CN112381621A - Big data collaborative supervision platform and method - Google Patents
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Abstract
The invention discloses a big data collaborative supervision platform and a big data collaborative supervision method. The commodity recommending module recommends commodities with higher priority to the customer, commodity sales trend analysis is carried out through the trend analysis module according to the commodity sales condition, and the analysis data is uploaded to the merchant login module and the manufacturer login module, so that merchants and manufacturers can conveniently cope with the commodity sales trend analysis, the commodity sales monitoring information is shared to logistics companies, manufacturers and merchants in the whole course, commodity sales, production and logistics scheduling are conveniently and reasonably arranged, and the efficiency is improved.
Description
Technical Field
The invention relates to the technical field of supervision platforms, in particular to a big data collaborative supervision platform and a big data collaborative supervision method.
Background
Big data, an IT industry term, refers to a data set that cannot be captured, managed, and processed with a conventional software tool within a certain time range, and is a massive, high-growth-rate, and diversified information asset that needs a new processing mode to have stronger decision-making power, insight discovery power, and process optimization capability.
With the rise of the internet, the online shopping of customers becomes a trend, but the customers of commodities with the same attribute experience differently, so that the sales volumes of the commodities with the same attribute and different products are different, in order to know the commodity sales degree, data dependence is timely provided for manufacturers, merchants and logistics companies, the manufacturers, the merchants and the logistics companies are convenient to deal with in time, a big data collaborative supervision platform is urgently needed to supervise the whole process, and the circulation sales efficiency of hot commodities is improved. Therefore, a big data collaborative supervision platform and a method are provided.
Disclosure of Invention
The invention aims to provide a big data collaborative supervision platform and a big data collaborative supervision method, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a big data collaborative supervision platform comprises a data acquisition module, a data statistics module, a big data analysis module, a commodity classification module, a data sharing module, a logistics management center, an early warning module, a commodity satisfaction degree grade division module, a commodity recommendation module, a trend analysis module, a manufacturer login module, an area division module, a merchant login module and an area grade setting module;
the data acquisition module is used for acquiring the commodity browsing record information, the commodity evaluation information, the logistics distribution information, the positioning information and the commodity information purchased by the customer;
the data statistics module is used for carrying out statistics on the data acquired by the data acquisition module so as to obtain data of different commodity information, purchase quantity in different areas, after-sale evaluation and time required by logistics delivery;
the big data analysis module is used for analyzing the customer requirements through big data, analyzing according to the commodity attribute browsed by the customer in a month, and acquiring commodity information with similar attribute through the big data when the ratio of the commodity quantity with the same attribute browsed by the customer to the total browsed quantity in the month exceeds 40% and uploading the similar commodity information to the commodity classification module;
the commodity classification module is used for classifying the commodity attributes and classifying the commodities into different primary and secondary categories according to the attributes;
the data sharing module is used for sharing data;
the logistics management center is used for managing logistics distribution;
the early warning module is used for early warning a busy logistics area and prompting the reasonable distribution of logistics resources;
the commodity satisfaction degree grading module is used for grading and prioritizing the purchased satisfaction degree of the commodity;
the commodity recommending module is used for recommending and displaying the high-quality commodities to merchants and customers according to the commodity satisfaction degree grade acquired by the commodity satisfaction degree grading module;
the trend analysis module is used for analyzing according to the commodity purchasing trend recommended by the commodity recommendation module, analyzing the probability variation trend of selecting purchase after the recommended commodities are browsed by the customer in a plurality of continuous unit time, and judging whether the recommended commodities are in an ascending trend or a descending trend;
the factory login module is used for a client to log in and acquire data information;
the region dividing module is used for dividing different geographic regions;
the merchant login module is used for logging in merchants to acquire data information;
the region grade setting module is used for carrying out the setting of the geographical region grade according to the ratio of the purchase times of different commodities in different geographical regions in the thirty days to the total sale amount of the commodities in the thirty days and in the order from large to small according to the sizes of the commodities in different geographical regions.
Preferably, the data acquisition module is connected with the data statistics module, the data statistics module is connected with the big data analysis module, the big data analysis module is connected with the commodity classification module, the commodity classification module is respectively connected with the data sharing module and the commodity satisfaction grading module, the commodity satisfaction grading module is connected with the commodity recommendation module, the commodity recommendation module is connected with the trend analysis module, the trend analysis module is respectively connected with the factory login module and the merchant login module, the data sharing module is respectively connected with the factory login module and the logistics management center, and the logistics management center is connected with the early warning module.
Preferably, the area division module is connected with an area grade setting module, and the area grade setting module is connected with the big data analysis module.
Preferably, the data statistics module is connected with a data storage module, and the data storage module is connected with a data maintenance module and an information security management module;
the data storage module is used for storing data;
the data maintenance module is used for maintaining data;
and the information security management module is used for managing data security.
Preferably, the big data analysis module is connected with a safety monitoring module, the safety monitoring module is connected with an alarm module, and the alarm module is connected with a control center;
the safety monitoring module is used for monitoring whether the purchase quantity of the dangerous goods in the single area reaches a set dangerous value;
the alarm module is used for alarming according to the danger data monitored by the safety monitoring module;
and the control center is used for responding the alarm information of the alarm module and carrying out tracking processing.
Preferably, the trend analysis module is connected with a market price acquisition module;
and the market price acquisition module is used for acquiring the market price of the commodity.
Preferably, the merchant login module is connected with a commodity replenishment reminding module, the commodity replenishment reminding module is connected with a commodity inventory information acquisition module, and the commodity inventory information acquisition module is connected with a commodity warehouse position information acquisition module;
the commodity warehouse position information acquisition module is used for acquiring commodity warehouse position information;
the commodity inventory information acquisition module is used for acquiring warehouse inventory information;
and the commodity replenishment reminding module is used for reminding a merchant of commodity replenishment when the commodity data acquired by the commodity inventory information acquisition module is lower than a set value.
Preferably, the data acquisition module comprises a customer information acquisition unit, a commodity evaluation information acquisition unit, a logistics information acquisition unit, a commodity receiving place information acquisition unit and a commodity information collection unit;
the customer information acquisition unit is used for acquiring the browsing record information of the customer and the information of the commodity purchased in the current period;
the commodity evaluation information acquisition unit is used for acquiring commodity evaluation information;
the logistics information acquisition unit is used for acquiring commodity distribution information;
the commodity receiving place information acquisition unit is used for acquiring commodity receiving place information;
the commodity information collection unit is used for collecting commodity attribute information.
In addition, the invention also provides a method for the big data collaborative supervision platform to carry out the big data collaborative supervision, and the big data collaborative supervision method comprises the following steps:
s1, acquiring the commodity browsing information and the commodity purchasing information, the commodity evaluation information, the logistics information, the commodity receiving place position information and the commodity information of the client through a data acquisition module, carrying out data classification and summary statistics through a data statistics module, and analyzing the data counted by the data statistics module through a big data analysis module;
s2, dividing different areas through an area dividing module, and setting the level priority of different geographical areas through an area level setting module;
s3, analyzing the commodity sales volume of the geographical area divided by the area dividing module through the big data analysis module and setting the priority of different commodities sold in different geographical areas through the area grade setting module;
s4, classifying attributes of different commodities through a commodity classification module and uploading the attributes to a data sharing module, sharing commodity information to a logistics management center, a merchant and a manufacturer through a logistics management center, a merchant login module and a manufacturer login module through the data sharing module, and pre-warning the logistics company through a pre-warning module by the logistics management center according to the commodity scheduling information of the area so as to conveniently and reasonably distribute logistics resources;
s5, the commodity satisfaction degree grading module is used for conducting priority grading on different product satisfaction degrees, commodities with higher priority levels are recommended to customers through the commodity recommending module, commodity sales trend analysis is conducted through the trend analyzing module according to the commodity sales conditions, analysis data are uploaded to the merchant login module and the manufacturer login module, and merchants and manufacturers can conveniently respond to the analysis data in time.
Preferably, the data acquisition module acquires client browsing record information and commodity evaluation information acquired by commodity information acquisition unit, the commodity evaluation information acquisition unit acquires commodity evaluation information, the logistics information acquisition unit acquires material distribution information, the commodity receiving place information acquisition unit acquires commodity receiving place information and the commodity attribute information acquisition unit acquires commodity attribute information, the data statistics module uploads data to the data storage module for storage and maintains and manages the data through the data maintenance module and the information security management module, the big data analysis module monitors whether the purchase quantity of a single area of a dangerous article reaches a set dangerous value through the security monitoring module, the big data analysis module alarms through the alarm module when the dangerous value is reached, the big data analysis module processes according to alarm information, and the trend analysis module acquires real-time commodity price information through the market price acquisition module, the merchant login module acquires commodity warehouse position information through the commodity warehouse position information acquisition module, acquires inventory information through the commodity inventory information acquisition module, and reminds the merchant of replenishment through the commodity replenishment reminding module.
Compared with the prior art, the invention has the beneficial effects that:
the different areas are divided by an area dividing module, and the level priority of the different areas is set by an area level setting module; analyzing the commodity sales volume of the areas divided by the area dividing module through a big data analysis module and setting the priorities of commodities sold in different areas through an area grade setting module; the commodity classification module is used for classifying attributes of different commodities and uploading the attributes to the data sharing module, the data sharing module is used for sharing commodity information to the logistics management center, the merchants and manufacturers through the logistics management center, the merchant login module and the manufacturer login module, and the logistics management center performs early warning on logistics companies through the early warning module according to the regional commodity scheduling information, so that logistics resources can be reasonably distributed conveniently; the commodity satisfaction degree grading module is used for conducting priority grading on different product satisfaction degrees, commodities with higher priorities are recommended to customers through the commodity recommending module, commodity sales trend analysis is conducted through the trend analyzing module according to commodity sales conditions, analysis data are uploaded to the merchant login module and the manufacturer login module, merchants and manufacturers can conveniently deal with the commodity satisfaction degree grading module in time, commodity sales monitoring information is shared to logistics companies, the manufacturers and the manufacturers in the whole process of commodity sales, commodity sales and production and logistics scheduling can be conveniently and reasonably arranged, and efficiency is improved.
Drawings
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a schematic diagram of a data acquisition module according to the present invention;
FIG. 3 is a schematic diagram of a connection relationship structure of a data statistics module according to the present invention;
FIG. 4 is a schematic diagram of a merchant login module connection structure according to the present invention;
fig. 5 is a schematic diagram of a connection relationship structure of a big data analysis module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides a technical solution:
as shown in fig. 1-5, a big data collaborative supervision platform includes a data acquisition module, a data statistics module, a big data analysis module, a commodity classification module, a data sharing module, a logistics management center, an early warning module, a commodity satisfaction grade division module, a commodity recommendation module, a trend analysis module, a factory login module, an area division module, a merchant login module, and an area grade setting module;
the data acquisition module is used for acquiring the commodity browsing record information, the commodity evaluation information, the logistics distribution information, the positioning information and the commodity information purchased by the customer;
the data statistics module is used for carrying out statistics on the data acquired by the data acquisition module to obtain different commodity information and data of purchase quantity, after-sale evaluation and time required by logistics delivery in different areas, the commodity purchase address is acquired through the commodity receiving place information acquisition unit, the commodity name and attribute classification is acquired through the commodity information acquisition unit, the total quantity of commodities sold in the area and the average value of logistics time are counted through the logistics information acquisition unit, the commodity quality evaluation quantity is acquired through the commodity evaluation information acquisition unit, and the commodity purchase quantity, after-sale evaluation and time required by logistics delivery are counted through the data statistics module;
the big data analysis module is used for analyzing the customer requirements through big data, analyzing according to the commodity attribute browsed by the customer in a month, and acquiring commodity information with similar attribute through the big data when the ratio of the commodity quantity with the same attribute browsed by the customer to the total browsed quantity in the month exceeds 40% and uploading the similar commodity information to the commodity classification module;
the commodity classification module is used for classifying the commodity attributes and classifying the commodities into different primary and secondary categories according to the attributes;
the data sharing module is used for sharing data;
the logistics management center is used for managing logistics distribution;
the early warning module is used for early warning a busy logistics area and prompting the reasonable distribution of logistics resources;
the commodity satisfaction degree grading module is used for grading and prioritizing the purchased satisfaction degree of the commodity;
the commodity recommending module is used for recommending and displaying the high-quality commodities to merchants and customers according to the commodity satisfaction degree grade acquired by the commodity satisfaction degree grading module;
the trend analysis module is used for analyzing according to the commodity purchasing trend recommended by the commodity recommendation module, analyzing the probability variation trend of selecting purchase after the recommended commodities are browsed by the customer in a plurality of continuous unit time, and judging whether the recommended commodities are in an ascending trend or a descending trend;
the factory login module is used for a client to log in and acquire data information;
the region dividing module is used for dividing different geographic regions;
the merchant login module is used for logging in merchants to acquire data information;
the region grade setting module is used for carrying out the setting of the geographical region grade according to the ratio of the purchase times of different commodities in different geographical regions in the thirty days to the total sale amount of the commodities in the thirty days and in the order from large to small according to the sizes of the commodities in different geographical regions.
Specifically, the data acquisition module is connected with the data statistics module, the data statistics module is connected with the big data analysis module, the big data analysis module is connected with the commodity classification module, the commodity classification module is connected with the data sharing module and the commodity satisfaction grading module respectively, the commodity satisfaction grading module is connected with the commodity recommendation module, the commodity recommendation module is connected with the trend analysis module, the trend analysis module is connected with the factory login module and the merchant login module respectively, the data sharing module is connected with the factory login module and the logistics management center respectively, and the logistics management center is connected with the early warning module.
Specifically, the area division module is connected with an area grade setting module, and the area grade setting module is connected with the big data analysis module.
Specifically, the data statistics module is connected with a data storage module, and the data storage module is connected with a data maintenance module and an information security management module;
the data storage module is used for storing data;
the data maintenance module is used for maintaining data;
and the information security management module is used for managing data security.
Specifically, the big data analysis module is connected with a safety monitoring module, the safety monitoring module is connected with an alarm module, and the alarm module is connected with a control center;
the safety monitoring module is used for monitoring whether the purchase quantity of the dangerous goods in the single area reaches a set dangerous value;
the alarm module is used for alarming the dangerous data monitored by the safety monitoring module;
and the control center is used for responding the alarm information of the alarm module and carrying out tracking processing.
Specifically, the trend analysis module is connected with a market price acquisition module;
and the market price acquisition module is used for acquiring the market price of the commodity.
Specifically, the merchant login module is connected with a commodity replenishment reminding module, the commodity replenishment reminding module is connected with a commodity inventory information acquisition module, and the commodity inventory information acquisition module is connected with a commodity warehouse position information acquisition module;
the commodity warehouse position information acquisition module is used for acquiring commodity warehouse position information;
the commodity inventory information acquisition module is used for acquiring warehouse inventory information;
and the commodity replenishment reminding module is used for reminding a merchant of commodity replenishment when the commodity data acquired by the commodity inventory information acquisition module is lower than a set value.
Specifically, the data acquisition module comprises a customer information acquisition unit, a commodity evaluation information acquisition unit, a logistics information acquisition unit, a commodity receiving place information acquisition unit and a commodity information collection unit;
the customer information acquisition unit is used for acquiring the browsing record information of the customer and the information of the commodity purchased in the current period;
the commodity evaluation information acquisition unit is used for acquiring commodity evaluation information;
the logistics information acquisition unit is used for acquiring commodity distribution information;
the commodity receiving place information acquisition unit is used for acquiring commodity receiving place information;
the commodity information collection unit is used for collecting commodity attribute information.
In addition, the invention also provides a method for the big data collaborative supervision platform to carry out the big data collaborative supervision, and the big data collaborative supervision method comprises the following steps:
s1, acquiring the commodity browsing information and the commodity purchasing information, the commodity evaluation information, the logistics information, the commodity receiving place position information and the commodity information of the client through a data acquisition module, carrying out data classification and summary statistics through a data statistics module, and analyzing the data counted by the data statistics module through a big data analysis module;
s2, dividing different areas through an area dividing module, and setting the level priority of different geographical areas through an area level setting module; the method is used for setting the priority according to the ratio of the purchase times of different commodities in different geographical areas in the last thirty days to the total sale amount of the commodities in the thirty days, and carrying out the geographical area grade from large to small according to the ratio of the commodities in different geographical areas.
S3, analyzing the commodity sales volume of the geographical area divided by the area dividing module through the big data analysis module and setting the priority of different commodities sold in different geographical areas through the area grade setting module; according to the ratio of the sales frequency of different commodities in different geographic areas in the thirty-day period to the total sales volume of the commodities in the thirty-day period, setting priorities according to the ratio of the commodities with the same attribute in the geographic areas in different commodity grades with the same attribute in the descending order.
S4, classifying attributes of different commodities through a commodity classification module and uploading the attributes to a data sharing module, sharing commodity information to a logistics management center, a merchant and a manufacturer through a logistics management center, a merchant login module and a manufacturer login module through the data sharing module, and pre-warning the logistics company through a pre-warning module by the logistics management center according to the commodity scheduling information of the area so as to conveniently and reasonably distribute logistics resources;
s5, the commodity satisfaction degree grading module is used for conducting priority grading on different product satisfaction degrees, commodities with higher priority levels are recommended to customers through the commodity recommending module, commodity sales trend analysis is conducted through the trend analyzing module according to the commodity sales conditions, analysis data are uploaded to the merchant login module and the manufacturer login module, and merchants and manufacturers can conveniently respond to the analysis data in time.
The data acquisition module acquires client browsing record information and current commodity purchasing information through a client information acquisition unit to acquire commodity evaluation information, the commodity evaluation information acquisition unit acquires commodity evaluation information, the logistics information acquisition unit acquires material distribution information, the commodity receiving place information acquisition unit acquires commodity receiving place information and the commodity attribute information acquisition unit acquires commodity attribute information, the data statistics module uploads data to a data storage module to be stored, and the data is maintained and safely managed through a data maintenance module and an information safety management module, the big data analysis module monitors whether the purchase quantity of a single dangerous article area reaches a set dangerous value through a safety monitoring module, alarms when the dangerous value is reached, the big data analysis module processes according to alarm information through an alarm module, and the trend analysis module acquires real-time commodity price information through a market price acquisition module, the merchant login module acquires commodity warehouse position information through the commodity warehouse position information acquisition module, acquires inventory information through the commodity inventory information acquisition module, and reminds the merchant of replenishment through the commodity replenishment reminding module.
Examples
When a customer needs to buy sweater, acquiring age, weight and sex information of the customer, current goods receiving address information of the customer, position information of a goods receiving address area, logistics distribution time information of the goods receiving address area and online shopping browsing footprint information of the customer within the last thirty days by a data acquisition module, counting the sweater purchase quantity, after-sale evaluation and time required by logistics delivery in a geographic area by a data counting module, analyzing by acquiring sweater footprint information browsed by the customer within the last month by a big data analysis module, acquiring sweater information with similar attributes by big data when the ratio of the sweater quantity browsed by the customer to the total browsed quantity exceeds 40% within the month, classifying the sweater with similar attributes into two categories of winter sweater and spring and autumn sweater by a commodity classification module, classifying into different subclasses according to different sweater styles, the sweater information with the same attribute is shared to a manufacturer, a logistics company and a merchant through a data sharing module, an early warning module reminds the logistics company that sweater orders with larger quantity are likely to be generated through sweater browsing amount information in the area, logistics resources are conveniently and reasonably deployed in advance, evaluation of different sweaters is divided into three levels of superior and inferior through a commodity satisfaction degree grade dividing module, then the sweater with high quality evaluation is recommended to a client through a commodity recommending module, the trend analysis module analyzes the trend according to the probability that the sweater recommended every day is browsed by the client in ten consecutive days and then selects to purchase, judges whether the sweater is in an upward trend or a downward trend, and the manufacturer and the merchant can reasonably arrange production and sell the sweater according to the recommended sweater change trend.
In conclusion, different areas are divided by the area dividing module, and the level priority of the different areas is set by the area level setting module; analyzing the commodity sales volume of the areas divided by the area dividing module through a big data analysis module and setting the priorities of commodities sold in different areas through an area grade setting module; the commodity classification module is used for classifying attributes of different commodities and uploading the attributes to the data sharing module, the data sharing module is used for sharing commodity information to the logistics management center, the merchants and manufacturers through the logistics management center, the merchant login module and the manufacturer login module, and the logistics management center performs early warning on logistics companies through the early warning module according to the regional commodity scheduling information, so that logistics resources can be reasonably distributed conveniently; the commodity satisfaction degree grading module is used for conducting priority grading on different product satisfaction degrees, commodities with higher priorities are recommended to customers through the commodity recommending module, commodity sales trend analysis is conducted through the trend analyzing module according to the commodity sales conditions, the analysis data are uploaded to the merchant login module and the manufacturer login module, merchants and manufacturers can conveniently deal with the commodity sales trend analysis in time, the commodity sales monitoring information is shared to logistics companies, the manufacturers and the manufacturers in the whole process, and commodity sales, production and logistics scheduling are conveniently and reasonably arranged.
The parts not involved in the present invention are the same as or can be implemented by the prior art. Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A big data collaborative supervision platform is characterized by comprising a data acquisition module, a data statistics module, a big data analysis module, a commodity classification module, a data sharing module, a logistics management center, an early warning module, a commodity satisfaction degree grading module, a commodity recommendation module, a trend analysis module, a factory login module, an area grading module, a merchant login module and an area grade setting module;
the data acquisition module is used for acquiring the commodity browsing record information, the commodity evaluation information, the logistics distribution information, the positioning information and the commodity information purchased by the customer;
the data statistics module is used for carrying out statistics on the data acquired by the data acquisition module so as to obtain data of different commodity information, purchase quantity in different areas, after-sale evaluation and time required by logistics delivery;
the big data analysis module is used for analyzing the customer requirements through big data, analyzing according to the commodity attribute browsed by the customer in a month, and acquiring commodity information with similar attribute through the big data when the ratio of the commodity quantity with the same attribute browsed by the customer to the total browsed quantity in the month exceeds 40% and uploading the similar commodity information to the commodity classification module;
the commodity classification module is used for classifying the commodity attributes and classifying the commodities into different primary and secondary categories according to the attributes;
the data sharing module is used for sharing data;
the logistics management center is used for managing logistics distribution;
the early warning module is used for early warning a busy logistics area and prompting the reasonable distribution of logistics resources;
the commodity satisfaction degree grading module is used for grading and prioritizing the purchased satisfaction degree of the commodity;
the commodity recommending module is used for recommending and displaying the high-quality commodities to merchants and customers according to the commodity satisfaction degree grade acquired by the commodity satisfaction degree grading module;
the trend analysis module is used for analyzing according to the commodity purchasing trend recommended by the commodity recommendation module, analyzing the probability variation trend of selecting purchase after the recommended commodities are browsed by the customer in a plurality of continuous unit time, and judging whether the recommended commodities are in an ascending trend or a descending trend;
the factory login module is used for a client to log in and acquire data information;
the region dividing module is used for dividing different geographic regions;
the merchant login module is used for logging in merchants to acquire data information;
the region grade setting module is used for carrying out the setting of the geographical region grade according to the ratio of the purchase times of different commodities in different geographical regions in the thirty days to the total sale amount of the commodities in the thirty days and in the order from large to small according to the sizes of the commodities in different geographical regions.
2. The big data collaborative supervision platform according to claim 1, wherein: the data acquisition module is connected with the data statistics module, the data statistics module is connected with the big data analysis module, the big data analysis module is connected with the commodity classification module, the commodity classification module is respectively connected with the data sharing module and the commodity satisfaction grading module, the commodity satisfaction grading module is connected with the commodity recommendation module, the commodity recommendation module is connected with the trend analysis module, the trend analysis module is respectively connected with the factory login module and the merchant login module, the data sharing module is respectively connected with the factory login module and the logistics management center, and the logistics management center is connected with the early warning module.
3. The big data collaborative supervision platform according to claim 1, wherein: the area division module is connected with an area grade setting module, and the area grade setting module is connected with a big data analysis module.
4. The big data collaborative supervision platform according to claim 1, wherein: the data statistics module is connected with a data storage module, and the data storage module is connected with a data maintenance module and an information security management module;
the data storage module is used for storing data;
the data maintenance module is used for maintaining data;
and the information security management module is used for managing data security.
5. The big data collaborative supervision platform according to claim 1, wherein: the big data analysis module is connected with a safety monitoring module, the safety monitoring module is connected with an alarm module, and the alarm module is connected with a control center;
the safety monitoring module is used for monitoring whether the purchase quantity of the dangerous goods in the single area reaches a set dangerous value;
the alarm module is used for alarming according to the danger data monitored by the safety monitoring module;
and the control center is used for responding the alarm information of the alarm module and carrying out tracking processing.
6. The big data collaborative supervision platform according to claim 1, wherein: the trend analysis module is connected with a market price acquisition module;
and the market price acquisition module is used for acquiring the market price of the commodity.
7. The big data collaborative supervision platform according to claim 1, wherein: the merchant login module is connected with a commodity replenishment reminding module, the commodity replenishment reminding module is connected with a commodity inventory information acquisition module, and the commodity inventory information acquisition module is connected with a commodity warehouse position information acquisition module;
the commodity warehouse position information acquisition module is used for acquiring commodity warehouse position information;
the commodity inventory information acquisition module is used for acquiring warehouse inventory information;
and the commodity replenishment reminding module is used for reminding a merchant of commodity replenishment when the commodity data acquired by the commodity inventory information acquisition module is lower than a set value.
8. The big data collaborative supervision platform according to claim 1, wherein: the data acquisition module comprises a customer information acquisition unit, a commodity evaluation information acquisition unit, a logistics information acquisition unit, a commodity receiving place information acquisition unit and a commodity information collection unit;
the customer information acquisition unit is used for acquiring the browsing record information of the customer and the information of the commodity purchased in the current period;
the commodity evaluation information acquisition unit is used for acquiring commodity evaluation information;
the logistics information acquisition unit is used for acquiring commodity distribution information;
the commodity receiving place information acquisition unit is used for acquiring commodity receiving place information;
the commodity information collection unit is used for collecting commodity attribute information.
9. A method for big data collaborative supervision by using a big data collaborative supervision platform according to any claim 1-8, wherein the big data collaborative supervision method comprises the following steps:
s1, acquiring the commodity browsing information and the commodity purchasing information, the commodity evaluation information, the logistics information, the commodity receiving place position information and the commodity information of the client through a data acquisition module, carrying out data classification and summary statistics through a data statistics module, and analyzing the data counted by the data statistics module through a big data analysis module;
s2, dividing different areas through an area dividing module, and setting the level priority of different geographical areas through an area level setting module;
s3, analyzing the commodity sales volume of the geographical area divided by the area dividing module through the big data analysis module and setting the priority of different commodities sold in different geographical areas through the area grade setting module;
s4, classifying attributes of different commodities through a commodity classification module and uploading the attributes to a data sharing module, sharing commodity information to a logistics management center, a merchant and a manufacturer through a logistics management center, a merchant login module and a manufacturer login module through the data sharing module, and pre-warning the logistics company through a pre-warning module by the logistics management center according to the commodity scheduling information of the area so as to conveniently and reasonably distribute logistics resources;
s5, the commodity satisfaction degree grading module is used for conducting priority grading on different product satisfaction degrees, commodities with higher priority levels are recommended to customers through the commodity recommending module, commodity sales trend analysis is conducted through the trend analyzing module according to the commodity sales conditions, analysis data are uploaded to the merchant login module and the manufacturer login module, and merchants and manufacturers can conveniently respond to the analysis data in time.
10. The method for big data collaborative supervision according to claim 9, wherein: the data acquisition module acquires client browsing record information and current commodity purchasing information through a client information acquisition unit to acquire commodity evaluation information, the commodity evaluation information acquisition unit acquires commodity evaluation information, the logistics information acquisition unit acquires material distribution information, the commodity receiving place information acquisition unit acquires commodity receiving place information and the commodity attribute information acquisition unit acquires commodity attribute information, the data statistics module uploads data to a data storage module to be stored, and the data is maintained and safely managed through a data maintenance module and an information safety management module, the big data analysis module monitors whether the purchase quantity of a single dangerous article area reaches a set dangerous value through a safety monitoring module, alarms when the dangerous value is reached, the big data analysis module processes according to alarm information through an alarm module, and the trend analysis module acquires real-time commodity price information through a market price acquisition module, the merchant login module acquires commodity warehouse position information through the commodity warehouse position information acquisition module, acquires inventory information through the commodity inventory information acquisition module, and reminds the merchant of replenishment through the commodity replenishment reminding module.
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