Photovoltaic energy product sales data analysis visualization method and related device

Abstract

The invention discloses a sales data analysis visualization method of a photovoltaic energy product and a related device, and the method comprises the steps: a rear-end server builds communication connection with a user terminal, and receives a customized analysis report request sent by the user terminal; performing data acquisition processing based on a data demand in the customized analysis report request to obtain acquired data information; performing data preprocessing on the acquired data to obtain preprocessed data information; carrying out analysis processing by utilizing the processed data information based on an analysis demand in the customized analysis report request to obtain at least one data analysis result; generating a corresponding customized analysis report based on the at least one data analysis result; and performing visualization processing on the customized analysis report based on the display parameters of the user terminal, and rendering a visualization result to the user terminal for visual display. According to the embodiment of the invention, a user can know the sales analysis data of the photovoltaic energy product in time according to requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a sales data analysis visualization method and related devices for photovoltaic energy products. Background Art

[0002] When selling photovoltaic energy products on the network platform, in order to timely understand customer demand for photovoltaic energy products and market preference trends for a wide range of energy products, managers need customers to extract corresponding data information on the network platform based on the information they need, and then import the data information into the corresponding data analysis software, and update the corresponding analysis results to generate the corresponding analysis report. This will not satisfy users' need to timely understand the sales analysis data of photovoltaic energy products, and the user interaction experience is not user-friendly. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a method and related devices for visualizing the sales data analysis of photovoltaic energy products, which can enable users to timely understand the sales analysis data of photovoltaic energy products according to their needs, and provide a good user interaction experience.

[0004] In order to solve the above technical problems, an embodiment of the present invention provides a method for analyzing and visualizing sales data of photovoltaic energy products, the method comprising:

[0005] The back-end server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, wherein the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis;

[0006] The backend server calls the corresponding data acquisition interface to perform data acquisition processing based on the data requirements in the customized analysis report request to obtain the collected data information;

[0007] The back-end server performs data preprocessing on the collected data to obtain preprocessed data information;

[0008] The backend server calls the corresponding analysis model based on the analysis requirements in the customized analysis report request and uses the processed data information to perform analysis and processing to obtain at least one data analysis result;

[0009] Generate a corresponding customized analysis report using a preset report template based on at least one data analysis result;

[0010] The customized analysis report is visualized based on the display parameters of the user terminal, and the visualization result is rendered on the user terminal for visualization display.

[0011] Optionally, the back-end server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, including:

[0012] After receiving the identity authentication information input by the user on the user terminal, encoding the identity authentication information based on the Rveit encoding model to generate unique identity encoding information;

[0013] The user terminal uploads the identity code information to the back-end server, and the back-end server performs authentication processing on the identity code information based on a differential obfuscation mechanism, and establishes a communication connection with the user terminal after the authentication is passed;

[0014] The back-end server receives a customized analysis report request corresponding to photovoltaic energy product sales data sent by a user terminal based on the communication connection, and the customized analysis report request is generated by a user operating on the user terminal.

[0015] Optionally, the backend server calls a corresponding data acquisition interface to perform data acquisition processing based on the data requirements in the customized analysis report request to obtain the collected data information, including:

[0016] The back-end server parses the customized analysis report request to obtain the corresponding data information required in the customized analysis report request;

[0017] According to the corresponding data information required to be obtained in the customized analysis report request, the corresponding data acquisition interface is called to perform data acquisition processing to obtain the collected data information. The data acquisition interface is designed and generated by a RESTful API.

[0018] Optionally, the back-end server performs data preprocessing on the collected data to obtain preprocessed data information, including:

[0019] The back-end server calls a data cleaning program to clean the collected data to obtain cleaned data information, wherein the data cleaning process includes removing invalid, duplicate or incomplete data;

[0020] The cleaned data information is converted into a data format to form data information in a unified format, wherein the unified format includes date format table conversion and numerical unit unification;

[0021] The data information in a unified format is subjected to feature extraction processing using a feature extraction program to form preprocessed data information, wherein the preprocessed data information includes user activity features and purchase frequency features.

[0022] Optionally, after the back-end server performs data preprocessing on the collected data and obtains the preprocessed data information, it further includes:

[0023] The preprocessed data information data is distributedly stored based on the MondoDB database, and when performing distributed storage, an association relationship between the MondoDB database and the column-based database management system is established.

[0024] Optionally, generating a corresponding customized analysis report based on at least one data analysis result using a preset report template includes:

[0025] Filling the at least one data analysis result into the preset report template according to the rules, and automatically generating an initial PDF customized analysis report, wherein the preset report template is optimized based on a Markdown template or a LaTeX template;

[0026] Performing keyword extraction processing on the initial PDF customized analysis report based on the NLP model, and generating text summary information according to the extracted keywords;

[0027] The text summary information is combined with the initial PDF customized analysis report to generate a corresponding customized analysis report.

[0028] Optionally, the visualizing the customized analysis report based on the display parameters of the user terminal, and rendering the visualization result to the user terminal for visual display, includes:

[0029] Performing data interactive processing on the customized analysis report based on an interactive dashboard to form a customized analysis report with interactive data, wherein the interactive dashboard is developed based on ECharts and supports multi-dimensional data screening and data drill-down analysis;

[0030] The back-end server obtains the display parameters of the user terminal, uses the display parameters to visualize the interactive customized analysis report of the data based on the mobile adaptation model, and renders the visualization processing results to the user terminal for visual display using a rendering program.

[0031] In addition, an embodiment of the present invention further provides a sales data analysis and visualization device for photovoltaic energy products, the device comprising:

[0032] Request receiving module: used for the back-end server to establish a communication connection with the user terminal based on identity authentication, and receive a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, wherein the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis;

[0033] Data collection module: used for the back-end server to call the corresponding data acquisition interface to perform data collection and processing based on the data requirements in the customized analysis report request to obtain collected data information;

[0034] Data processing module: used for the back-end server to perform data preprocessing on the collected data to obtain preprocessed data information;

[0035] Data analysis module: used for the back-end server to call the corresponding analysis model based on the analysis requirements in the customized analysis report request and use the processed data information to perform analysis and processing to obtain at least one data analysis result;

[0036] Report generation module: used to generate a corresponding customized analysis report based on at least one data analysis result using a preset report template;

[0037] Visualization module: used to visualize the customized analysis report based on the display parameters of the user terminal, and render the visualization results to the user terminal for visual display.

[0038] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the sales data analysis visualization method as described in any one of the above is implemented.

[0039] In addition, an embodiment of the present invention further provides a backend server, the backend server comprising:

[0040] one or more processors;

[0041] Memory;

[0042] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to: execute the sales data analysis visualization method according to any one of the above.

[0043] In an embodiment of the present invention, a communication connection is established with a user terminal through a back-end server, and a customized analysis report request sent by the user terminal is received; data collection and processing are performed based on the data requirements in the customized analysis report request to obtain collected data information; data preprocessing is performed on the collected data to obtain preprocessed data information; analysis and processing are performed using the processed data information based on the analysis requirements in the customized analysis report request to obtain at least one data analysis result; a corresponding customized analysis report is generated based on at least one data analysis result; the customized analysis report is visualized based on the display parameters of the user terminal, and the visualization results are rendered to the user terminal for visual display; users can timely understand the sales analysis data of photovoltaic energy products according to their needs; and have a good user interaction experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 is a flow chart of a method for visualizing sales data analysis of photovoltaic energy products in an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of the structure of a device for analyzing and visualizing sales data of photovoltaic energy products in an embodiment of the present invention;

[0047] Figure 3 It is a schematic diagram of the structural composition of the back-end server in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] For example, see Figure 1 , Figure 1 It is a flow chart of a method for visualizing sales data analysis of photovoltaic energy products in an embodiment of the present invention.

[0050] like Figure 1 As shown, a method for analyzing and visualizing sales data of photovoltaic energy products, the method comprising:

[0051] S11: The backend server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, wherein the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis;

[0052] In the specific implementation process of the present invention, the back-end server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, including: after receiving the identity authentication information input by the user on the user terminal, encoding the identity authentication information based on the Rveit coding model to generate unique identity coding information; the user terminal uploads the identity coding information to the back-end server, the back-end server authenticates the identity coding information based on a differential confusion mechanism, and establishes a communication connection with the user terminal after the authentication is passed; the back-end server receives the customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal based on the communication connection, and the customized analysis report request is generated by the user operation on the user terminal.

[0053] Specifically, first, the back-end server needs to authenticate the identity information of the user operating on the user terminal, and then establish a communication connection with the user terminal according to the authentication result, so that the user can generate a corresponding customized analysis report request on the user terminal according to his own authority operation; during identity authentication, first, the identity authentication information input by the user is received through the corresponding information receiving box on the user terminal, and the identity authentication information can be a unique account information and corresponding password information; then, the identity authentication information is encoded through the Rveit encoding model built into the user terminal to form a unique identity coding information, wherein the Rveit encoding model has two layers of encoding, and its encoding rule is to encode the identity authentication information input by the user through two layers of encoding; after completing the encoding processing, the user terminal uploads the unique identity coding information obtained by encoding to the back-end server; The differential confusion mechanism is called on the device to authenticate the identity coding information, obtain the authentication result, and establish a communication connection with the user terminal when the authentication result is authentication passed; wherein the differential confusion mechanism is a differential confusion strategy constructed according to the network environment where the user terminal is located, and then the uploaded identity coding information is subjected to feature analysis and processing, and a plurality of differential confusion feature information in the identity coding information is extracted, the identity coding information is optimized into a plurality of differential confusion feature components, and the differential confusion probability corresponding to each differential confusion feature classification is calculated to form a data set of differential confusion feature components corresponding to the user's identity authentication information, and a first data set of differential confusion feature components corresponding to the user's real identity authentication feature information and a second data set of differential confusion feature components corresponding to the false identity authentication feature information are formed, and then similarity matching is performed with the first data set and the second data set of the user respectively, and the identity authentication result is obtained according to the similarity matching result.

[0054] After completing identity authentication and establishing a communication connection, the back-end server will receive a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal based on the communication connection; the customized analysis report request is generated by the user on the user terminal based on the authority he has; the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis.

[0055] S12: The backend server calls the corresponding data acquisition interface to perform data acquisition processing based on the data requirements in the customized analysis report request to obtain the collected data information;

[0056] In the specific implementation process of the present invention, the back-end server calls the corresponding data acquisition interface to perform data collection and processing based on the data requirements in the customized analysis report request to obtain collected data information, including: the back-end server parses the customized analysis report request to obtain the corresponding data information required to be obtained in the customized analysis report request; calls the corresponding data acquisition interface to perform data collection and processing according to the corresponding data information required to be obtained in the customized analysis report request to obtain the collected data information, and the data acquisition interface is designed and generated by a RESTful API.

[0057] Specifically, first the back-end server needs to parse and process the customized analysis report request to obtain the corresponding data information required in the customized analysis report request; then follow up with the teammate data information required to be obtained to call the corresponding data acquisition interface to perform data collection and processing, so as to obtain the corresponding collected data information; in this embodiment, all data acquisition interfaces are designed and generated using RESTful API, and these data acquisition interfaces are standard interfaces for processing HTTP requests, and can effectively ensure the secure transmission of data; at the same time, in order to realize the asynchronous data processing capability of the back-end server, the back-end server uses message queues to perform task processing on data processing, which can ensure the user response speed of the back-end server and the user's usage experience.

[0058] S13: the back-end server performs data preprocessing on the collected data information to obtain preprocessed data information;

[0059] In the specific implementation process of the present invention, the back-end server performs data preprocessing on the collected data information to obtain preprocessed data information, including: the back-end server calls a data cleaning program to perform cleaning processing on the collected data information to obtain cleaned data information, wherein the data cleaning processing includes removing invalid, repeated or incomplete data; the cleaned data information is converted into a data format to form data information in a unified format, wherein the unified format includes date format table conversion and numerical unit unification; the data information in the unified format is subjected to feature extraction processing using a feature extraction program to form preprocessed data information, wherein the preprocessed data information contains user activity features and purchase frequency features.

[0060] Furthermore, after the back-end server performs data preprocessing on the collected data and obtains the preprocessed data information, it also includes: performing distributed storage processing on the preprocessed data information based on the MondoDB database, and establishing an association relationship between the MondoDB database and the column-based database management system when performing distributed storage.

[0061] Specifically, after the back-end server obtains the collected data information, it is necessary to perform corresponding processing on the collected data information. In this embodiment, the back-end server first calls the built-in data cleaning program to perform cleaning processing on the collected data information, wherein the data cleaning performed by the data cleaning program mainly includes removing invalid, repeated or incomplete data, etc., so as to obtain cleaned data information; then it is necessary to perform data format conversion processing on the cleaned data information, mainly including date format table conversion and numerical unit unification, so as to obtain data information in a unified format. In this embodiment, Pandas is used to realize data format conversion; finally, it is necessary to perform feature extraction processing on the data information in the unified format using a feature extraction program to form preprocessed data information, wherein the preprocessed data information contains user activity features and purchase frequency features. In this embodiment, Scikit-learn is used to select and convert features.

[0062] After completing the preprocessing of the data, the preprocessed data information needs to be stored, and after storage, it needs to be convenient for subsequent query and analysis needs; therefore, the preprocessed data information needs to be distributed stored and processed through the MondoDB database, and the corresponding database management system needs to be introduced, and the database and the database management system need to be managed to facilitate subsequent query and data extraction during analysis; in this embodiment, the database can be a MongoDB database or a Cassandra database; the required database management system can be a ClickHouse system or a Druid system, which will support fast OLAP queries and meet subsequent real-time analysis needs.

[0063] S14: The backend server calls the corresponding analysis model based on the analysis requirements in the customized analysis report request and uses the processed data information to perform analysis and processing to obtain at least one data analysis result;

[0064] In the specific implementation process of the present invention, the analysis requirements in the customized analysis report request at least include one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis; when performing user behavior analysis, it is necessary to obtain the user's behavior information on photovoltaic energy products based on the processed data information, wherein the behavior information includes browsing, collecting, adding to shopping carts, purchasing, rating, commenting, and interacting, and assign corresponding weight values ​​based on each piece of behavior information, and use the corresponding weight values ​​to perform linear weighted processing to obtain the user's implicit feedback on the photovoltaic energy product; then, a corresponding interaction matrix is ​​constructed based on the user's implicit feedback on the photovoltaic energy product; wherein the interaction matrix is ​​based on the user's interest in the photovoltaic energy product. The corresponding operator operation is performed on the triple of values ​​(product, (user, interest value)), and a record is formed by aggregating the values ​​corresponding to the photovoltaic energy product as the key. Here, the key is the photovoltaic energy product, and the value is an iterable element object composed of all users who have scored the photovoltaic energy product and their corresponding behaviors. Then, the corresponding algorithm is used to further transform the elastically distributed data set of (product, iterable [user, interest value]) into a dictionary structure, that is, (product, {user 1: interest value 1, user 2: interest value 2...}); then the above dictionary structure is represented by a sparse vector, and finally the corresponding interaction matrix is ​​generated by the sparse vector representation, and finally the user behavior analysis is realized through the interaction matrix.

[0065] In market trend forecasting, we first need to obtain the policies and regulations, macroeconomics and incoming sales data from the pre-processed data information, and then use the rophet model to predict the future market capacity to obtain market trend forecasts.

[0066] For product preference analysis, we first need to obtain the interaction factors, preference factors, etc. between photovoltaic energy products and users in the pre-processed data information, and then use factor analysis and joint analysis to determine the key factors affecting preference. Finally, based on the key factors, we confirm the user's preference for the photovoltaic energy product.

[0067] S15: Generate a corresponding customized analysis report using a preset report template based on at least one data analysis result;

[0068] In the specific implementation process of the present invention, the corresponding customized analysis report is generated based on at least one data analysis result using a preset report template, including: filling in the at least one data analysis result into the preset report template according to the rules, and automatically generating an initial PDF customized analysis report, wherein the preset report template is optimized based on a Markdown template or a LaTeX template; performing keyword extraction processing on the initial PDF customized analysis report based on the NLP model, and generating text summary information based on the extracted keywords; merging the text summary information with the initial PDF customized analysis report to generate a corresponding customized analysis report.

[0069] Specifically, first, at least one data analysis result is filled in the corresponding report template in sequence, and then after the filling is completed, an initial PDF customized analysis report is automatically generated according to the report template, wherein the report template is generally formed by modifying and optimizing a Markdown template or a LaTeX template; then, the initial PDF report template is keyworded, and a corresponding text summary is generated according to the keyword. In this embodiment, the initial PDF customized analysis report can be subjected to keyword extraction processing through the NLP model in the natural language model. At the same time, the initial PDF analysis report also needs to be semantically extracted through the NLP model, and the corresponding semantic information is obtained. Then, the corresponding text summary information is generated according to the extracted keywords and semantic information, and finally, the text summary information is merged with the initial PDF customized analysis report to generate the corresponding customized analysis report.

[0070] S16: Visualize the customized analysis report based on the display parameters of the user terminal, and render the visualization result to the user terminal for visualization display.

[0071] In the specific implementation process of the present invention, the customized analysis report is visualized based on the display parameters of the user terminal, and the visualization results are rendered on the user terminal for visual display, including: data interaction processing of the customized analysis report based on an interactive dashboard to form a data interactive customized analysis report, the interactive dashboard is developed based on ECharts, and supports multi-dimensional data screening and data drill-down analysis; the back-end server obtains the display parameters of the user terminal, visualizes the data interactive customized analysis report using the display parameters based on a mobile adaptation model, and renders the visualization processing results on the user terminal for visual display using a rendering program.

[0072] Specifically, when performing visualization processing, data interaction processing is first required. In this embodiment, data interaction processing is performed on the customized analysis report through an interactive dashboard to form a customized analysis report with data interaction. The interactive dashboard is developed based on ECharts and supports multi-dimensional data filtering and data drill-down analysis. This can effectively facilitate subsequent users to filter, analyze and view the visualized data.

[0073] After completing the data interaction processing to form a customized analysis report of data interaction, the back-end server will send a display parameter acquisition instruction to the user terminal where the user is located, and the user terminal will feedback the corresponding display parameters to the back-end server. After the back-end server obtains the display parameters of the user terminal, the display parameters are input into the mobile adapter, which is an application program set on the back-end server. Then, the customized analysis report of data interaction is visualized according to the display parameters in the mobile adapter to obtain the corresponding visualization results. Finally, the visualization results are rendered to the user terminal through the promotion program on the back-end server for visualization display.

[0074] In an embodiment of the present invention, a communication connection is established with a user terminal through a back-end server, and a customized analysis report request sent by the user terminal is received; data collection and processing are performed based on the data requirements in the customized analysis report request to obtain collected data information; data preprocessing is performed on the collected data to obtain preprocessed data information; analysis and processing are performed using the processed data information based on the analysis requirements in the customized analysis report request to obtain at least one data analysis result; a corresponding customized analysis report is generated based on at least one data analysis result; the customized analysis report is visualized based on the display parameters of the user terminal, and the visualization results are rendered to the user terminal for visual display; users can timely understand the sales analysis data of photovoltaic energy products according to their needs; and have a good user interaction experience.

[0075] For example 2, please refer to Figure 2 , Figure 2 It is a schematic diagram of the structural composition of the sales data analysis and visualization device of the photovoltaic energy product in the embodiment of the present invention.

[0076] like Figure 2 As shown, a sales data analysis and visualization device for photovoltaic energy products, the device comprising:

[0077] Request receiving module 21: used for the back-end server to establish a communication connection with the user terminal based on identity authentication, and receive a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, wherein the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis;

[0078] In the specific implementation process of the present invention, the back-end server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, including: after receiving the identity authentication information input by the user on the user terminal, encoding the identity authentication information based on the Rveit coding model to generate unique identity coding information; the user terminal uploads the identity coding information to the back-end server, the back-end server authenticates the identity coding information based on a differential confusion mechanism, and establishes a communication connection with the user terminal after the authentication is passed; the back-end server receives the customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal based on the communication connection, and the customized analysis report request is generated by the user operation on the user terminal.

[0079] Specifically, first, the back-end server needs to authenticate the identity information of the user operating on the user terminal, and then establish a communication connection with the user terminal according to the authentication result, so that the user can generate a corresponding customized analysis report request on the user terminal according to his own authority operation; during identity authentication, first, the identity authentication information input by the user is received through the corresponding information receiving box on the user terminal, and the identity authentication information can be a unique account information and corresponding password information; then, the identity authentication information is encoded through the Rveit encoding model built into the user terminal to form a unique identity coding information, wherein the Rveit encoding model has two layers of encoding, and its encoding rule is to encode the identity authentication information input by the user through two layers of encoding; after completing the encoding processing, the user terminal uploads the unique identity coding information obtained by encoding to the back-end server; The differential confusion mechanism is called on the device to authenticate the identity coding information, obtain the authentication result, and establish a communication connection with the user terminal when the authentication result is authentication passed; wherein the differential confusion mechanism is a differential confusion strategy constructed according to the network environment where the user terminal is located, and then the uploaded identity coding information is subjected to feature analysis and processing, and a plurality of differential confusion feature information in the identity coding information is extracted, the identity coding information is optimized into a plurality of differential confusion feature components, and the differential confusion probability corresponding to each differential confusion feature classification is calculated to form a data set of differential confusion feature components corresponding to the user's identity authentication information, and a first data set of differential confusion feature components corresponding to the user's real identity authentication feature information and a second data set of differential confusion feature components corresponding to the false identity authentication feature information are formed, and then similarity matching is performed with the first data set and the second data set of the user respectively, and the identity authentication result is obtained according to the similarity matching result.

[0080] After completing identity authentication and establishing a communication connection, the back-end server will receive a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal based on the communication connection; the customized analysis report request is generated by the user on the user terminal based on the authority he has; the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis.

[0081] Data collection module 22: used for the back-end server to call the corresponding data acquisition interface to perform data collection and processing based on the data requirements in the customized analysis report request to obtain collected data information;

[0082] In the specific implementation process of the present invention, the back-end server calls the corresponding data acquisition interface to perform data collection and processing based on the data requirements in the customized analysis report request to obtain collected data information, including: the back-end server parses the customized analysis report request to obtain the corresponding data information required to be obtained in the customized analysis report request; calls the corresponding data acquisition interface to perform data collection and processing according to the corresponding data information required to be obtained in the customized analysis report request to obtain the collected data information, and the data acquisition interface is designed and generated by a RESTful API.

[0083] Specifically, first the back-end server needs to parse and process the customized analysis report request to obtain the corresponding data information required in the customized analysis report request; then follow up with the teammate data information required to be obtained to call the corresponding data acquisition interface to perform data collection and processing, so as to obtain the corresponding collected data information; in this embodiment, all data acquisition interfaces are designed and generated using RESTful API, and these data acquisition interfaces are standard interfaces for processing HTTP requests, and can effectively ensure the secure transmission of data; at the same time, in order to realize the asynchronous data processing capability of the back-end server, the back-end server uses message queues to perform task processing on data processing, which can ensure the user response speed of the back-end server and the user's usage experience.

[0084] Data processing module 23: used for the back-end server to perform data preprocessing on the collected data to obtain preprocessed data information;

[0085] In the specific implementation process of the present invention, the back-end server performs data preprocessing on the collected data information to obtain preprocessed data information, including: the back-end server calls a data cleaning program to perform cleaning processing on the collected data information to obtain cleaned data information, wherein the data cleaning processing includes removing invalid, repeated or incomplete data; the cleaned data information is converted into a data format to form data information in a unified format, wherein the unified format includes date format table conversion and numerical unit unification; the data information in the unified format is subjected to feature extraction processing using a feature extraction program to form preprocessed data information, wherein the preprocessed data information contains user activity features and purchase frequency features.

[0086] Furthermore, after the back-end server performs data preprocessing on the collected data and obtains the preprocessed data information, it also includes: performing distributed storage processing on the preprocessed data information based on the MondoDB database, and establishing an association relationship between the MondoDB database and the column-based database management system when performing distributed storage.

[0087] Specifically, after the back-end server obtains the collected data information, it is necessary to perform corresponding processing on the collected data information. In this embodiment, the back-end server first calls the built-in data cleaning program to perform cleaning processing on the collected data information, wherein the data cleaning performed by the data cleaning program mainly includes removing invalid, repeated or incomplete data, etc., so as to obtain cleaned data information; then it is necessary to perform data format conversion processing on the cleaned data information, mainly including date format table conversion and numerical unit unification, so as to obtain data information in a unified format. In this embodiment, Pandas is used to realize data format conversion; finally, it is necessary to perform feature extraction processing on the data information in the unified format using a feature extraction program to form preprocessed data information, wherein the preprocessed data information contains user activity features and purchase frequency features. In this embodiment, Scikit-learn is used to select and convert features.

[0088] After completing the preprocessing of the data, the preprocessed data information needs to be stored, and after storage, it needs to be convenient for subsequent query and analysis needs; therefore, the preprocessed data information needs to be distributed stored and processed through the MondoDB database, and the corresponding database management system needs to be introduced, and the database and the database management system need to be managed to facilitate subsequent query and data extraction during analysis; in this embodiment, the database can be a MongoDB database or a Cassandra database; the required database management system can be a ClickHouse system or a Druid system, which will support fast OLAP queries and meet subsequent real-time analysis needs.

[0089] Data analysis module 24: used for the back-end server to call the corresponding analysis model based on the analysis requirements in the customized analysis report request and use the processed data information to perform analysis and processing to obtain at least one data analysis result;

[0090] In the specific implementation process of the present invention, the analysis requirements in the customized analysis report request at least include one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis; when performing user behavior analysis, it is necessary to obtain the user's behavior information on photovoltaic energy products based on the processed data information, wherein the behavior information includes browsing, collecting, adding to shopping carts, purchasing, rating, commenting, and interacting, and assign corresponding weight values ​​based on each piece of behavior information, and use the corresponding weight values ​​to perform linear weighted processing to obtain the user's implicit feedback on the photovoltaic energy product; then, a corresponding interaction matrix is ​​constructed based on the user's implicit feedback on the photovoltaic energy product; wherein the interaction matrix is ​​based on the user's interest in the photovoltaic energy product. The corresponding operator operation is performed on the triple of values ​​(product, (user, interest value)), and a record is formed by aggregating the values ​​corresponding to the photovoltaic energy product as the key. Here, the key is the photovoltaic energy product, and the value is an iterable element object composed of all users who have scored the photovoltaic energy product and their corresponding behaviors. Then, the corresponding algorithm is used to further transform the elastically distributed data set of (product, iterable [user, interest value]) into a dictionary structure, that is, (product, {user 1: interest value 1, user 2: interest value 2...}); then the above dictionary structure is represented by a sparse vector, and finally the corresponding interaction matrix is ​​generated by the sparse vector representation, and finally the user behavior analysis is realized through the interaction matrix.

[0091] In market trend forecasting, we first need to obtain the policies and regulations, macroeconomics and incoming sales data from the pre-processed data information, and then use the rophet model to predict the future market capacity to obtain market trend forecasts.

[0092] For product preference analysis, we first need to obtain the interaction factors, preference factors, etc. between photovoltaic energy products and users in the pre-processed data information, and then use factor analysis and joint analysis to determine the key factors affecting preference. Finally, based on the key factors, we confirm the user's preference for the photovoltaic energy product.

[0093] Report generation module 25: used to generate a corresponding customized analysis report based on at least one data analysis result using a preset report template;

[0094] In the specific implementation process of the present invention, the corresponding customized analysis report is generated based on at least one data analysis result using a preset report template, including: filling in the at least one data analysis result into the preset report template according to the rules, and automatically generating an initial PDF customized analysis report, wherein the preset report template is optimized based on a Markdown template or a LaTeX template; performing keyword extraction processing on the initial PDF customized analysis report based on the NLP model, and generating text summary information based on the extracted keywords; merging the text summary information with the initial PDF customized analysis report to generate a corresponding customized analysis report.

[0095] Specifically, first, at least one data analysis result is filled in the corresponding report template in sequence, and then after the filling is completed, an initial PDF customized analysis report is automatically generated according to the report template, wherein the report template is generally formed by modifying and optimizing a Markdown template or a LaTeX template; then, the initial PDF report template is keyworded, and a corresponding text summary is generated according to the keyword. In this embodiment, the initial PDF customized analysis report can be subjected to keyword extraction processing through the NLP model in the natural language model. At the same time, the initial PDF analysis report also needs to be semantically extracted through the NLP model, and the corresponding semantic information is obtained. Then, the corresponding text summary information is generated according to the extracted keywords and semantic information, and finally, the text summary information is merged with the initial PDF customized analysis report to generate the corresponding customized analysis report.

[0096] Visualization module 26: used for visualizing the customized analysis report based on the display parameters of the user terminal, and rendering the visualization result to the user terminal for visual display.

[0097] In the specific implementation process of the present invention, the customized analysis report is visualized based on the display parameters of the user terminal, and the visualization results are rendered on the user terminal for visual display, including: data interaction processing of the customized analysis report based on an interactive dashboard to form a data interactive customized analysis report, the interactive dashboard is developed based on ECharts, and supports multi-dimensional data screening and data drill-down analysis; the back-end server obtains the display parameters of the user terminal, visualizes the data interactive customized analysis report using the display parameters based on a mobile adaptation model, and renders the visualization processing results on the user terminal for visual display using a rendering program.

[0098] Specifically, when performing visualization processing, data interaction processing is first required. In this embodiment, data interaction processing is performed on the customized analysis report through an interactive dashboard to form a customized analysis report with data interaction. The interactive dashboard is developed based on ECharts and supports multi-dimensional data filtering and data drill-down analysis. This can effectively facilitate subsequent users to filter, analyze and view the visualized data.

[0099] After completing the data interaction processing to form a customized analysis report of data interaction, the back-end server will send a display parameter acquisition instruction to the user terminal where the user is located, and the user terminal will feedback the corresponding display parameters to the back-end server. After the back-end server obtains the display parameters of the user terminal, the display parameters are input into the mobile adapter, which is an application program set on the back-end server. Then, the customized analysis report of data interaction is visualized according to the display parameters in the mobile adapter to obtain the corresponding visualization results. Finally, the visualization results are rendered to the user terminal through the promotion program on the back-end server for visualization display.

[0100] In an embodiment of the present invention, a communication connection is established with a user terminal through a back-end server, and a customized analysis report request sent by the user terminal is received; data collection and processing are performed based on the data requirements in the customized analysis report request to obtain collected data information; data preprocessing is performed on the collected data to obtain preprocessed data information; analysis and processing are performed using the processed data information based on the analysis requirements in the customized analysis report request to obtain at least one data analysis result; a corresponding customized analysis report is generated based on at least one data analysis result; the customized analysis report is visualized based on the display parameters of the user terminal, and the visualization results are rendered to the user terminal for visual display; users can timely understand the sales analysis data of photovoltaic energy products according to their needs; and have a good user interaction experience.

[0101] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the sales data analysis visualization method of any one of the above embodiments is implemented. The computer-readable storage medium includes, but is not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (EraSable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or optical card. That is, the storage device includes any medium that can store or transmit information in a readable form by a device (for example, a computer, a mobile phone), which can be a read-only memory, a disk or an optical disk, etc.

[0102] An embodiment of the present invention further provides a computer application program that runs on a computer and is used to execute the sales data analysis visualization method of any one of the above embodiments.

[0103] also, Figure 3 It is a schematic diagram of the structural composition of the back-end server in an embodiment of the present invention.

[0104] The embodiment of the present invention also provides a back-end server, such as Figure 3 The backend server includes a processor 302, a memory 303, an input unit 304, a display unit 305 and other devices. Those skilled in the art will understand that Figure 3 The back-end server structure device shown does not constitute a limitation on all devices, and may include more or fewer components than shown, or combine certain components. The memory 303 can be used to store the application 301 and each functional module, and the processor 302 runs the application 301 stored in the memory 303, thereby executing various functional applications and data processing of the device. The memory can be an internal memory or an external memory, or include both internal and external memories. The internal memory may include a read-only memory (ROM), a programmable ROM (PROM), an electrically programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, or a random access memory. The external memory may include a hard disk, a floppy disk, a ZIP disk, a U disk, a magnetic tape, etc. The memory disclosed in the present invention includes but is not limited to these types of memories. The memory disclosed in the present invention is only used as an example and not as a limitation.

[0105] The input unit 304 is used to receive the input of the signal and the keyword input by the user. The input unit 304 may include a touch panel and other input devices. The touch panel can collect the user's touch operation on or near it (such as the user's operation on or near the touch panel using any suitable object or accessory such as a finger, stylus, etc.), and drive the corresponding connection device according to a pre-set program; other input devices may include but are not limited to one or more of a physical keyboard, a function key (such as a playback control key, a switch key, etc.), a trackball, a mouse, a joystick, etc. The display unit 305 can be used to display the information input by the user or the information provided to the user and various menus of the terminal device. The display unit 305 can be in the form of a liquid crystal display, an organic light emitting diode, etc. The processor 302 is the control center of the terminal device, which uses various interfaces and lines to connect the various parts of the entire device, and executes various functions and processes data by running or executing software programs and / or modules stored in the memory 303, and calling the data stored in the memory.

[0106] As an embodiment, the back-end server includes: one or more processors 302, a memory 303, and one or more applications 301, wherein the one or more applications 301 are stored in the memory 303 and are configured to be executed by the one or more processors 302, and the one or more applications 301 are configured to execute the sales data analysis visualization method in any one of the above-mentioned embodiments.

[0107] In an embodiment of the present invention, a communication connection is established with a user terminal through a back-end server, and a customized analysis report request sent by the user terminal is received; data collection and processing are performed based on the data requirements in the customized analysis report request to obtain collected data information; data preprocessing is performed on the collected data to obtain preprocessed data information; analysis and processing are performed using the processed data information based on the analysis requirements in the customized analysis report request to obtain at least one data analysis result; a corresponding customized analysis report is generated based on at least one data analysis result; the customized analysis report is visualized based on the display parameters of the user terminal, and the visualization results are rendered to the user terminal for visual display; users can timely understand the sales analysis data of photovoltaic energy products according to their needs; and have a good user interaction experience.

[0108] In addition, the above is a detailed introduction to the sales data analysis visualization method and related devices of a photovoltaic energy product provided by an embodiment of the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for analyzing and visualizing sales data of photovoltaic energy products, characterized in that: The method comprises: The back-end server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, wherein the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis; The backend server calls the corresponding data acquisition interface to perform data acquisition processing based on the data requirements in the customized analysis report request to obtain the collected data information; The back-end server performs data preprocessing on the collected data information to obtain preprocessed data information; The backend server calls the corresponding analysis model based on the analysis requirements in the customized analysis report request and uses the processed data information to perform analysis and processing to obtain at least one data analysis result; Generate a corresponding customized analysis report using a preset report template based on at least one data analysis result; The customized analysis report is visualized based on the display parameters of the user terminal, and the visualization result is rendered on the user terminal for visualization display.

2. The sales data analysis visualization method according to claim 1, characterized in that: The back-end server establishes a communication connection with the user terminal based on identity authentication, and receives a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, including: After receiving the identity authentication information input by the user on the user terminal, encoding the identity authentication information based on the Rveit encoding model to generate unique identity encoding information; The user terminal uploads the identity code information to the back-end server, and the back-end server performs authentication processing on the identity code information based on a differential obfuscation mechanism, and establishes a communication connection with the user terminal after the authentication is passed; The back-end server receives a customized analysis report request corresponding to photovoltaic energy product sales data sent by a user terminal based on the communication connection, and the customized analysis report request is generated by a user operating on the user terminal.

3. The sales data analysis visualization method according to claim 1, characterized in that: The backend server calls the corresponding data acquisition interface to perform data acquisition processing based on the data requirements in the customized analysis report request to obtain the collected data information, including: The back-end server parses the customized analysis report request to obtain the corresponding data information required in the customized analysis report request; According to the corresponding data information required to be obtained in the customized analysis report request, the corresponding data acquisition interface is called to perform data collection and processing to obtain the collected data information. The data acquisition interface is designed and generated by RESTful API.

4. The sales data analysis visualization method according to claim 1, characterized in that: The back-end server performs data preprocessing on the collected data information to obtain preprocessed data information, including: The back-end server calls a data cleaning program to clean the collected data information to obtain cleaned data information, wherein the data cleaning process includes removing invalid, duplicate or incomplete data; The cleaned data information is converted into a data format to form data information in a unified format, wherein the unified format includes date format table conversion and numerical unit unification; The data information in a unified format is subjected to feature extraction processing using a feature extraction program to form preprocessed data information, wherein the preprocessed data information includes user activity features and purchase frequency features.

5. The sales data analysis visualization method according to claim 1, characterized in that: After the back-end server performs data preprocessing on the collected data and obtains the preprocessed data information, it also includes: The preprocessed data information is distributedly stored based on the MondoDB database, and when performing distributed storage, an association relationship between the MondoDB database and the column-based database management system is established.

6. The sales data analysis visualization method according to claim 1, characterized in that: The generating a corresponding customized analysis report based on at least one data analysis result using a preset report template includes: Filling the at least one data analysis result into the preset report template according to the rules, and automatically generating an initial PDF customized analysis report, wherein the preset report template is optimized based on a Markdown template or a LaTeX template; Performing keyword extraction processing on the initial PDF customized analysis report based on the NLP model, and generating text summary information according to the extracted keywords; The text summary information is combined with the initial PDF customized analysis report to generate a corresponding customized analysis report.

7. The sales data analysis visualization method according to claim 1, characterized in that: The visualizing the customized analysis report based on the display parameters of the user terminal, and rendering the visualization result to the user terminal for visual display, includes: Performing data interactive processing on the customized analysis report based on an interactive dashboard to form a customized analysis report with interactive data, wherein the interactive dashboard is developed based on ECharts and supports multi-dimensional data screening and data drill-down analysis; The back-end server obtains the display parameters of the user terminal, uses the display parameters to visualize the interactive customized analysis report of the data based on the mobile adaptation model, and renders the visualization processing results to the user terminal for visual display using a rendering program.

8. A sales data analysis and visualization device for photovoltaic energy products, characterized in that: The device comprises: Request receiving module: used for the back-end server to establish a communication connection with the user terminal based on identity authentication, and receive a customized analysis report request corresponding to the photovoltaic energy product sales data sent by the user terminal, wherein the customized analysis report request includes one or more of customer behavior analysis, market trend forecast analysis, and product preference analysis; Data collection module: used for the back-end server to call the corresponding data acquisition interface to perform data collection and processing based on the data requirements in the customized analysis report request to obtain collected data information; Data processing module: used for the back-end server to perform data preprocessing on the collected data information to obtain preprocessed data information; Data analysis module: used for the back-end server to call the corresponding analysis model based on the analysis requirements in the customized analysis report request and use the processed data information to perform analysis and processing to obtain at least one data analysis result; Report generation module: used to generate a corresponding customized analysis report based on at least one data analysis result using a preset report template; Visualization module: used to visualize the customized analysis report based on the display parameters of the user terminal, and render the visualization results to the user terminal for visual display.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the sales data analysis and visualization method as described in any one of claims 1 to 7 is implemented.

10. A backend server, characterized in that: The back-end server comprises: one or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to: execute the sales data analysis visualization method according to any one of claims 1 to 7.

Images