Method, device and equipment for processing data, medium and product

Abstract

The embodiment of the invention relates to a data processing method and device, equipment, a medium and a product. The method comprises the step of analyzing the acquired data file. The method further includes displaying data analysis content for the data file on the user interface based on the analysis, the data analysis content including the data. The method further includes displaying description content related to the generation of the data in response to receiving the operation for the data. Through the method, the user can further understand the source and the generation logic of the data while viewing the data analysis content, so that the transparency, the understandability and the credibility of the data analysis result are improved, and the use experience of the user on the data analysis result is improved.

Description

Technical Field

[0001] The embodiments of this disclosure generally relate to the field of data processing, and more specifically to methods, apparatuses, devices, media, and products for processing data. Background Technology

[0002] With the continuous development of data processing and intelligent analysis technologies, automated computing capabilities for data analysis have significantly improved in terms of data scale, processing efficiency, and analytical complexity. Data analysis can efficiently parse and process structured and semi-structured data, and through automated computing logic, generate multi-dimensional statistical, aggregation, and analytical results, greatly reducing the cost of manual analysis. This type of technology has been widely applied in various fields such as business analysis, data operations, and scientific research statistics, providing more efficient and flexible technical means for data value mining and information utilization.

[0003] With the continuous enhancement of computing power and the ongoing improvement of algorithm frameworks and software ecosystems, data analysis technology is constantly improving in terms of ease of use and intelligence. By introducing technologies such as automated logic generation, scripted computation, and intelligent assisted analysis, users can complete complex data processing tasks with a relatively low technical threshold. The development of related technologies has promoted the application of data analysis capabilities in multiple industries and business scenarios, providing a solid technical foundation for building an efficient and intelligent data processing system. Summary of the Invention

[0004] Embodiments of this disclosure provide a method, apparatus, device, medium, and product for processing data.

[0005] According to a first aspect of this disclosure, a method for processing data is provided. The method includes analyzing the data in response to receiving a first request from a user for analyzing the data from a client. The method further includes generating data analysis content for the data based on the analysis and sending it to the client for display, the data analysis content including data objects. The method also includes generating descriptive content related to the generation process of the data objects in response to receiving a second request for analyzing the data objects and sending it to the client for display.

[0006] According to a second aspect of this disclosure, a method for processing data is provided. The method includes sending a first request for analyzing data to a server in response to receiving an operation from a user for analyzing data. The method further includes displaying the data analysis content, including a data object, in response to receiving data analysis content related to the first request from the server. The method also includes sending a second request for analyzing the data object to the server in response to receiving an operation on the data object. The method further includes displaying the description content related to the generation process of the data object in response to receiving the second request from the server.

[0007] According to a third aspect of this disclosure, an apparatus for processing data is provided. The apparatus includes a data file analysis module configured to analyze data in response to receiving a first request from a user for analyzing data from a client; a data analysis content display module configured to generate data analysis content for the data based on the analysis and send it to the client for display, the data analysis content including data objects; and a description content display module configured to generate description content related to the generation process of the data objects and send it to the client for display in response to receiving a second request for analyzing the data objects.

[0008] According to a fourth aspect of this disclosure, an apparatus for processing data is provided. The apparatus includes a first request sending module configured to send a first request for data analysis to a server in response to receiving an operation from a user for data analysis; a first content display module configured to display data analysis content, including a data object, in response to receiving data analysis content related to the first request from the server; a second request sending module configured to send a second request for data object analysis to the server in response to receiving an operation related to the data object; and a second content display module configured to display descriptive content related to the generation process of the data object in response to receiving descriptive content related to the second request from the server.

[0009] In a fifth aspect of this disclosure, an electronic device is provided, including at least one processor; and a storage device for storing at least one program, which, when executed by at least one processor, causes at least one processor to implement the method according to a first or second aspect of this disclosure.

[0010] In a fourth aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method according to a first or second aspect of this disclosure.

[0011] In a fifth aspect of this disclosure, a computer program product is provided. This computer program product includes a computer program that, when executed by a processor, implements the method according to a first or second aspect of this disclosure.

[0012] It should be understood that the content described in this section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0013] The above and other objects, features and advantages of this disclosure will become more apparent from the accompanying drawings, in which like reference numerals generally denote like parts.

[0014] Figure 1 The illustration shows a schematic diagram of an example environment in which some embodiments of the present disclosure may be implemented;

[0015] Figure 2 The illustration shows a schematic diagram of an example method for processing data according to some embodiments of the present disclosure;

[0016] Figure 3 The illustration shows a schematic diagram of another example method for processing data according to some embodiments of the present disclosure;

[0017] Figure 4 The illustration shows a flowchart of an example method for data analysis and processing according to some embodiments of the present disclosure;

[0018] Figure 5 The illustration is a schematic diagram showing an example of tracing the source of analysis result values ​​according to some embodiments of the present disclosure;

[0019] Figure 6 The illustration shows an example of the processing approach and conversion logic for data source tracing according to some embodiments of the present disclosure;

[0020] Figure 7 The illustration shows a flowchart of an example process for tracing the numerical results of analysis results step by step according to some embodiments of the present disclosure;

[0021] Figure 8 The illustration shows a schematic block diagram of an apparatus for processing data according to some embodiments of the present disclosure;

[0022] Figure 9 The illustration shows a schematic block diagram of another apparatus for processing data according to some embodiments of the present disclosure;

[0023] Figure 10A schematic block diagram of an example device suitable for implementing various embodiments of the present disclosure is illustrated. Detailed Implementation

[0024] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0025] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0026] For example, upon receiving a user's proactive request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0027] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0028] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0029] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0030] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0031] In existing data analysis techniques, data is typically aggregated, calculated, and analyzed by parsing user-uploaded data files and using automatically generated programmatic calculation logic to output corresponding analysis results. This type of method has significant advantages in improving data processing efficiency and lowering the barrier to entry. However, because the calculation process is mainly completed through code execution, the analysis logic and intermediate calculation processes are often not directly perceptible to users. Users usually only obtain the final numerical analysis results and find it difficult to intuitively understand the specific source and formation process of these results.

[0032] Furthermore, existing data analysis products typically employ a uniform presentation format for result interpretation, failing to adequately differentiate between users' varying levels of understanding and verification needs. For users focused solely on the accuracy of results, those seeking to understand the computational logic, and those requiring self-verification through formulas and field-level information, current technologies struggle to simultaneously provide explanations tailored to their specific needs. This single-level result presentation leaves users lacking sufficient comprehension and verification tools when faced with complex calculations, limiting the effectiveness of data analysis results in trusted use and in-depth application scenarios.

[0033] Therefore, embodiments of this disclosure propose a method for processing data. In this method, in response to receiving a first request from a user on a client for data analysis, the server analyzes the data. Then, based on the analysis, the server generates data analysis content for the data and sends it to the client for display; the data analysis content includes data objects. In response to receiving a second request for analyzing the data objects, the server generates descriptive content related to the generation process of the data objects and sends it to the client for display. This method enables users to understand the source and generation logic of the data while viewing the data analysis content, improving the interactive experience during the data analysis process.

[0034] The embodiments of this disclosure will now be described in further detail with reference to the accompanying drawings. Figure 1 The illustration shows an example environment in which the devices and / or methods of embodiments of this disclosure may be implemented. In environment 100, server 102 and client 104 can process data to generate corresponding data analysis content and display it to the user.

[0035] Examples of server 102 include, but are not limited to, personal computers, server computers, multiprocessor systems, consumer electronics, minicomputers, mainframes, and distributed computing environments that include any of the above systems or devices. Examples of client 104 include, but are not limited to, personal computers, handheld or laptop devices, mobile devices (such as mobile phones, personal digital assistants (PDAs), media players, etc.), multiprocessor systems, consumer electronics, minicomputers, and mainframes.

[0036] like Figure 1 As shown, users can analyze data through a local client 102. For example, a user can select data to analyze and then perform the analysis. Therefore, the client interface can receive an operation 106 for data analysis, triggered by the user clicking a control for data analysis. Then, the client 102 sends a first request 108 for data analysis to the server 104. Upon receiving the first request 108, the server 104 can obtain the data. For example, it can obtain the data through a data identifier in the first request or include the data in the first request. Then, the server 104 performs analysis on the data to obtain data analysis content 110. By analyzing the data, the server 104 can parse the field information, data type, data distribution, and relationships between data to identify content that can be analyzed, further determine the organization of the data content, and the computational basis between data, providing necessary data support for the subsequent generation of data analysis content 110. In addition to generating data analysis content, the analysis can also generate data sources, which include certain fields. Some of the data objects in the data analysis content are the values ​​in these fields.

[0037] After completing the analysis of the data file, the server 104 further generates data analysis content 110 based on the analysis results. The server 104 then sends the generated data analysis content 110 to the client 102 for display 112, thereby showcasing the data analysis content through a user interface. The data analysis content displayed in the user interface includes data results obtained through statistical analysis, aggregation, or computation of data content or key values ​​in the data, such as data objects. By presenting the data analysis content in the user interface, users can directly view the analysis results related to the data without having to perform complex calculations on the raw data themselves.

[0038] During the data analysis content display process, client 102 supports users to perform operations 114 on data objects through the user interface. When client 102 detects that a user performs an operation such as clicking, selecting, or viewing on a data object, it will trigger the explanation and display process corresponding to that data object. At this time, client 102 will send a second request 116 to server 104 for analyzing the data object. After receiving the second request 116, server 104 will generate descriptive content 118 related to the generation process of the data object. For example, when generating data analysis content by performing data analysis operations, data source path information and field path information for the data object will also be generated. The data source path information indicates the generation path of the data source, and the field path information indicates the generation path of the field. Then, the data object can be analyzed based on the data source path information and field path information to generate descriptive content 118 for the generation process of the data object. Next, server 104 will send the descriptive content 118 to client 102 for display in the user interface 120. The descriptive content is used to explain the source and formation process of the data to enhance the user's understanding of the data analysis results.

[0039] The displayed description may include the calculation method of the data object, the upstream data source on which the data object depends, and a description of the process by which the data object is obtained from the upstream data. Client 102 can present the above description through text descriptions, structured information, or visualizations, so that users can intuitively understand that the data is not arbitrarily generated by the model, but is obtained from real data files through a clear analysis and calculation process.

[0040] For users who only care about the authenticity of the data, they can quickly confirm whether the data comes from a real data file by viewing the description. For users who have certain requirements for the calculation logic, they can understand whether the calculation path of the data meets expectations by viewing the description. For users who have high requirements for accuracy, they can verify the data themselves based on the displayed calculation method and source information.

[0041] This method enables the linked display of data analysis results and data generation explanations without increasing the user's operational burden. This allows users at different levels of understanding to obtain the corresponding information explanations according to their own needs, thereby improving the overall data analysis user experience and system interaction.

[0042] The above combination Figure 1 The following is a schematic diagram illustrating an example environment in which some embodiments of this disclosure may be implemented, in conjunction with... Figure 2 A schematic diagram illustrating example methods for processing data according to some embodiments of the present disclosure. Figure 2 The method in can be derived from Figure 1The server can be executed on 104 or any suitable device.

[0043] like Figure 2 As shown, in example method 200, at box 202, server 104 responds to receiving a first request from the client for data analysis from the user and analyzes the data. After receiving the first request from the client for data analysis, the server can obtain the data to be analyzed by the user and process it as the first data source. In this stage, the server reads data content from the data to obtain the raw data set for subsequent processing. This raw data set may include multiple fields, records, or data items to reflect the underlying information structure stored in the data file.

[0044] After reading data from the first data source, the server further performs a transformation operation on the first data source to generate data analysis content specific to it. This transformation operation maps the raw data in the first data source from its initial storage format to a data format suitable for analysis and calculation, and then generates subsequent data sources and fields within those data sources. In some embodiments, the transformation operation may include processing steps such as data format conversion, field renaming, type resolution, and data calculation to ensure that data from different sources or with different structures has a consistent representation during the analysis phase. Additionally, this transformation operation is implemented through a model.

[0045] During the data transformation process, the server can utilize data from the first data source to generate at least one second data source and a data object corresponding to at least one field included in the first second data source. The second data source represents the intermediate data result obtained after transformation of the original data, and each second data source can contain at least one field. This field is used to characterize the statistical or analytical results of a certain dimension or feature in the first data source. Furthermore, the data objects corresponding to the fields generated during the transformation process can be used to generate data analysis content for the data, enabling the data analysis content to present the overall characteristics of the first data source in a structured manner, including the data objects.

[0046] While generating the second data source and fields, the server can also obtain data source path information corresponding to at least one second data source and field path information corresponding to at least one field during the transformation process. This information is used to generate descriptive content related to the generation process of the data object. Data source path information describes the relationship between the second data source and its upstream data source, while field path information describes the generation process of a field from the original data or a field in the original data source to the current field. By recording data source path information and field path information, the server can provide path evidence for subsequent data tracing and display, calculation logic explanation, and result verification.

[0047] In some embodiments, fields are generated from at least one original field in a data file through arithmetic or aggregation operations. Arithmetic operations may include calculations such as addition, subtraction, multiplication, or division, while aggregation operations may include operations such as summation, average, maximum, minimum, or counting. By performing arithmetic or aggregation operations on the original fields, the server can extract statistically or business-related analytical fields from the original data, thereby improving the expressive power of the data analysis content.

[0048] Before performing analysis or transformation operations on the data in the data file, the server can also perform at least one preprocessing operation on the data. Preprocessing operations may include limiting the units of the data, filtering the data, or determining whether the data falls within a predetermined range. By limiting the units of the data, the server can avoid ambiguity in the calculation process due to data of different dimensions; by filtering the data, data records that do not meet the analysis conditions can be removed; by determining the range, abnormal or invalid data can be identified, thereby improving the accuracy and reliability of the data analysis results.

[0049] In the process of generating data analysis content, in addition to the data fields generated using the aforementioned transformation operations, the context associated with the data object, generated during the transformation operations, is also incorporated. For example, the textual descriptions preceding and following the data field in the data analysis content. The server then uses this data field combined with the contextual descriptions to form the data analysis content. Furthermore, this data transformation operation and the generation of the data analysis content are implemented by a data analysis model.

[0050] At box 204, the server generates data analysis content based on the analysis and sends it to the client for display. This data analysis content includes data objects. After completing the data analysis and processing, the server sends the resulting data analysis content to the client and presents it to the user through the user interface. This data analysis content visually reflects the state of the data after analysis, transformation, and calculation.

[0051] Data analysis content can include numerical results, statistical information, or analytical conclusions calculated based on fields, used to express the data's performance under specific analytical dimensions. The server 104 organizes this data in a structured format and sends it to the client to be mapped to the corresponding display area of ​​the user interface, allowing users to directly view the analysis results related to the data file.

[0052] In some embodiments, the display of data analysis content may include data items presented in the form of lists, tables, cards, or graphs, with each data item corresponding to an analysis result generated from a data file. The server can group or layout different data items based on data type, field characteristics, or display strategy, thereby forming a clear data analysis view in the user interface. In this way, users can quickly understand the analysis results of the data file without viewing the underlying data.

[0053] While displaying data analysis content on the user interface, the client can also configure interactive capabilities for data objects, enabling users to perform operations on specific data objects. For example, users can select or click on a data object on the interface, which serves as a trigger for subsequently displaying descriptive content related to the data object's generation process. By associating data analysis content with user interactions, the client can provide an entry point for further data understanding and tracing while displaying analysis results.

[0054] At box 206, in response to receiving the second request for analyzing the data object, the server generates descriptive content related to the data object's generation process and sends it to the client for display. When a user performs actions such as clicking, selecting, or hovering over a piece of data in the client's user interface, the client detects the action and triggers the display process of the descriptive content corresponding to that data object.

[0055] In the description content display process, client 102 sends a second request 116 to server 104 for analyzing the data object. Next, based on this second request, the server retrieves the third data source and the first field corresponding to the data object. For example, the field to which the data object belongs and the data source to which that field belongs. Then, the server further retrieves the data source path information for the third data source and the field path information for the first field. Then, based on the data source path information and the field path information, it determines how the data object was obtained. For example, which field the data object was obtained from and the definition of that field, and may also include data source-related information. Finally, the server sends the description content to the client for display.

[0056] This method establishes a connection between data sources and computational logic during the generation of data analysis results, ensuring clear transformation paths and computational bases for data at different analysis stages. Users can maintain ease of operation while gaining a clear understanding of data authenticity, computational rationality, and generation accuracy, thus enhancing the overall credibility of data analysis results and the user experience.

[0057] The above combination Figure 2Schematic diagrams illustrating example methods for processing data according to some embodiments of this disclosure are provided. These example methods represent a server-side processing flow. The following is in conjunction with… Figure 3 The illustration depicts another example method for processing data according to some embodiments of the present disclosure, which is a client-side processing flow. Figure 3 The method in can be derived from Figure 1 It can be executed on client 102 or any suitable device.

[0058] At box 302, in response to receiving an operation from the user for analyzing data, client 102 sends a first request for data analysis to the server. The client can present data analysis functionality to the user through a user interface. For example, the user can select data to be processed in the user interface and then analyze the data by triggering the corresponding interface element. At this time, client 102 can send a first request for data analysis to the server. Additionally, this first request may contain a data identifier for the data to be analyzed, or the first request may include the data to be analyzed. After receiving the request, the server can obtain the data, for example, by using the data identifier. Then, the server analyzes the data, as in the analysis process in example method 200, and then generates data analysis content and sends it to client 102.

[0059] At box 304, client 102 responds to receiving the data analysis content for the first request from the server and displays the data analysis content, which includes data objects. After receiving the data analysis content, the client displays it on the user interface. For example, the analysis content includes a description of the analysis of the entire data. If the data to be analyzed is a log file, the analysis results for that log can be displayed, such as what operations were performed, the number of times they were performed, or the main tasks completed. Additionally, the analysis content also includes data objects, such as specific numerical values.

[0060] At box 306, in response to receiving an operation on a data object, client 102 sends a second request to the server for analyzing the data object. After presenting the data analysis content to the user, the user will browse the content. When the user views some data objects, they may need to know the source of these data objects or whether the data objects are correct. At this time, the user can perform an operation on the data object, such as clicking on the data object. Then, the client sends a second request to the server for analyzing the data object.

[0061] At box 308, client 102 responds to receiving a description of the data object's generation process from the server in response to the second request, and displays the description. After receiving the second request, the server analyzes the data object. For example, it uses the field path information of the data object's fields and the data source path information of the data source to obtain a description of the data object's generation process. Upon receiving this description, the client can display it on the first interface element.

[0062] In this process, the client first displays a first interface element in the user interface, which carries descriptive information related to the generation process of the data object. The first interface element can be presented in the form of a bubble, overlay, pop-up, or sidebar, and is associated with the data triggered by the user's operation at the interface location, so that the user can clearly understand the data object corresponding to the currently displayed descriptive content.

[0063] In some embodiments, when displaying descriptive content related to the data generation process on the first interface element, the first interface element may display descriptions of fields corresponding to the data object, field definitions, and the data source where the data object resides. Users can also further view information about the data source. If an operation is received on the data source, detailed information about the data source can be displayed. For example, in the first interface element, the client can display field information corresponding to the data, as well as information about the data source, such as field descriptions and definitions. In some embodiments, when a user further performs an operation on the data source information displayed in the first interface element, the client responds to the operation and displays detailed information about the data source in the user interface. This detailed information may include the name of the data source, data structure, field descriptions, or data record range, to help users understand the specific location and organization of the data in the data file.

[0064] In some embodiments, when displaying descriptive content related to the data generation process on a first interface element, content describing the data calculation process may also be displayed on the first interface element, and a second interface element for obtaining data source information may also be displayed on the first interface element. The second interface element may be presented as a button, link, or clickable icon to guide the user to further view the underlying data source and transformation process. In one example, if an operation is received on the second interface element, the data source containing the data object and the transformation operation that generated the data source are displayed. In another example, if an operation is received on the second interface element, the data content in the data source, including the data object, is displayed.

[0065] For example, the first interface element can display text content describing the data calculation process. This text content summarizes the calculation logic of the data in natural language, describing how the data is generated from raw data through transformation, filtering, operation, or aggregation. Through this text content, users can determine whether the current data calculation method is consistent with their own business understanding or calculation logic.

[0066] When a user performs an operation on a second interface element, the client responds to the operation and performs one of the following operations: On the one hand, the client can display the data source including the current data and the transformation operation information that generated the data source in the user interface, thereby showing the data transformation process from the original data file to the current data in a chain form; on the other hand, the client can also directly display the specific data content in the data source, so that the user can view the original data records used to calculate the current data.

[0067] This method enables the visualization of data sources during the generation of data analysis results, revealing the transformation path and calculation basis of data objects. Users can gain a clear understanding of the data's authenticity, calculation rationality, and generation accuracy while maintaining simple operation, thus improving the overall credibility of the data analysis results and the user experience.

[0068] The above combination Figure 3 Schematic diagrams illustrating example methods for processing data according to some embodiments of this disclosure are shown below. Figure 4 A flowchart describing an example method for data analysis and processing according to some embodiments of the present disclosure. Figure 4 Example method 400 is in Figure 2 The operations performed during data transformation in the example methods described can be performed by... Figure 1 The server can handle 104 errors or any suitable device.

[0069] like Figure 4 As shown, Example Method 400 illustrates a data analysis and processing flow for data sources and derived fields. When the server performs data analysis on the user-uploaded data source, it structures and records the data source transformation logic and the resulting derived fields. While generating the analysis result values, it simultaneously constructs the corresponding data source path and field reference path, thereby achieving a traceable display of the analysis results.

[0070] The server obtains the first data source 402, which can be a raw file uploaded by the user or a data set imported from an external system. Based on the first data source 402, the server determines several raw fields associated with it, including field 404, field 406, and field 408. These three fields can be used to describe the basic data fields in the data source that can be directly read or analyzed.

[0071] Subsequently, the server performs aggregation or operation processing on the original fields 404 and 406 according to preset transformation logic to generate at least one derived field 412. The transformation logic may include addition, filtering, association, or summary operations to map multiple original fields into derived fields with business meaning. The generated derived field 412 is recorded as the result obtained from the original fields through the transformation logic.

[0072] The server generates a second data source 410 based on the first data source 402 and the transformation logic. The second data source 410 contains derived fields 412 and other related derived fields 414, and is used as the data foundation for subsequent analysis and result presentation. At the same time, the server records the reference relationship between the second data source 410 and the first data source 402 to form a traceability link between data sources.

[0073] In addition to generating a second data source 410, the server can also create a third data source 416 based on transformation operations, and further identify the corresponding derived fields 418 or 420. When outputting the final value, the server synchronously generates the path information corresponding to the value. The path information can be used to indicate the position of the derived field from which the value originates in the corresponding data source.

[0074] This method provides users with a complete traceability path from the numerical value to derived fields and then to the data source. This allows for the demonstration of the calculation logic related to the numerical value, the relationships between derived fields, and the data source transformation process during subsequent operations, thereby improving the interpretability and verifiability of the analysis results.

[0075] The above combination Figure 4 A flowchart describing an example method for data analysis and processing according to some embodiments of this disclosure is presented below; in conjunction with Figure 5 A schematic diagram illustrating examples of tracing the source of analysis result values ​​according to some embodiments of this disclosure, corresponding to... Figure 2 and Figure 3 This is an example of a data analysis process that displays content and performs operations on the data.

[0076] like Figure 5 As shown, example interface 500 demonstrates an interactive, traceable interface structure for presenting the numerical results and their associated explanations during the data analysis results display phase. After completing the statistical analysis of the page data, the server simultaneously displays summary information of key fields and corresponding traceability information areas in the unified client interface, allowing users to further understand and verify the source and calculation basis of the conclusions while viewing them.

[0077] On the left side of the interface, the client displays an overview of key page data fields in a structured table format, including total number of pages, number of unique user identifiers, total number of messages, total number of edits, average number of messages per page, and median number of messages per page, providing a general overview of page usage. Below this area, the client generates analysis conclusion text based on the fields. The analysis conclusions marked 502, 504, and 506 are interactive elements, used to indicate values ​​or fields highly relevant to the current analysis conclusion.

[0078] When a user clicks on the interactive content 502 in the analysis conclusion text, the client responds to the interaction by updating the data source display area on the right side of the interface to present the analysis result value and its source information corresponding to the clicked content. The interactive content guides users directly from the conclusion description to the key values ​​supporting the conclusion, thus establishing an intuitive connection between the conclusion text and the data.

[0079] On the right side of the interface, the client presents the calculation information corresponding to the currently selected value in a traceability display format. This area includes a result value display area, a calculation method display area, and a related field display area. The calculation method display area explains the calculation logic of the result value, such as the method of averaging or summarizing specific fields. Box 508, representing the average number of messages per page, indicates the field currently being traced. The calculation method display area presents the generation logic of the result value in a concise, natural language description, allowing ordinary users to intuitively understand the source of the result value without delving into the complete field or data source chain. The dotted boxes 510 and 512 in the related field display area represent derived fields involved in the calculation from the original field, enabling users to understand the compositional relationships of the result value. The related field display area presents the derived fields involved in the generation of the result value and their interrelationships in a structured manner, allowing users with certain accuracy requirements to understand the basis of the result value's composition without delving into the original data source.

[0080] In addition, the right side of the interface includes a data source display area, which can be used to identify the data files on which the analysis results are based. When the user clicks on the interactive content in the analysis conclusion text at point 514, the client can further expand the traceability information related to the data source to show the reference relationship between the result values ​​and the original data files. The data source display area allows users with high accuracy requirements to verify the result values ​​step by step by expanding the field chain and data source chain.

[0081] This method can provide users with an actionable traceability entry point based on the conclusions while displaying the data analysis results, enabling users to verify and understand the analysis results as needed, thereby improving the transparency, credibility, and overall user experience of the data analysis results.

[0082] The above combination Figure 5 A schematic diagram illustrating examples of tracing the source of analysis results numerical values ​​according to some embodiments of this disclosure is provided below. Figure 6 A flowchart describing an example process for tracing the numerical results of analysis according to some embodiments of this disclosure. Figure 6 Yes Figure 5 The content displayed after clicking on the data source in the file.

[0083] like Figure 6 As shown, example interface 600 demonstrates an interactive interface structure that traces and displays the data sources and data calibers upon which the analysis results are based during the data analysis results presentation stage. After the server completes the statistical analysis of the page data, the client simultaneously displays an overview of the analysis result fields and data source tracing information in a unified interface, allowing users to further understand the data sources and processing calibers upon which the analysis conclusions are based while viewing the analysis conclusions.

[0084] On the left side of the interface, the client displays an overview of key page data fields in a structured table format, including total number of pages, number of unique user IDs, total number of messages, total number of edits, average number of messages per page, and median number of messages per page. These fields provide a general overview of page usage. The left side also includes analysis conclusions generated from these fields, explaining the current statistical results and providing users with a holistic perspective on the data. Figure 5 As described. If the user clicks Figure 5 The data source shown is located in the right-hand area of ​​the interface. The client provides a data source traceability display area 602, which presents the data source information corresponding to the analysis results. The data source traceability display area includes data source identification information 604, input file information 606, and a description of the data scope corresponding to the data source 608, enabling users to clearly understand the data files and their sources upon which the current analysis results depend.

[0085] In the data scope display area, the client displays a textual explanation of the data record range, statistical granularity, and field processing rules. For example, the data scope explanation includes the definition of the object represented by each record, the method for determining the statistical unit, and the range of fields involved in the statistics, which is used to define the basis for the calculation of the analysis results.

[0086] In addition, the data caliber display area also includes explanations of field cleaning and rule processing methods, such as numerical processing rules for fields like message count, edit count, and page number, as well as deduplication or matching rules for fields like user identifier and sharing status. These rules describe the necessary processing operations performed on the raw data during the generation of statistical fields, enabling users to understand the conditions under which the analysis results are formed.

[0087] This method allows for the association and display of analysis results with their corresponding data sources and data definitions without directly exposing the underlying processing code. This enables users to trace the data source and statistical rules step by step from the result fields, improving the transparency, understandability, and credibility of the data analysis results.

[0088] The above combination Figure 6 A flowchart illustrating an example process for tracing the numerical results of analysis according to some embodiments of this disclosure is provided below. Figure 7 A flowchart describing an example process for tracing the numerical results of analysis according to some embodiments of this disclosure, corresponding to... Figure 2 and Figure 3 The example method is another example of a process for displaying data analysis content and manipulating data.

[0089] like Figure 7 As shown in the example interface 700, an interactive process for tracing the source of data analysis results is presented. When a user views the data analysis results page, the client presents the result values ​​in an interactive manner, allowing the user to trigger a traceability display related to the generation process of the result values ​​through their actions. This achieves a layered interpretation and understandable presentation of the data analysis results.

[0090] In the initial stage of the process, the client displays the analysis results, including numerical values, on the first interface at box 702. When the user clicks on the corresponding numerical value (e.g., "12.2") on the first interface, the client responds by generating a pop-up tooltip 704 near the numerical value. This tooltip briefly explains how the numerical value was generated and provides an entry point for further tracing operations, allowing the user to quickly determine whether the numerical value was generated based on the actual analysis process. The pop-up tooltip includes a button 706 to trigger data source tracing. When the user clicks the data source tracing button in the pop-up tooltip, the client displays a floating tracing interface 708, showing the data source information most relevant to the numerical value and the corresponding calculation logic explanation. This allows the user to understand whether the calculation logic of the numerical value matches their understanding of the calculation method.

[0091] In the floating window, the client displays the result value 710 and can highlight the corresponding position of the result value in the target data source to indicate the relationship between the result value and the target data source. This helps users intuitively confirm that the result value is not arbitrarily generated by the model, but comes from a clear data foundation.

[0092] In addition, the floating window displays transformation logic information describing how the target data source was generated from the previous level data source, and further presents the calculation formulas or calculation paths related to the result values ​​in the box, allowing users with high accuracy requirements to verify the result values ​​themselves based on the displayed information. When the user continues to perform the upstream tracing operation, the client further displays the upstream data source and its corresponding transformation process in box 712.

[0093] This method enables clients to provide differentiated information support to users at different levels of understanding, thereby comprehensively improving the credibility, interpretability, and user interaction experience of data analysis results while maintaining the simplicity of the interface.

[0094] Figure 8 The illustration shows a schematic block diagram of an apparatus for processing data according to some embodiments of the present disclosure. Figure 8 As shown, device 800 can Figure 1 Implemented in server 104, and corresponding to method 200. The apparatus 800 includes a data file analysis module 802, configured to analyze data in response to receiving a first request from a user for data analysis from a client; a data analysis content display module 804, configured to generate data analysis content for the data based on the analysis and send it to the client for display, the data analysis content including data objects; and a description content display module 806, configured to generate description content related to the generation process of the data objects and send it to the client for display in response to receiving a second request for data object analysis.

[0095] In some embodiments, the data file analysis module 802 includes: a data acquisition module configured to acquire data as a first data source; and a data conversion module configured to perform conversion operations on the first data source to generate data analysis content for the first data source.

[0096] In some embodiments, the data transformation module includes: a second data source generation module configured to generate at least one second data source and a data object corresponding to at least one field of the at least one second data source based on a transformation operation; and a data analysis content generation module configured to generate data analysis content for the first data source based on the data object.

[0097] In some embodiments, the data conversion module further includes a data source path information and field path information acquisition module, configured to generate data source path information for at least one second data source and field path information for at least one field based on the conversion operation, for use in generating descriptive content related to the generation process of the data object, wherein the data source path information indicates the generation path of the data source and the field path information indicates the generation path of the field.

[0098] In some embodiments, at least one field is generated from at least one original field in the first data source through arithmetic or aggregation operations.

[0099] In some embodiments, the data analysis content generation module includes: a context acquisition module configured to acquire the context associated with the data object; and a generation module configured to generate data analysis content based on the data object and the context.

[0100] In some embodiments, the data source and field determination module is configured to describe the content display module 806 as including:

[0101] The third data source and the first field related to the data object are determined; and the process-related content generation module is configured to generate descriptive content related to the generation process of the data object based on the data source path information for the third data source and the field path information for the first field.

[0102] In some embodiments, the apparatus 800 further includes a preprocessing execution module configured to perform preprocessing on the data before analyzing the data, the preprocessing including at least one of the following: defining the units of the data; filtering the data; or determining whether the data is within a predetermined data range.

[0103] Figure 9 A schematic block diagram of another apparatus for processing data according to some embodiments of the present disclosure is illustrated. Figure 9 As shown, device 900 can Figure 1 Implemented in client 102, and corresponding to method 300. The apparatus 900 includes a first request sending module 902, configured to send a first request for data analysis to a server in response to receiving an operation from a user for data analysis; a first content display module 904, configured to display data analysis content, including data objects, in response to receiving data analysis content related to the first request from the server; a second request sending module 906, configured to send a second request for data object analysis to the server in response to receiving an operation related to the data object; and a second content display module 908, configured to display descriptive content related to the generation process of the data object in response to receiving descriptive content related to the second request from the server.

[0104] In some embodiments, the second content display module 908 includes a description content display module configured to display description content related to the generation process of the data object on a first interface element.

[0105] In some embodiments, the description content display module includes: a data object information display module, configured to display the description content of the field corresponding to the data object, the definition of the field, and the data source where the data object is located on a first interface element; and a detailed information display module, configured to display detailed information about the data source in response to receiving an operation on the data source.

[0106] In some embodiments, the description content display module includes: a first display module configured to display content describing the calculation process of data on a first interface element; a second display module configured to display a second interface element for obtaining source information of data; and an action execution module configured to, in response to receiving an operation on the second interface element, perform one of the following: display the data source where the data object is located and the conversion operation that generates the data source; or display the data content in the data source that includes the data object.

[0107] Figure 10 A schematic block diagram of an example device 1000 that can be used to implement embodiments of the present disclosure is shown. Figure 1 The client 102 and server 104 can be implemented using device 1000. As shown, device 1000 includes a central processing unit (CPU) 1001, which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) 1002 or loaded from storage unit 1008 into random access memory (RAM) 1003. RAM 1003 can also store various programs and data required for the operation of device 1000. CPU 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Input / output (I / O) interface 1007 is also connected to bus 1004.

[0108] Multiple components in device 1000 are connected to I / O interface 1007, including: input unit 1006, such as keyboard, mouse, etc.; output unit 1007, such as various types of monitors, speakers, etc.; storage unit 1008, such as disk, optical disk, etc.; and communication unit 1009, such as network card, modem, wireless transceiver, etc. Communication unit 1009 allows device 1000 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0109] The various processes and procedures described above, such as methods 200 and 300, can be executed by processing unit 1001. For example, in some embodiments, methods 200 and 300 can be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 1008. In some embodiments, part or all of the computer program can be loaded and / or installed on device 1000 via ROM 1002 and / or communication unit 1009. When the computer program is loaded into RAM 1003 and executed by CPU 1001, one or more actions of the example methods 200 and 300 described above can be performed.

[0110] This disclosure can be a method, apparatus, system, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of this disclosure.

[0111] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0112] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0113] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0114] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0115] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0116] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0118] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for processing data, comprising: In response to receiving a first request from a user on a client for data analysis, the data is analyzed. Based on the analysis, data analysis content for the data is generated and sent to the client for display. The data analysis content includes data objects. as well as In response to receiving a second request for analyzing the data object, a description of the data object's generation process is generated and sent to the client for display.

2. The method according to claim 1, wherein analyzing the data includes: Obtain the data that serves as the first data source; as well as The first data source is transformed to generate data analysis content specific to the first data source.

3. The method according to claim 2, wherein the conversion operation on the first data source includes: Based on the transformation operation, at least one second data source and a data object corresponding to at least one field included in the at least one second data source are generated; as well as Based on the data object, the data analysis content for the first data source is generated.

4. The method according to claim 3, wherein the conversion operation on the first data source further includes: Based on the transformation operation, data source path information for the at least one second data source and field path information for the at least one field are generated to generate descriptive content related to the generation process of the data object. The data source path information indicates the generation path of the data source, and the field path information indicates the generation path of the field.

5. The method according to claim 3, wherein the at least one field is generated by at least one original field in the first data source through arithmetic or aggregation operations.

6. The method according to claim 3, wherein generating the data analysis content for the first data source based on the data object includes: Obtain the context associated with the data object; as well as The data analysis content is generated based on the data object and the context.

7. The method of claim 1, wherein generating the descriptive content related to the generation process of the data object includes: Determine the third data source and the first field associated with the data object; as well as Based on the data source path information for the third data source and the field path information for the first field, a description related to the generation process of the data object is generated.

8. The method according to claim 1, further comprising: Before analyzing the data, the data is preprocessed, and the preprocessing includes at least one of the following: Define the units of the data; Filter the data; or Determine whether the data is within the predetermined data range.

9. A method for processing data, comprising: In response to receiving an operation from the user for analyzing data, a first request for analyzing data is sent to the server; In response to receiving data analysis content for the first request from the server, the data analysis content is displayed, and the data analysis content includes a data object; In response to receiving an operation on the data object, a second request for analyzing the data object is sent to the server; as well as In response to receiving a description of the data object's generation process from the server in connection with the second request, the description is displayed.

10. The method of claim 9, wherein displaying the description includes: The description related to the generation process of the data object is displayed on the first interface element.

11. The method of claim 10, wherein displaying the descriptive content related to the generation process of the data object on the first interface element comprises: The first interface element displays the description of the field corresponding to the data object, the definition of the field, and the data source where the data object is located; as well as In response to receiving an operation for the data source, display detailed information for the data source.

12. The method of claim 10, wherein displaying the descriptive content related to the generation process of the data object on the first interface element comprises: Display content describing the calculation process of the data object on the first interface element; Displays a second interface element for obtaining source information of the data object; as well as In response to receiving an operation for the second interface element, perform one of the following: Displays the data source containing the data object and the transformation operation that generated the data source; or Displays the data content of the data object in the data source.

13. An apparatus for processing data, comprising: The data file analysis module is configured to analyze the data in response to receiving a first request from a user on a client for data analysis. The data analysis content display module is configured to generate data analysis content for the data based on the analysis and send it to the client for display. The data analysis content includes data objects. as well as The description content display module is configured to, in response to receiving a second request for analyzing the data object, generate description content related to the generation process of the data object and send it to the client for display.

14. An apparatus for processing data, comprising: The first request sending module is configured to send a first request for data analysis to the server in response to receiving an operation from the user for data analysis. The first content display module is configured to display the data analysis content, which includes a data object, in response to receiving data analysis content for the first request from the server. as well as The second request sending module is configured to send a second request to the server for analyzing the data object in response to receiving an operation on the data object. as well as The second content display module is configured to display the description content in response to receiving from the server a description of the data object's generation process in response to the second request.

15. An electronic device comprising: At least one processor; as well as A memory for storing at least one program, which, when executed by the at least one processor, causes the at least one processor to implement the method according to any one of claims 1-12.

16. A computer-readable storage medium having a computer program stored thereon, the computer program implementing the method according to any one of claims 1-12 when executed by a processor.

17. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-12.

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