E-commerce visual data management method and system based on cloud computing

Abstract

The invention relates to the technical field of e-commerce data management, in particular to an e-commerce visual data management method and system based on cloud computing. The system is in butt joint with an order system, a user system and a commodity system in an e-commerce platform, collects various e-commerce data in real time, uploads the processed e-commerce data to an AmazonS3 object storage service, dispersedly stores the data in a plurality of global data centers, establishes data partitions, and quickly processes and analyzes the stored data by means of a cloud computing platform. According to e-commerce business requirements and characteristics, a visual chart is designed, different types of data are displayed, an interactive interface is established, a user is allowed to click on the visual chart in the interactive interface through a mouse, and the data are screened, sorted and zoomed according to requirements, so that visual display and interactive analysis of the data are realized by adopting the mode, and the user experience is improved. Key information can be rapidly extracted from mass data, so that a user can visually insight laws and trends behind the data.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce data management, and in particular to a method and system for e-commerce visual data management based on cloud computing. Background Art

[0002] With the continuous development of electronic technology, people have gradually become accustomed to using e-commerce for economic consumption and management. Compared with traditional consumption methods, e-commerce companies generate massive amounts of data every day, covering multiple dimensions such as user behavior, transaction records, product information, and marketing campaign effects.

[0003] Since e-commerce companies generate massive amounts of data every day, existing e-commerce data displays usually use simple tables and reports, which lack intuitiveness and interactivity. They are unable to quickly extract key information from massive data, resulting in users being unable to intuitively understand the patterns and trends behind the data. Summary of the Invention

[0004] The purpose of the present invention is to provide a cloud computing-based e-commerce visualization data management method and system, aiming to solve the technical problem that existing e-commerce data display usually adopts simple tables and reports, lacks intuitiveness and interactivity, cannot quickly extract key information from massive data, and results in users unable to intuitively understand the laws and trends behind the data.

[0005] To achieve the above objectives, the present invention adopts a cloud computing-based e-commerce visual data management method, which includes the following steps:

[0006] Connect with the order system, user system, and product system of the e-commerce platform to collect various e-commerce data in real time;

[0007] Clean the collected e-commerce data and standardize the data in different formats and structures into a unified format;

[0008] Upload the processed e-commerce data to Amazon S3 object storage service, where the data is distributed and stored in multiple data centers around the world;

[0009] Create data partitions;

[0010] Leveraging the parallel computing capabilities of the cloud computing platform, the MapReduce framework is used to quickly process and analyze stored data;

[0011] Design visual charts to display different types of data based on e-commerce business needs and characteristics;

[0012] Create an interactive interface that allows users to click on visual charts in the interactive interface with their mouse to filter, sort, and zoom data as needed to understand the information behind the data;

[0013] Set up a data management permission system and set corresponding data access and operation permissions according to user roles and responsibilities;

[0014] Build an e-commerce data sharing platform for data sharing and collaboration.

[0015] Among them, in the steps of connecting with the order system, user system and product system in the e-commerce platform and collecting various e-commerce data in real time:

[0016] E-commerce data includes information on user browsing history, purchasing behavior, product inventory, and price changes.

[0017] Among them, in the step of cleaning the collected e-commerce data, standardizing the data in different formats and structures, and converting them into a unified format:

[0018] E-commerce data cleaning includes removing duplicate data, erroneous data, and invalid data.

[0019] Among them, in the step of establishing data partitions:

[0020] The data is divided into different partitions according to time, region and product category.

[0021] Among them, in the steps of using the parallel computing capabilities of the cloud computing platform and using the MapReduce framework to quickly process and analyze the stored data:

[0022] Analyze data in real time and respond promptly to real-time decision-making needs in e-commerce operations.

[0023] Among them, in the steps of designing visual charts to display different types of data according to e-commerce business needs:

[0024] Visualization charts include bar charts, line charts, and scatter charts.

[0025] Among them, in the steps of setting up the data management permission system and setting corresponding data access and operation permissions according to user roles and responsibilities:

[0026] Establish an identity authentication system so that users can access and operate data and authenticate their identities.

[0027] The present invention also provides a cloud computing-based e-commerce visualization data management system, which includes a data acquisition module, a data processing module, a data storage module, a data visualization module, and a management module, wherein:

[0028] The data collection module is used to collect various e-commerce data in real time;

[0029] The data processing module is used to clean and format the data;

[0030] The data storage module is used to store e-commerce data and establish data partitions;

[0031] The data visualization module is used to generate visualization charts based on e-commerce business requirements and data characteristics;

[0032] The management module is used to set data management permissions for different users and departments, and set data access and operation permissions according to the user's role and responsibilities.

[0033] The present invention discloses a method and system for e-commerce visualization data management based on cloud computing. The method first connects with the order system, user system, and product system of the e-commerce platform to collect various e-commerce data in real time. The collected e-commerce data is then cleaned and data of different formats and structures is standardized and converted into a unified format. The processed e-commerce data is then uploaded to the Amazon S3 object storage service. The data is distributed and stored in multiple data centers around the world, and data partitions are established. Subsequently, the MapReduce framework is used to quickly process and analyze the stored data, leveraging the parallel computing capabilities of the cloud computing platform. Visual charts are designed to display different types of data based on the needs and characteristics of e-commerce business. An interactive interface is established, allowing users to click on the visual charts in the interactive interface with a mouse to filter, sort, and zoom the data as needed to understand the information behind the data. A data management permission system is established, corresponding data access and operation permissions are set according to user roles and responsibilities, and an e-commerce data sharing platform is established to share and collaborate on data. The above method realizes intuitive display and interactive analysis of data, can quickly extract key information from massive data, and enables users to intuitively understand the patterns and trends behind the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 It is a flow chart of the cloud computing-based e-commerce visual data management method of the present invention.

[0036] Figure 2It is a schematic diagram of the principle of the cloud computing-based e-commerce visual data management system of the present invention.

[0037] 10-data acquisition module, 20-data processing module, 30-data storage module, 40-data visualization module, 50-management module. DETAILED DESCRIPTION

[0038] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with this application.

[0039] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0040] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0041] See also Figure 1 The present invention provides a method for managing e-commerce visual data based on cloud computing, comprising the following steps:

[0042] S100: Connects with the order system, user system, and product system of the e-commerce platform to collect various e-commerce data in real time, including user browsing history, purchasing behavior, product inventory, and price changes;

[0043] S200: Cleaning the collected e-commerce data and standardizing data of different formats and structures into a unified format. E-commerce data cleaning includes removing duplicate data, erroneous data, and invalid data.

[0044] S300: uploads processed e-commerce data to Amazon S3 object storage service, where the data is distributed across multiple data centers around the world.

[0045] S400: Establish data partitions, dividing the data into different partitions based on time, region, and product category;

[0046] S500: Leveraging the parallel computing capabilities of the cloud computing platform, the MapReduce framework is used to rapidly process and analyze stored data. This allows for real-time data analysis and timely response to real-time decision-making needs in e-commerce operations.

[0047] S600: Design visualization charts based on e-commerce business needs and characteristics to display different types of data. Visualization charts include bar charts, line charts, and scatter plots.

[0048] S700: Create an interactive interface that allows users to click on visual charts in the interactive interface with their mouse to filter, sort, and zoom data as needed to understand the information behind the data;

[0049] S800: Set up a data management authority system, assign corresponding data access and operation permissions based on user roles and responsibilities, and establish an identity authentication system so that users need to be authenticated for data access and operation;

[0050] S900: Build an e-commerce data sharing platform for data sharing and collaboration.

[0051] In this embodiment, the order system, user system and product system of the e-commerce platform are connected first, and various e-commerce data are collected in real time. The e-commerce data includes user browsing history, purchase behavior, product inventory and price change information. Then the collected e-commerce data is cleaned and the data of different formats and structures are standardized and converted into a unified format. E-commerce data cleaning includes removing duplicate data, erroneous data and invalid data. Then the processed e-commerce data is uploaded to Amazon. In the S3 object storage service, data is stored in multiple data centers around the world, and data partitions are established. Data is divided into different partitions according to time, region, and product category. Then, with the help of the parallel computing capabilities of the cloud computing platform, the MapReduce framework is used to quickly process and analyze the stored data. At the same time, data is analyzed in real time to promptly respond to real-time decision-making needs in e-commerce operations. According to the needs and characteristics of e-commerce business, visual charts are designed to display different types of data. Visual charts include bar charts, line charts, and scatter charts. An interactive interface is established to allow users to click on the visual charts in the interactive interface with their mouse, filter, sort, and zoom the data according to their needs, and understand the information behind the data. By setting up a data management permission system, corresponding data access and operation permissions are set according to the user's role and responsibilities. At the same time, an identity authentication system is established. User identity authentication is required for data access and operation, and an e-commerce data sharing platform is built for data sharing and collaboration.

[0052] See also Figure 2 The present invention also provides a cloud computing-based e-commerce visualization data management system, including a data acquisition module 10, a data processing module 20, a data storage module 30, a data visualization module 40, and a management module 50, wherein:

[0053] The data collection module 10 is used to collect various e-commerce data in real time;

[0054] The data processing module 20 is used to clean and format the data;

[0055] The data storage module 30 is used to store e-commerce data and establish data partitions;

[0056] The data visualization module 40 is used to generate visualization charts based on e-commerce business requirements and data characteristics;

[0057] The management module 50 is used to set data management permissions for different users and departments, and to set data access and operation permissions according to the roles and responsibilities of the users.

[0058] In this embodiment, the data acquisition module 10 collects various types of e-commerce data in real time, and uses the data processing module 20 to clean and convert the data. The data storage module 30 stores the e-commerce data and establishes data partitions. The data visualization module 40 is used to generate visual charts based on e-commerce business needs and data characteristics. The management module 50 sets data management permissions for different users and departments, and sets data access and operation permissions based on the user's role and responsibilities.

[0059] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the contents disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of this application and include common knowledge or customary techniques in the art that are not disclosed in this application.

[0060] It will be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A method for visual data management of e-commerce based on cloud computing, characterized in that: The steps include: Connect with the order system, user system, and product system of the e-commerce platform to collect various e-commerce data in real time; Clean the collected e-commerce data and standardize the data in different formats and structures into a unified format; Upload the processed e-commerce data to Amazon S3 object storage service, where the data is distributed and stored in multiple data centers around the world; Create data partitions; Leveraging the parallel computing capabilities of the cloud computing platform, the MapReduce framework is used to quickly process and analyze stored data; Design visual charts to display different types of data based on e-commerce business needs and characteristics; Create an interactive interface that allows users to click on visual charts in the interactive interface with their mouse to filter, sort, and zoom data as needed to understand the information behind the data; Set up a data management permission system and set corresponding data access and operation permissions according to user roles and responsibilities; Build an e-commerce data sharing platform for data sharing and collaboration.

2. The method for managing e-commerce visual data based on cloud computing according to claim 1, characterized in that: In the steps of connecting with the order system, user system, and product system in the e-commerce platform to collect various e-commerce data in real time: E-commerce data includes information on user browsing history, purchasing behavior, product inventory, and price changes.

3. The method for managing e-commerce visual data based on cloud computing according to claim 2, characterized in that: In the step of cleaning the collected e-commerce data and standardizing the data in different formats and structures and converting them into a unified format: E-commerce data cleaning includes removing duplicate data, erroneous data, and invalid data.

4. The method for managing e-commerce visual data based on cloud computing according to claim 1, wherein: In the steps of creating data partitions: The data is divided into different partitions according to time, region and product category.

5. The method for managing e-commerce visual data based on cloud computing according to claim 3, characterized in that: In the steps of using the parallel computing capabilities of the cloud computing platform and using the MapReduce framework to quickly process and analyze stored data: Analyze data in real time and respond promptly to real-time decision-making needs in e-commerce operations.

6. The method for managing e-commerce visual data based on cloud computing according to claim 1, wherein: In the steps of designing visual charts to display different types of data according to e-commerce business needs: Visualization charts include bar charts, line charts, and scatter charts.

7. The method for managing e-commerce visual data based on cloud computing according to claim 6, characterized in that: In the steps of setting up the data management permission system and setting corresponding data access and operation permissions according to user roles and responsibilities: Establish an identity authentication system so that users can access and operate data and authenticate their identities.

8. A cloud computing-based e-commerce visualization data management system, applied to the cloud computing-based e-commerce visualization data management method according to claim 1, characterized in that: It includes data acquisition module, data processing module, data storage module, data visualization module and management module, among which: The data collection module is used to collect various e-commerce data in real time; The data processing module is used to clean and format the data; The data storage module is used to store e-commerce data and establish data partitions; The data visualization module is used to generate visualization charts based on e-commerce business requirements and data characteristics; The management module is used to set data management permissions for different users and departments, and set data access and operation permissions according to the user's role and responsibilities.

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