent to the second terminal so that the second terminal can display the data based on the target behavior link data.

12. A data processing apparatus, applied to a second terminal, the apparatus comprising: The generation module is used to generate data query requests in response to data query operations; The sending module is used to send the data query request to the server; The second receiving module is used to receive target behavior link data sent by the server; the target behavior link data is obtained by the server from a structured database based on the data query request; The structured database includes behavioral link data for each user; the behavioral link data for each user is used to describe the behavioral trajectory of each user in the target business scenario; the behavioral link data for each user is constructed based on the data from each tracking point. Any data point is sent by the first terminal when it detects any user behavior event that meets the preset reporting conditions; Each user behavior event is triggered by a target operation behavior in the target client; The rendering module is used to render the user behavior storyline based on at least one target behavior node data in the target behavior link data; The user behavior storyline is presented in the form of a timeline, on which each target interaction node is marked in chronological order with the data of each target behavior node. The display module is used to respond to a trigger operation on any target interaction node and display the target behavior node data corresponding to the target interaction node.

13. An electronic device, comprising: Processor and memory; The memory stores a computer program, and when the processor executes the computer program, it implements the method steps of any one of claims 1-8.

14. A computer storage medium storing a plurality of instructions adapted for loading by a processor and performing the method steps of any one of claims 1-8.

15. A computer program product comprising a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1-8.

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