Statistical method and system of BI report

Abstract

The invention relates to the technical field of data processing, and discloses a statistical method and system for BI reports. Comprising the steps of requirement analysis definition of BI report statistics, data collection and integration of the BI report statistics, data cleaning and conversion of the BI report statistics, data modeling support of the BI report statistics, design presentation of the BI report statistics, report development implementation of the BI report statistics, test verification optimization of the BI report statistics and release deployment online of the BI report statistics. According to the statistical method and system for the BI report, through deep demand analysis, report demands of a business department can be accurately understood, it is ensured that the statistical content and the display mode of the report meet actual business demands, blind development and resource waste of the report can be avoided, meanwhile, the practicability and the user satisfaction degree of the report are improved, and the user experience is improved. By utilizing advanced report development tools and technologies, the report statistics and display functions can be quickly and accurately realized, and the report development efficiency and quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and specifically to a statistical method and system for BI reports. Background Art

[0002] As an important tool for data-driven decision-making, business intelligence reports rely on a series of advanced technologies and methods. These technologies not only improve the efficiency of data processing but also greatly enrich the means of data analysis and presentation. The background technology of BI report statistical methods and systems covers multiple aspects such as data warehouse technology, ETL processing processes, OLAP analysis technology, data visualization methods, data integration technology, data mining technology, and report design technology. These technologies support and complement each other, jointly constituting a solid foundation for BI report statistics. By making full use of these technologies, enterprises can manage and utilize data resources more efficiently and provide strong support for decision-making. Business intelligence reports are a set of enterprise decision-making solutions that can integrate existing user data of enterprises, quickly and accurately provide reports, and give decision-making bases to help enterprises make wise business decisions. However, when faced with a large amount of user data, it becomes increasingly difficult to conduct BI report analysis relying on traditional relational databases. Therefore, the present application now proposes a statistical method and system for BI reports. Summary of the Invention

[0003] (I) Technical Problems to be Solved Aiming at the deficiencies of the prior art, the present invention provides a statistical method and system for BI reports, which has the advantages of significantly improving the accuracy and efficiency of report statistics and providing strong guarantee for enterprise data management and decision-making support, and solves the problem that it becomes increasingly difficult to conduct BI report analysis relying on traditional relational databases when faced with a large amount of user data.

[0004] (II) Technical Solutions To achieve the above object, the present invention provides the following technical solutions: A statistical method and system for BI reports, including clear demand analysis for BI report statistics, data collection and integration for BI report statistics, data cleaning and transformation for BI report statistics, data modeling support for BI report statistics, design and presentation for BI report statistics, report development and implementation for BI report statistics, test verification and optimization for BI report statistics, and release, deployment, and online for BI report statistics. The specific steps are as follows: S1. Clearly define the specific requirements and objectives of the report to form a detailed requirements document; S2. According to the requirements document, collect the required data from various data sources and perform integration processing; S3. Clean and transform the integrated data to solve data quality problems; S4. Design and implement a data model according to the report requirements and data characteristics; S5. Design the visual elements such as the interface layout, color scheme, and font size of the report according to the requirements document and the data model; S6. In the selected report development tool, implement the development of the report according to the design document; S7. Conduct a comprehensive test on the developed report; S8. Deploy the optimized report application to the production environment and perform configuration and debugging.

[0005] Preferably, the requirements analysis of the BI report statistics clearly includes the report type, display content, data range, and in-depth communication with relevant stakeholders such as report users and data providers to ensure the accuracy and comprehensiveness of the requirement understanding. Organize the results of the requirements analysis into a detailed requirements document to provide clear guidance for subsequent work; Requirements analysis is the starting point of the BI report statistics work, aiming to clarify the report's goals, audience, data range, and display requirements. This includes in-depth communication with business departments to understand their data needs, ensuring that the report can accurately reflect the business situation and provide strong support for decision-making.

[0006] Preferably, the data collection and integration of the BI report statistics include data source identification, data extraction, and data integration. The data sources include databases, data warehouses, and third-party data services. According to the requirements document, extract relevant data from each data source, integrate the extracted data to form a unified data view, and then perform subsequent processing; The data collection and integration stage involves extracting the required data from multiple data sources and performing integration processing. This process ensures the integrity, consistency, and accuracy of the data, laying a foundation for subsequent data cleaning and transformation.

[0007] Preferably, the data cleaning and transformation of the BI report statistics include data quality inspection, data cleaning, and data transformation, where: Data quality inspection: Check the integrity, accuracy, consistency, etc. of the data, identify and handle data errors; Data cleaning: Clean the identified data problems, including filling missing values, handling outliers, and converting data formats; Data transformation: Perform necessary transformations on the data according to the report requirements, including data aggregation and calculating new fields; Data cleaning and transformation are an essential part of BI report statistics. In this stage, problems such as missing values, outliers, and duplicate values in the data will be processed to ensure the cleanliness and accuracy of the data. At the same time, data transformation will be performed according to the report requirements, such as data aggregation, splitting, and format conversion, to meet the requirements of subsequent analysis.

[0008] Preferably, the data modeling support for the BI report statistics includes model design and model implementation. First, according to the data characteristics and report requirements, a suitable data model is designed, where the data model includes star model and snowflake model. Then, the designed data model is implemented in the data warehouse or data lake, and it is ensured that the organization and storage of data meet the report requirements. The data modeling stage aims to construct an efficient data structure and query path to support complex report statistics requirements, which may involve designs such as star model and snowflake model to improve the efficiency of data query and analysis.

[0009] Preferably, the report design and presentation of the BI report statistics designs the interface layout, color, and font of the report according to user requirements and aesthetic requirements, and designs the interactive functions of report filtering, sorting, and drilling down, and makes a prototype of the report for users to conduct preliminary evaluation and feedback. The design and presentation stage focuses on the visual effect and user experience of the report. According to the requirements document and data characteristics, the layout, color, font, etc. of the report are designed to ensure that the report is both beautiful and easy to understand. At the same time, the interactive functions of the report, such as filtering, sorting, drilling down, etc., are designed to improve the convenience of user use.

[0010] Preferably, the report development and implementation of the BI report statistics includes report tool selection, report development, and performance optimization. Among them, the report tool selection selects a suitable report development tool according to the complexity of the report and the team's technology stack, develops the report in the selected tool, realizes the interface design, data binding, and interactive functions, and optimizes the performance of the report to ensure that the loading speed and response speed of the report meet user requirements. In the report development and implementation stage, based on the design document and data model, the report will be developed using BI tools or custom development platforms. This includes data binding, interface rendering, and interactive function implementation.

[0011] Preferably, the test, verification, and optimization of the BI report statistics include function test, performance test, and user experience test, as follows: Function test: Test each function of the report to ensure the correctness and integrity of the function; Performance test: Test the performance of the report under different data volumes and different user concurrency situations; User experience test: Invite users to try out, collect feedback, and optimize and adjust the report; Test, verification, and optimization are the key steps to ensure the quality and performance of the report. In this stage, the report will be comprehensively tested, including function test, performance test, compatibility test, etc. According to the test results, the report will be optimized and adjusted to ensure that it meets user requirements.

[0012] Preferably, the release, deployment, and go-live of the BI report statistics include deployment preparation, deployment implementation, go-live training, and go-live monitoring. The specific steps are as follows: Step 1: Prepare the deployment server, database, and report tool environment; Step 2: Deploy the developed report to the production environment and perform final configuration and debugging; Step 3: Train users on report usage to ensure they can proficiently use the new report; Step 4: Continuously monitor the running status of the report and user feedback after going live, and promptly handle any issues that arise; Testing, verification, and optimization are key steps to ensure the quality and performance of the report. In this stage, comprehensive testing of the report will be carried out, including functional testing, performance testing, compatibility testing, etc. Based on the test results, the report will be optimized and adjusted to ensure it meets user requirements.

[0013] Compared with the prior art, the present invention provides a statistical method and system for BI reports, having the following beneficial effects: 1. The statistical method and system for BI reports can accurately understand the report requirements of the business department through in-depth requirements analysis, ensuring that the statistical content and display method of the report meet the actual business needs. This helps to avoid blind development and resource waste of the report, and at the same time improves the practicality of the report and user satisfaction; the data collection and integration stage can ensure the accurate and comprehensive collection of the required data from multiple data sources and perform effective integration processing, which helps to solve the data silo problem, improve the availability and consistency of data, and provide a reliable basis for subsequent data processing and analysis.

[0014] 2. The statistical method and system for BI reports can ensure that the statistical function and display effect of the report meet the design requirements through efficient report development implementation. By using advanced report development tools and technologies, the statistical and display functions of the report can be quickly and accurately realized, improving the development efficiency and quality of the report.

[0015] 3. The statistical method and system for BI reports can ensure the accuracy of the statistical results and display effect of the report through comprehensive testing, verification, and optimization. Through various testing means such as functional testing, performance testing, and compatibility testing, problems and defects existing in the report can be discovered and fixed, improving the stability and reliability of the report. At the same time, optimizing and adjusting the report according to the test results can further improve the performance and user experience of the report. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flowchart of the statistical method for the BI report of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0018] A statistical method and system for BI reports, including clear demand analysis for BI report statistics, data collection and integration for BI report statistics, data cleaning and transformation for BI report statistics, data modeling support for BI report statistics, design and presentation for BI report statistics, report development and implementation for BI report statistics, test verification and optimization for BI report statistics, and release, deployment, and online for BI report statistics. The specific steps are as follows: S1. Clearly define the specific requirements and goals of the report to form a detailed requirements document; S2. According to the requirements document, collect the required data from various data sources and perform integration processing; S3. Clean and transform the integrated data to solve data quality problems; S4. Design and implement a data model according to the report requirements and data characteristics; S5. According to the requirements document and data model, design the visual elements such as the interface layout, color scheme, and font size of the report; S6. In the selected report development tool, implement the development of the report according to the design document; S7. Conduct a comprehensive test on the developed report; S8. Deploy the optimized report to the production environment and perform configuration and debugging.

[0019] Further, the clear demand analysis for BI report statistics includes report type, display content, data range, and in-depth communication with relevant stakeholders such as report users and data providers to ensure the accuracy and comprehensiveness of demand understanding. Organize the demand analysis results into a detailed requirements document to provide clear guidance for subsequent work. Demand analysis is the starting point of BI report statistics work, aiming to clarify the report's goals, audience, data range, and display requirements. This includes in-depth communication with business departments to understand their data needs and ensure that the report can accurately reflect the business situation and provide strong support for decision-making.

[0020] Furthermore, the data collection and integration for BI report statistics include data source identification, data extraction, and data integration. The data sources include databases, data warehouses, and third-party data services. According to the requirements document, relevant data is extracted from each data source, and the extracted data is integrated to form a unified data view, and then subsequent processing is carried out; the data collection and integration stage involves extracting the required data from multiple data sources and performing integration processing. This process ensures the integrity, consistency, and accuracy of the data, laying a foundation for subsequent data cleaning and transformation.

[0021] Furthermore, the data cleaning and transformation for BI report statistics include data quality inspection, data cleaning, and data transformation, where: Data quality inspection: Check the integrity, accuracy, consistency, etc. of the data, identify and handle data errors; Data cleaning: Clean the identified data problems, including filling missing values, handling outliers, and converting data formats; Data transformation: According to the report requirements, perform necessary transformations on the data, including data aggregation and calculating new fields; Data cleaning and transformation is an essential part of BI report statistics. In this stage, problems such as missing values, outliers, and duplicate values in the data will be processed to ensure the cleanliness and accuracy of the data. At the same time, data transformation is performed according to the report requirements, such as data aggregation, splitting, and format conversion, to meet the requirements of subsequent analysis.

[0022] Furthermore, the data modeling support for BI report statistics includes model design and model implementation. First, according to the data characteristics and report requirements, a suitable data model is designed. The data model includes star models and snowflake models. Then, the designed data model is implemented in a data warehouse or data lake, and the organization and storage of the data are ensured to meet the report requirements; the data modeling stage aims to build an efficient data structure and query path to support complex report statistics requirements, which may involve the design of star models, snowflake models, etc. to improve the efficiency of data query and analysis.

[0023] Furthermore, the report design and presentation for BI report statistics design the interface layout, colors, and fonts of the report according to user requirements and aesthetic requirements, and design the interactive functions of report filtering, sorting, and drilling down, and produce a prototype of the report for users to conduct preliminary evaluation and feedback. The design and presentation stage focuses on the visual effects and user experience of the report. According to the requirements document and data characteristics, the layout, colors, fonts, etc. of the report are designed to ensure that the report is both beautiful and easy to understand. At the same time, the interactive functions of the report, such as filtering, sorting, and drilling down, are designed to improve the convenience of user use.

[0024] Furthermore, the realization of report development in BI report statistics includes report tool selection, report development, and performance optimization. Among them, for report tool selection, an appropriate report development tool is selected according to the complexity of the report and the team's technology stack. Report development is carried out in the selected tool to achieve interface design, data binding, and interactive functions. The performance of the report is optimized to ensure that the loading speed and response speed of the report meet user requirements. In the stage of realizing report development, based on the design document and data model, the report is developed using BI tools or custom development platforms. This includes data binding, interface rendering, and implementation of interactive functions.

[0025] Furthermore, the test verification and optimization of BI report statistics include function testing, performance testing, and user experience testing, which are specifically as follows: Function testing: Test each function of the report to ensure the correctness and integrity of the functions; Performance testing: Test the performance of the report under different data volumes and different user concurrency situations; User experience testing: Invite users to try out, collect feedback, and optimize and adjust the report; Test verification and optimization are key steps to ensure the quality and performance of the report. In this stage, the report will be comprehensively tested, including function testing, performance testing, compatibility testing, etc. According to the test results, the report will be optimized and adjusted to ensure that it meets user requirements.

[0026] Furthermore, the release, deployment, and going live of BI report statistics include deployment preparation, deployment implementation, on-line training, and on-line monitoring. The specific steps are as follows: Step 1: Prepare the deployment server, database, and report tool environment; Step 2: Deploy the developed report to the production environment for final configuration and debugging; Step 3: Train users on the use of the report to ensure that users can proficiently use the new report; Step 4: Continuously monitor the running status of the report and user feedback after going live, and promptly handle any problems that occur; Test verification and optimization are key steps to ensure the quality and performance of the report. In this stage, the report will be comprehensively tested, including function testing, performance testing, compatibility testing, etc. According to the test results, the report will be optimized and adjusted to ensure that it meets user requirements.

[0027] Example 1: A statistical method and system for BI reports, including the clear demand analysis of BI report statistics, the data collection and integration of BI report statistics, the data cleaning and transformation of BI report statistics, the data modeling support of BI report statistics, the design and presentation of BI report statistics, the report development and implementation of BI report statistics, the test verification and optimization of BI report statistics, and the release, deployment and online of BI report statistics. The specific steps are as follows: S1. Define the specific requirements and objectives of the report to form a detailed requirements document; S2. Collect the required data from various data sources according to the requirements document and perform integration processing; S3. Clean and transform the integrated data to solve data quality problems; S4. Design and implement a data model according to the report requirements and data characteristics; S5. Design the visual elements such as the interface layout, color scheme, and font size of the report according to the requirements document and data model; S6. Implement the development of the report in the selected report development tool according to the design document; S7. Conduct a comprehensive test on the developed report; S8. Deploy the optimized report to the production environment and perform configuration and debugging.

[0028] Embodiment 2: A statistical method and system for BI reports proposed according to Embodiment 1. The clear demand analysis of BI report statistics includes report type, display content, data range, and in-depth communication with relevant stakeholders such as report users and data providers to ensure the accuracy and comprehensiveness of demand understanding. Organize the demand analysis results into a detailed requirements document to provide clear guidance for subsequent work; Demand analysis is the starting point of BI report statistics work, aiming to clarify the report's goals, audience, data range, and display requirements, which includes in-depth communication with business departments to understand their data needs, ensuring that the report can accurately reflect the business situation and provide strong support for decision-making; The data collection and integration of BI report statistics includes data source identification, data extraction, and data integration. The data sources include databases, data warehouses, and third-party data services. According to the requirements document, extract relevant data from each data source, integrate the extracted data to form a unified data view, and then perform subsequent processing; The data collection and integration stage involves extracting the required data from multiple data sources and performing integration processing. This process ensures the integrity, consistency, and accuracy of the data, laying a foundation for subsequent data cleaning and transformation; Through in-depth requirements analysis, it is possible to accurately understand the report requirements of the business department, ensure that the statistical content and display methods of the reports meet the actual business needs, which helps to avoid blind development and resource waste of the reports, and at the same time improve the usability and user satisfaction of the reports; the data collection and integration stage can ensure the accurate and comprehensive collection of the required data from multiple data sources and perform effective integration processing, which helps to solve the data silo problem, improve the availability and consistency of the data, and provide a reliable basis for subsequent data processing and analysis.

[0029] Example Three: A statistical method and system for BI reports proposed according to Example One. The data cleaning and transformation of BI report statistics includes data quality inspection, data cleaning, and data transformation, where: Data quality inspection: Check the integrity, accuracy, consistency, etc. of the data, identify and handle data errors; Data cleaning: Clean the identified data problems, including filling missing values, handling outliers, and converting data formats; Data transformation: Perform necessary transformations on the data according to the report requirements, including data aggregation and calculating new fields; Data cleaning and transformation is an essential part of BI report statistics. In this stage, problems such as missing values, outliers, and duplicate values in the data will be processed to ensure the cleanliness and accuracy of the data. At the same time, data transformation will be performed according to the report requirements, such as data aggregation, splitting, and format conversion, to meet the requirements of subsequent analysis; The data modeling support for BI report statistics includes model design and model implementation. First, design a suitable data model according to the data characteristics and report requirements. The data model includes star model and snowflake model. Then, implement the designed data model in the data warehouse or data lake and ensure that the organization and storage of the data meet the report requirements; the data modeling stage aims to build an efficient data structure and query path to support complex report statistical requirements, which may involve the design of star model, snowflake model, etc. to improve the efficiency of data query and analysis; Data cleaning and transformation is a key step to ensure the quality of report data. By cleaning problems such as missing values, outliers, and duplicate values in the data and performing necessary data transformation, the accuracy and reliability of the data can be improved, which helps to reduce the impact of data errors on the report statistical results and improve the accuracy and credibility of the reports.

[0030] Example Four: A statistical method and system for BI reports proposed according to Embodiment 1. The report design and presentation of BI report statistics are based on user requirements and aesthetic requirements. The interface layout, color, and font of the report are designed, and the interactive functions such as report filtering, sorting, and drilling are designed. A prototype of the report is made for users to conduct preliminary evaluation and feedback. The design and presentation stage focuses on the visual effect and user experience of the report. According to the requirement document and data characteristics, the layout, color, font, etc. of the report are designed to ensure that the report is both beautiful and easy to understand. At the same time, the interactive functions of the report, such as filtering, sorting, and drilling, are designed to improve the convenience of users; The report development and implementation of BI report statistics include report tool selection, report development, and performance optimization. Among them, the report tool selection is based on the complexity of the report and the team's technology stack to select a suitable report development tool. The report is developed in the selected tool to achieve interface design, data binding, and interactive functions, and the performance of the report is optimized to ensure that the loading speed and response speed of the report meet user requirements. In the report development and implementation stage, based on the design document and data model, the report will be developed using a BI tool or a custom development platform, which includes data binding, interface rendering, and interactive function implementation; Good report design and presentation can intuitively display the relationships and trends between data, improving the readability and understandability of data. Through reasonable layout, style setting, and interactive function design, the visual experience and operation convenience of users can be enhanced, and the practicality and user satisfaction of the report can be improved; Efficient report development and implementation can ensure that the statistical functions and display effects of the report meet the design requirements. By using advanced report development tools and technologies, the statistical and display functions of the report can be quickly and accurately implemented, improving the development efficiency and quality of the report.

[0031] Embodiment 5: A statistical method and system for BI reports proposed according to Embodiment 1. The test verification and optimization of BI report statistics include function testing, performance testing, and user experience testing, as follows: Function testing: Test the various functions of the report to ensure the correctness and integrity of the functions; Performance testing: Test the performance of the report under different data volumes and different user concurrency situations; User experience testing: Invite users to conduct trials, collect feedback, and optimize and adjust the report; Test verification and optimization are key steps to ensure the quality and performance of the report. In this stage, the report will be comprehensively tested, including function testing, performance testing, compatibility testing, etc. According to the test results, the report will be optimized and adjusted to ensure that it meets user requirements; Comprehensive test verification and optimization can ensure the accuracy of the statistical results and display effects of reports. Through various testing methods such as functional testing, performance testing, and compatibility testing, problems and defects existing in the reports can be discovered and fixed, improving the stability and reliability of the reports. At the same time, optimizing and adjusting the reports according to the test results can further enhance the performance and user experience of the reports.

[0032] Embodiment Six: A statistical method and system for a BI report proposed according to Embodiment One. The release, deployment, and online launch of BI report statistics include deployment preparation, deployment implementation, online training, and online monitoring. The specific steps are as follows: Step One: Prepare the deployment server, database, and report tool environment; Step Two: Deploy the developed report to the production environment and perform final configuration and debugging; Step Three: Train users on the use of the report to ensure that users can proficiently use the new report; Step Four: Continuously monitor the running status of the report and user feedback after going online, and promptly handle any problems that occur; Test verification and optimization are key steps to ensure the quality and performance of reports. In this stage, comprehensive testing of the reports will be carried out, including functional testing, performance testing, compatibility testing, etc. According to the test results, the reports will be optimized and adjusted to ensure that they meet user requirements; Timely release, deployment, and online launch can quickly put the tested and verified reports into actual use. Through reasonable deployment and configuration, it can be ensured that the reports operate normally and stably in the production environment. At the same time, providing necessary training and guidance to users can improve users' usage ability and the utilization rate of the reports.

[0033] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A statistical method and system for BI reports, characterized in that: It includes the clear demand analysis of BI report statistics, data collection and integration of BI report statistics, data cleaning and transformation of BI report statistics, data modeling support of BI report statistics, design and presentation of BI report statistics, report development and implementation of BI report statistics, test verification and optimization of BI report statistics, and release, deployment and online of BI report statistics. The specific steps are as follows: S1. Define the specific requirements and objectives of the report to form a detailed requirements document; S2. According to the requirements document, collect the required data from various data sources and perform integration processing; S3. Clean and transform the integrated data to solve data quality problems; S4. Design and implement a data model according to the report requirements and data characteristics; S5. Design the visual elements such as the interface layout, color scheme, and font size of the report according to the requirements document and data model; S6. In the selected report development tool, implement the development of the report according to the design document; S7. Conduct a comprehensive test on the developed report; S8. Deploy the optimized report application to the production environment and perform configuration and debugging.

2. The statistical method and system for a BI report form according to claim 1, characterized in that: The clear demand analysis of the BI report statistics includes report type, display content, data range, and in-depth communication with relevant stakeholders such as report users and data providers to ensure the accuracy and comprehensiveness of demand understanding. Organize the demand analysis results into a detailed requirements document to provide clear guidance for subsequent work.

3. A statistical method and system for BI reports according to claim 1, characterized in that: The data collection and integration of the BI report statistics include data source identification, data extraction, and data integration. The data sources include databases, data warehouses, and third-party data services. According to the requirements document, extract relevant data from each data source, integrate the extracted data to form a unified data view, and then perform subsequent processing.

4. A statistical method and system for BI reports according to claim 1, characterized in that: The data cleaning and transformation of the BI report statistics include data quality inspection, data cleaning, and data transformation, where: Data quality inspection: Check the integrity, accuracy, consistency, etc. of the data, identify and process data errors; Data cleaning: Clean the identified data problems, including filling missing values, handling outliers, and converting data formats; Data transformation: Perform necessary transformations on the data according to the report requirements, including data aggregation and calculating new fields.

5. A statistical method and system for BI reports according to claim 1, characterized in that: The data modeling support of the BI report statistics includes model design and model implementation. First, design a suitable data model according to the data characteristics and report requirements, where the data model includes star model and snowflake model. Then implement the designed data model in the data warehouse or data lake and ensure that the organization and storage of the data meet the report requirements.

6. The statistical method and system of a BI report form according to claim 1, characterized in that: The report design and presentation of the BI report statistics design the interface layout, color, and font of the report according to user requirements and aesthetic requirements, and design the interactive functions of report filtering, sorting, and drilling down to produce a prototype of the report for users to conduct preliminary evaluation and feedback.

7. A statistical method and system for BI reports according to claim 1, characterized in that: The report development implementation of the BI report statistics includes report tool selection, report development, and performance optimization. Among them, the report tool is selected according to the complexity of the report and the team's technology stack, and a suitable report development tool is selected. The report is developed in the selected tool to achieve interface design, data binding, and interactive functions, and the performance of the report is optimized to ensure that the loading speed and response speed of the report meet the user's requirements.

8. A statistical method and system for BI reports according to claim 1, characterized in that: The test verification and optimization of the BI report statistics include function testing, performance testing, and user experience testing, which are specifically as follows: Function testing: Test each function of the report to ensure the correctness and integrity of the function. Performance testing: Test the performance of the report under different data volumes and different user concurrency situations. User experience testing: Invite users to try out the report, collect feedback, and optimize and adjust the report.

9. A statistical method and system for a BI report form according to claim 1, wherein: The release, deployment, and go-live of the BI report statistics include deployment preparation, deployment implementation, go-live training, and go-live monitoring. The specific steps are as follows: Step 1: Prepare the deployment server, database, and report tool environment. Step 2: Deploy the developed report to the production environment for final configuration and debugging. Step 3: Train users on how to use the report to ensure that users can use the new report proficiently. Step 4: Continuously monitor the running status of the report and user feedback after going live, and promptly handle any problems that arise.

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