Intelligent data analysis workflow system and method based on ChatBI

Abstract

The invention discloses an intelligent data analysis workflow system and method based on ChatBI, and relates to the technical field of natural language processing and intelligent data analysis. A workflow stage is divided, and system cue words are provided according to the workflow stage, and the method comprises the following steps: an analysis intention recognition stage, establishment of different semantic models, arrangement of the semantic models through the system cue words, generation of initial analysis dimensions in combination with historical problems or agents, an intention clarification stage, and demand adjustment according to user feedback. The method comprises the following steps: verifying the rationality of operation through an intelligent agent and generating an adjustment suggestion, which comprises the steps of newly adding or merging indexes, performing a data preparation stage, executing data type cleaning, performing dimension and index correction, optimizing a data set by the intelligent agent according to domain knowledge, performing a report production stage, generating a chart configuration template, and recommending a chart type and an analysis model by the intelligent agent. A large model selects an analysis model, a preliminary analysis summary is generated, a report optimization stage is carried out, a user puts forward modification suggestions and intelligent agent verification logic, a chart configuration template is regenerated, and analysis content is combined.

Description

Technical Field

[0001] The present invention discloses an intelligent data analysis workflow system and method based on ChatBI, relating to the technical field of natural language processing and intelligent data analysis. Background Art

[0002] Business intelligence (BI) tools require users to manually configure analysis dimensions, metrics, and models. This relies on specialized data knowledge, resulting in cumbersome interaction processes and a lack of user friendliness for non-technical users. Existing technologies lack intelligent demand analysis capabilities, making it difficult to dynamically respond to diverse user needs. For example, when users repeatedly adjust analysis dimensions or regenerate reports, existing tools are unable to adapt quickly, resulting in low efficiency. Summary of the Invention

[0003] In response to the problems of the existing technology, the present invention provides an intelligent data analysis workflow system and method based on ChatBI, introduces a phased workflow design, a dual prompt word collaboration mechanism and a professional intelligent agent, and solves the problems of low interaction efficiency and insufficient dynamic optimization capabilities in the existing technology.

[0004] The specific scheme proposed by the present invention is:

[0005] The present invention provides an intelligent data analysis workflow method based on ChatBI, which divides the workflow into stages and provides prompt words according to the workflow stages, including:

[0006] In the analysis intention recognition stage, different semantic models are established, the semantic models are sorted out through system prompt words, and the initial analysis dimensions are generated by combining historical questions or intelligent agents.

[0007] In the intention clarification phase, demand adjustments are made based on user feedback. The agent verifies the rationality of the operation and generates adjustment suggestions, including adding or merging indicators.

[0008] In the data preparation phase, data type cleaning is performed, dimensions and indicators are corrected, and the agent optimizes the data set based on domain knowledge.

[0009] In the report preparation stage, a chart configuration template is generated, the intelligent agent recommends chart types and analysis models, the large model selects the analysis model, and generates a preliminary analysis summary.

[0010] During the report optimization phase, users make modification suggestions, the agent verifies the logic, regenerates the chart configuration template, and merges the analysis content.

[0011] Furthermore, the method of providing system prompts according to the workflow stages of the intelligent data analysis workflow based on ChatBI includes: presetting standardized prompts at each stage to guide large models and professional intelligent agents to perform tasks, and delivering requirements and triggering responses according to user prompts.

[0012] Furthermore, the ChatBI-based intelligent data analysis workflow method defines a semantic model prompt word interface, including: configuring an independent prompt word interface for each semantic model, storing description information, supporting cross-module reuse,

[0013] By calling the interface content through the intelligent agent, the analysis process is optimized in combination with domain knowledge.

[0014] The present invention also provides an intelligent data analysis workflow system based on ChatBI, including a stage management module and a prompt word management module. The stage management module divides the workflow into stages, and the prompt word management module provides prompt words according to the workflow stages, including:

[0015] The stage management module divides the analysis intention recognition stage, establishes different semantic models, organizes the semantic models through system prompt words, and generates initial analysis dimensions based on historical issues or intelligent agents.

[0016] In the intention clarification phase, demand adjustments are made based on user feedback. The agent verifies the rationality of the operation and generates adjustment suggestions, including adding or merging indicators.

[0017] In the data preparation phase, data type cleaning is performed, dimensions and indicators are corrected, and the agent optimizes the data set based on domain knowledge.

[0018] In the report preparation stage, a chart configuration template is generated, the intelligent agent recommends chart types and analysis models, the large model selects the analysis model, and generates a preliminary analysis summary.

[0019] During the report optimization phase, users make modification suggestions, the agent verifies the logic, regenerates the chart configuration template, and merges the analysis content.

[0020] Furthermore, the prompt word management module of the intelligent data analysis workflow system based on ChatBI provides system prompt words according to the workflow stage, including: pre-setting standardized prompt words for each stage, guiding large models and professional intelligent agents to perform tasks, and conveying requirements and triggering responses based on user prompt words.

[0021] Furthermore, the intelligent data analysis workflow system based on ChatBI also includes an interface management module, which defines the semantic model prompt word interface, including: configuring an independent prompt word interface for each semantic model, storing description information, and supporting cross-module reuse.

[0022] By calling the interface content through the intelligent agent, the analysis process is optimized in combination with domain knowledge.

[0023] The present invention also provides an intelligent data analysis workflow device based on ChatBI, comprising: at least one memory and at least one processor;

[0024] The at least one memory is configured to store a machine-readable program;

[0025] The at least one processor is used to call the machine-readable program to execute the ChatBI-based intelligent data analysis workflow method.

[0026] The present invention also provides a computer-readable medium having computer instructions stored thereon. When the computer instructions are executed by a processor, the processor executes the ChatBI-based intelligent data analysis workflow method.

[0027] The benefits of the present invention are:

[0028] The present invention forms a structured process and standardizes the stage division to improve logical clarity and scalability.

[0029] This invention realizes intelligent collaboration, deep integration of the dual prompt word mechanism and intelligent agent, and achieves accurate demand analysis and dynamic optimization.

[0030] The present invention is highly professional and provides domain knowledge support through intelligent agents to ensure the professionalism and compliance of analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 It is a schematic flow chart of the method of the present invention.

[0033] Figure 2 It is a schematic diagram showing the functions of each stage in the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described below with reference to the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it. However, the embodiments are not intended to limit the present invention.

[0035] Example 1

[0036] The present invention provides an intelligent data analysis workflow method based on ChatBI, which divides the workflow into stages and provides prompt words according to the workflow stages, including: presetting standardized prompt words for each stage, guiding the large model and professional intelligent agents to perform tasks, and transmitting requirements and triggering responses according to user prompt words,

[0037] The process of the present invention may include the following:

[0038] Divide workflow into stages and perform data analysis, including:

[0039] In the analysis intention recognition stage, different semantic models are established, the semantic models are sorted out through system prompt words, and the initial analysis dimensions are generated by combining historical questions or intelligent agents.

[0040] In the intention clarification phase, demand adjustments are made based on user feedback. The agent verifies the rationality of the operation and generates adjustment suggestions, including adding or merging indicators.

[0041] In the data preparation phase, data type cleaning is performed, dimensions and indicators are corrected, and the agent optimizes the data set based on domain knowledge.

[0042] In the report preparation stage, a chart configuration template is generated, the intelligent agent recommends chart types and analysis models, the large model selects the analysis model, and generates a preliminary analysis summary.

[0043] During the report optimization phase, users make modification suggestions, the agent verifies the logic, regenerates the chart configuration template, and merges the analysis content.

[0044] The present invention also defines the semantic model prompt word interface, including: configuring an independent prompt word interface for each semantic model, storing description information, supporting cross-module reuse, calling interface content through the intelligent agent, and optimizing the analysis process in combination with domain knowledge. Figure 2 .

[0045] Example 2

[0046] The present invention also provides an intelligent data analysis workflow system based on ChatBI, including a stage management module and a prompt word management module. The stage management module divides the workflow stages, and the prompt word management module provides system prompt words according to the workflow stages, including:

[0047] The stage management module divides the analysis intention recognition stage, establishes different semantic models, organizes the semantic models through system prompt words, and generates initial analysis dimensions based on historical issues or intelligent agents.

[0048] In the intention clarification phase, demand adjustments are made based on user feedback. The agent verifies the rationality of the operation and generates adjustment suggestions, including adding or merging indicators.

[0049] In the data preparation phase, data type cleaning is performed, dimensions and indicators are corrected, and the agent optimizes the data set based on domain knowledge.

[0050] In the report preparation stage, a chart configuration template is generated, the intelligent agent recommends chart types and analysis models, the large model selects the analysis model, and generates a preliminary analysis summary.

[0051] During the report optimization phase, users make modification suggestions, the agent verifies the logic, regenerates the chart configuration template, and merges the analysis content.

[0052] The information interaction, execution process and other contents between the modules in the above system are based on the same concept as the embodiment of the method of the present invention. For specific contents, please refer to the description in the embodiment of the method of the present invention and will not be repeated here.

[0053] Similarly, the system of the present invention can form a structured process, and the standardized stage division improves logical clarity and scalability; it realizes intelligent collaboration, and the dual prompt word mechanism is deeply integrated with the intelligent agent to achieve accurate analysis and dynamic optimization of needs; it is highly professional, and provides domain knowledge support through the intelligent agent to ensure the professionalism and compliance of the analysis results.

[0054] Example 3

[0055] The present invention also provides an intelligent data analysis workflow device based on ChatBI, comprising: at least one memory and at least one processor;

[0056] The at least one memory is configured to store a machine-readable program;

[0057] The at least one processor is used to call the machine-readable program to execute the ChatBI-based intelligent data analysis workflow method.

[0058] The information interaction, execution of readable program process, etc. of the processor in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. The specific contents can be found in the description of the embodiment of the method of the present invention and will not be repeated here.

[0059] Similarly, the device of the present invention can form a structured process, and the standardized stage division improves logical clarity and scalability; it realizes intelligent collaboration, and the dual prompt word mechanism is deeply integrated with the intelligent body to achieve accurate analysis and dynamic optimization of needs; it is highly professional, and provides domain knowledge support through the intelligent body to ensure the professionalism and compliance of the analysis results.

[0060] Example 4

[0061] The present invention also provides a computer-readable medium having computer instructions stored thereon. When executed by a processor, the computer instructions cause the processor to execute the ChatBI-based intelligent data analysis workflow method. Specifically, a system or device equipped with a storage medium can be provided. The storage medium stores software program code that implements the functions of any of the above-described embodiments, and the computer (or CPU or MPU) of the system or device can read and execute the program code stored in the storage medium.

[0062] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute part of the present invention.

[0063] Examples of storage media for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, the program code can be downloaded from a server computer via a communication network.

[0064] In addition, it should be clear that the functions of any of the above embodiments can be achieved not only by executing the program code read by the computer, but also by enabling the operating system operating on the computer to complete part or all of the actual operations based on the instructions of the program code.

[0065] In addition, it can be understood that the program code read from the storage medium is written into the memory provided in the expansion board inserted into the computer or into the memory provided in the expansion unit connected to the computer, and then based on the instructions of the program code, the CPU installed on the expansion board or expansion unit is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above embodiments.

[0066] It should be noted that not all steps and modules in the above-mentioned processes and system structures are required, and certain steps or modules can be omitted according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The system structure described in the above-mentioned embodiments can be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or may be implemented by certain components in multiple independent devices.

[0067] The above embodiments are merely preferred embodiments for the purpose of fully illustrating the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are within the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims.

Claims

1. An intelligent data analysis workflow method based on ChatBI, characterized by Divide the workflow into stages and provide prompt words according to the workflow stages, including: In the analysis intention recognition stage, different semantic models are established, the semantic models are sorted out through system prompt words, and the initial analysis dimensions are generated by combining historical questions or intelligent agents. In the intention clarification phase, demand adjustments are made based on user feedback. The agent verifies the rationality of the operation and generates adjustment suggestions, including adding or merging indicators. In the data preparation phase, data type cleaning is performed, dimensions and indicators are corrected, and the agent optimizes the data set based on domain knowledge. In the report preparation stage, a chart configuration template is generated, the intelligent agent recommends chart types and analysis models, the large model selects the analysis model, and generates a preliminary analysis summary. During the report optimization phase, users make modification suggestions, the agent verifies the logic, regenerates the chart configuration template, and merges the analysis content.

2. The ChatBI-based intelligent data analysis workflow method according to claim 1 is characterized by: The system prompt words are provided according to the workflow stages, including: presetting standardized prompt words for each stage, guiding the large model and professional intelligent agents to perform tasks, and conveying requirements and triggering responses according to user prompt words.

3. The ChatBI-based intelligent data analysis workflow method according to claim 1 is characterized by defining Semantic model prompt word interface, including: configuring an independent prompt word interface for each semantic model, storing description information, and supporting cross-module reuse. By calling the interface content through the intelligent agent, the analysis process is optimized in combination with domain knowledge.

4. An intelligent data analysis workflow system based on ChatBI, characterized by It includes a stage management module and a prompt word management module. The stage management module divides the workflow into stages, and the prompt word management module provides prompt words according to the workflow stages, including: The stage management module divides the analysis intention recognition stage, establishes different semantic models, organizes the semantic models through system prompt words, and generates initial analysis dimensions based on historical issues or intelligent agents. In the intention clarification phase, demand adjustments are made based on user feedback. The agent verifies the rationality of the operation and generates adjustment suggestions, including adding or merging indicators. In the data preparation phase, data type cleaning is performed, dimensions and indicators are corrected, and the agent optimizes the data set based on domain knowledge. In the report preparation stage, a chart configuration template is generated, the intelligent agent recommends chart types and analysis models, the large model selects the analysis model, and generates a preliminary analysis summary. During the report optimization phase, users make modification suggestions, the agent verifies the logic, regenerates the chart configuration template, and merges the analysis content.

5. The ChatBI-based intelligent data analysis workflow system according to claim 4 is characterized by: The prompt word management module provides system prompt words according to the workflow stage, including: presetting standardized prompt words for each stage, guiding the large model and professional intelligent agents to perform tasks, and conveying requirements and triggering responses based on user prompt words.

6. The ChatBI-based intelligent data analysis workflow system according to claim 4 is characterized by: It also includes an interface management module, which defines the semantic model prompt word interface, including: configuring an independent prompt word interface for each semantic model, storing description information, and supporting cross-module reuse. By calling the interface content through the intelligent agent, the analysis process is optimized in combination with domain knowledge.

7. An intelligent data analysis workflow device based on ChatBI, characterized by include: at least one memory and at least one processor; The at least one memory is configured to store a machine-readable program; The at least one processor is configured to call the machine-readable program to execute the ChatBI-based intelligent data analysis workflow method described in any one of claims 1 to 3.

8. Computer readable medium, characterized in that The computer-readable medium stores computer instructions, which, when executed by a processor, cause the processor to execute the ChatBI-based intelligent data analysis workflow method according to any one of claims 1 to 3.

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