CN110956307A - Business data standardization processing method and device - Google Patents
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Abstract
The invention discloses a standardized processing method and a standardized processing device for service data, wherein the method comprises the following steps: identifying the cause data in the received service data and judging whether the cause data changes; if the dynamic factor data changes, calculating the dynamic factor data by adopting a pre-constructed model to generate optimal source information of the commodity corresponding to the dynamic factor data, wherein the optimal source information comprises an optimal delivery address; and pushing the optimal goods source information to the target platform so that the target platform can select the optimal goods source when delivering goods. According to the invention, the pre-constructed model is adopted to calculate the dynamic data to generate the optimal goods source information of the goods corresponding to the dynamic data, so that the standardized processing of the pre-sale preparation data is realized, the sales platform is helped to position the delivery position more quickly, the operating profit margin is improved, the automatic calculation source searching (namely the goods source information) service is realized instead of manpower, the platform response speed is greatly improved, and the maintenance workload of business personnel is reduced.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and an apparatus for standardized processing of service data.
Background
At present, various state stores, various operation modes and various warehouse types of each sales platform have great difference in management of price, inventory, logistics distribution, financial settlement and the like, for example, personalized delivery rules are adopted respectively, and the personalized delivery rules are adopted for a long time, so that the defects of low efficiency, incapability of comprehensively utilizing goods sources and the like exist.
In view of the above drawbacks, it is desirable to provide a new standardized processing method for service data.
Disclosure of Invention
In order to solve the problems in the prior art, embodiments of the present invention provide a method and an apparatus for standardized processing of business data, so as to overcome the problems in the prior art that due to the adoption of personalized shipment rules for a long time, the efficiency is low, the source of goods cannot be utilized comprehensively, and the like.
In order to solve one or more technical problems, the invention adopts the technical scheme that:
in one aspect, a method for standardizing service data is provided, which includes the following steps:
identifying the cause data in the received service data, and judging whether the cause data changes;
if the cause data changes, calculating the cause data by adopting a pre-constructed model to generate optimal source information of the commodity corresponding to the cause data, wherein the optimal source information comprises an optimal delivery address:
and pushing the optimal goods source information to a target platform so that the target platform can select the optimal goods source when delivering goods.
Further, the calculating the dynamic factor data by using the pre-constructed model, and the generating the optimal source information of the commodity corresponding to the dynamic factor data includes:
acquiring a store range which influences the optimal goods source and corresponds to the goods corresponding to the dynamic factor data according to the dynamic factor data;
and calculating the store model and the dynamic factor data by adopting a pre-constructed model to obtain the optimal goods source information of the commodity.
Further, the cause data includes option data, the option data includes commodity, store, source information of the merchant, and a corresponding relationship between the commodity, the store, and the merchant, and the obtaining of the store range, which affects the optimal source, corresponding to the commodity corresponding to the cause data according to the cause data includes:
and inquiring preset commodity planning data according to the selection data, and acquiring a store range which influences the optimal goods source and corresponds to the commodity corresponding to the selection data.
Further, the cause data includes inventory data, and the obtaining of the store range of the optimal source of influence corresponding to the commodity corresponding to the cause data according to the cause data includes:
analyzing commodity and store information corresponding to the inventory data according to inventory records;
acquiring the item selection data corresponding to the store according to the commodity and the store information;
and acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the inventory data according to the selected data corresponding to the stores.
Further, the analyzing the commodity and store information corresponding to the inventory data according to the inventory records includes:
analyzing the inventory location and the commodity information in the inventory data, and judging whether the inventory location belongs to a preset goods source location of a logistics door storeroom;
if the current position information belongs to the corresponding position information, acquiring corresponding position information of the stock location;
and acquiring store information corresponding to the inventory location according to the library location information and a preset corresponding relation table of the library locations and stores.
Further, after the obtaining of the library position information corresponding to the inventory location, the method further includes:
and verifying whether the storage position information belongs to a preset goods source storage position of the logistics store.
Further, the analyzing the commodity and store information corresponding to the inventory data according to the inventory records further includes:
if the inventory location does not belong to a preset logistics door store source location, judging whether the inventory location belongs to the preset logistics door store source location;
if the current position information belongs to the corresponding position information, acquiring corresponding position information of the stock location;
and acquiring store information corresponding to the inventory location according to the inventory location information and a preset city and location corresponding relation table.
Further, after the obtaining of the library position information corresponding to the inventory location, the method further includes:
and verifying whether the storage position information belongs to a preset store source storage position of the store.
Further, the cause data includes price data, and the obtaining of the store range, corresponding to the commodity corresponding to the cause data, of the optimal source of influence according to the cause data includes:
and inquiring preset commodity planning data according to the price data, and acquiring a store range which influences the optimal goods source and corresponds to the commodity corresponding to the price data.
In another aspect, an apparatus for normalizing service data is provided, where the apparatus includes:
the data judgment module is used for identifying the cause data in the received service data and judging whether the cause data changes;
the information calculation module is used for calculating the dynamic data by adopting a pre-constructed model if the dynamic data changes, and generating the optimal source information of the commodity corresponding to the dynamic data, wherein the optimal source information comprises an optimal delivery address;
and the information pushing module is used for pushing the optimal goods source information to the target platform so that the target platform can select the optimal goods source when delivering goods.
Further, the information calculation module includes:
the range acquisition unit is used for acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the dynamic factor data according to the dynamic factor data;
and the information calculation unit is used for calculating the store range and the cause data by adopting a pre-constructed model to acquire the optimal goods source information of the commodity.
Further, the range acquisition unit includes:
and the first query unit is used for querying preset commodity planning data according to the option data and acquiring the store range which affects the optimal goods source and corresponds to the commodity corresponding to the option data.
Further, the range acquiring unit further includes:
the data analysis unit is used for analyzing the commodity and store information corresponding to the inventory data according to the inventory records;
the first acquisition unit is used for acquiring the item data corresponding to the store according to the commodity and the store information;
and the second acquisition unit is used for acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the inventory data according to the selection data corresponding to the stores.
Further, the data parsing unit includes:
the data analysis subunit is used for analyzing the inventory location and the commodity information in the inventory data;
the first judgment subunit is used for judging whether the inventory location belongs to a preset goods source location of a logistics door storeroom;
the first acquisition subunit is used for acquiring the storage position information corresponding to the storage location;
and the second acquisition subunit is used for acquiring store information corresponding to the inventory location according to the store information and a preset corresponding relation table between the store and the store.
Further, the data parsing unit further includes:
and the first verification subunit is used for verifying whether the storage position information belongs to a preset goods source storage position of the logistics store.
Further, the data parsing unit further includes:
the second judging subunit is used for judging whether the inventory location belongs to a preset store source location of the logistics store if the inventory location does not belong to the preset store source location of the logistics store;
the third acquisition subunit is used for acquiring the storage position information corresponding to the storage location;
and the fourth acquisition subunit is used for acquiring store information corresponding to the inventory location according to the inventory location information and a preset city and location corresponding relation table.
Further, the data parsing unit further includes:
and the second verification subunit is used for verifying whether the storage position information belongs to a preset store source storage position.
Further, the range acquiring unit further includes:
and the second query unit is used for querying preset commodity planning data according to the price data and acquiring the store range which influences the optimal goods source and corresponds to the commodity corresponding to the price data.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
1. according to the business data standardization processing method and device provided by the embodiment of the invention, the cause data in the received business data is identified, whether the cause data changes is judged, if the cause data changes, the cause data is calculated by adopting a pre-established model, the optimal source information of the commodity corresponding to the cause data is generated, and the optimal source information is pushed to a target platform so that the target platform can select the optimal source when delivering the goods, so that the business preparation data is standardized, the sales platform is helped to position the delivery position more quickly, and the profit rate of operation is improved;
2. according to the business data standardization processing method and device provided by the embodiment of the invention, the pre-constructed model is adopted to calculate the dynamic data to generate the optimal goods source information of the goods corresponding to the dynamic data, the automatic calculation and source searching (namely the goods source information) service is realized instead of manpower, the platform response speed is greatly improved, and the maintenance workload of business personnel is reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow diagram illustrating a method of standardized processing of business data in accordance with an exemplary embodiment;
FIG. 2 is a flow chart illustrating calculation of causal data using a pre-constructed model to generate optimal source information for a commodity corresponding to the causal data, according to an exemplary embodiment;
FIG. 3 is a flow diagram illustrating the obtaining of store areas affecting an optimal source corresponding to a good corresponding to the incentive data based on the incentive data, according to an exemplary embodiment;
FIG. 4 is a flowchart illustrating parsing out inventory data corresponding to goods and store information from inventory records, according to an exemplary embodiment;
fig. 5 is a schematic structural diagram illustrating a service data normalization processing apparatus according to an exemplary embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying 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.
Fig. 1 is a flowchart illustrating a method for standardizing processing of service data according to an exemplary embodiment, and referring to fig. 1, the method includes the following steps:
s1: and identifying the cause data in the received service data and judging whether the cause data changes.
Specifically, in the embodiment of the present invention, the service data mainly includes data related to the commodity. The cause data is set according to actual requirements, when the cause data changes, standardized processing of business data is triggered, and here, the optimal source information needs to be adjusted again according to the changed cause data. Therefore, after receiving the service data, it is necessary to identify the received service data to identify the cause data included in the service data, and then, to determine whether there is a change in the cause data by determining the identified cause data. In the specific judgment, the identified cause data can be compared with the historical cause data, if the identified cause data is not consistent with the historical cause data, the cause data is changed, otherwise, the cause data is not changed. It should be noted that, in the embodiment of the present invention, the cause data includes, but is not limited to, the following data: selection data, inventory data, price data, contract data, database age data, and the like.
S2: if the dynamic data changes, calculating the dynamic data by adopting a pre-constructed model to generate the optimal source information of the commodity corresponding to the dynamic data, wherein the optimal source information comprises an optimal delivery address.
Specifically, in the embodiment of the present invention, first, a calculation rule for calculating the optimal source information of the commodity needs to be preset according to the actual demand of the user, where the calculation rule includes a sales preparation policy and a rule, for example, different self-operated prices and self-operated inventory and contract are checked according to the commodity + store + merchant + business identifier of the supply chain selection. The following is a specific example: assuming that a business needs to sell a bottle of water in a small store channel of a merchant 1 in a store A, firstly, the business needs to operate a supply chain option (commodity water + store A + merchant 1+ business mark small stores), after the option is found, according to a calculation rule of optimal source information, according to the commodity water + store A + merchant 1, price inquiry is carried out, then inventory inquiry is continued according to the commodity water + store A + merchant 1, a contract is inquired according to a supplier corresponding to the commodity water + store A + merchant 1, and then under the condition of a plurality of sources, the lowest price and the largest storage age are preferentially taken as the optimal source (first-in first-out rule). After the fact that the dynamic factor data changes is judged, corresponding calculation rules are selected according to the specific dynamic factor data, and then the optimal source information of the commodities corresponding to the dynamic factor data is calculated and generated according to the selected calculation rules and the dynamic factor data, wherein the optimal source information comprises an optimal delivery address. It should be noted that, in the embodiment of the present invention, the optimal source information of the commodity corresponding to the cause data is calculated and generated according to the cause data and the preset calculation rule, so that an automated calculation source-searching service (i.e., source information) can be implemented instead of a manual work, the platform response speed is greatly increased, and the maintenance workload of service personnel is reduced.
Then, a calculation model is constructed according to a preset calculation rule, wherein as a preferred example, the model in the embodiment of the present invention may include a plurality of comparison operators, such as a price comparison operator, a library age comparison operator, an inventory status comparison operator, and an inventory available date comparison operator. The concrete flow of calculating the dynamic factor data by adopting the pre-constructed model to generate the optimal goods source information of the goods corresponding to the dynamic factor data is as follows:
when a plurality of effective goods sources exist, firstly, the operation of a price comparison operator is triggered, for example, the selling prices corresponding to the plurality of effective goods sources can be compared, and one or more goods sources with the minimum selling price are taken as an optimal source; if a plurality of effective goods sources exist after the steps, triggering the operation of the storage age comparison operator, and if the storage age of the goods corresponding to the plurality of effective goods sources can be compared, taking one or more goods sources with the minimum storage age as an optimal source; if a plurality of effective goods sources exist, the operation of the inventory state comparison operator is triggered, for example, the inventory states corresponding to the plurality of effective goods sources can be compared, and for example, the principle that the spot goods are in transit (meaning in transit); and finally, if a plurality of valid sources exist and the inventory states are all in transit, triggering the operation of an inventory available date comparison operator, such as the source which can meet the user requirement at the earliest can be selected.
S3: and pushing the optimal goods source information to a target platform so that the target platform can select the optimal goods source when delivering goods.
Specifically, after the optimal source information of the commodity corresponding to the incentive data is acquired, the optimal source information is pushed to a target platform (such as a sales platform) so that the target platform can select the optimal source for delivery when delivering the commodity, the sales platform is helped to position the delivery position more quickly, and the profit margin of operation is improved.
Fig. 2 is a flowchart illustrating that an actuator data is calculated by using a pre-constructed model according to an exemplary embodiment to generate optimal source information of a commodity corresponding to the actuator data, and as a preferred implementation manner, referring to fig. 2, in an embodiment of the present invention, calculating the actuator data by using the pre-constructed model to generate the optimal source information of the commodity corresponding to the actuator data includes:
s201: and acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the dynamic data according to the dynamic data.
Specifically, in the embodiment of the present invention, when the cause data changes, the product corresponding to the cause data is first obtained according to the specific cause data, and then the store range affecting the optimal source corresponding to the product is obtained.
S202: and calculating the store range and the cause data by adopting a pre-constructed model to obtain the optimal source information of the commodity.
Specifically, in the embodiment of the present invention, a pre-constructed model is used to calculate the store range and the cause data obtained according to the above steps, so as to obtain the optimal source information of the commodity. The item selection data comprises data such as a commodity + store + merchant + business identifier, and if one of the data changes, the corresponding commodity + store + merchant generates an item selection change cause, and the calculation of the prior item selection optimal source at the side is triggered (the calculation logic refers to the calculation rule of the optimal source information).
As a preferred implementation manner, in an embodiment of the present invention, the cause data includes option data, the option data includes commodities, stores, source information of merchants, and correspondence between the commodities, the stores, and the merchants, and the obtaining, according to the cause data, a store range that affects an optimal source corresponding to a commodity corresponding to the cause data includes:
and inquiring preset commodity planning data according to the selection data, and acquiring a store range which influences the optimal goods source and corresponds to the commodity corresponding to the selection data.
Specifically, in the embodiment of the present invention, the preset motivation data includes several types, including option data, where the option data refers to the commodity, store, and source information of the merchant, and the corresponding relationship between the commodity, the store, and the source information. When the cause data contained in the business data is identified as the option data, the option data is judged to be changed as long as the data of the commodity, the store, the source information of the merchant and one of the corresponding relations among the commodity, the store and the merchant is identified to be changed. Then, according to the item selection data, preset commodity planning data (such as prior commodity planning data specifically including a commodity code, an store code, a supplier code, an item selection type, an operation mode and the like) is queried, and an store range which affects the optimal goods source and corresponds to the commodity corresponding to the item selection data is obtained, that is, the store which affects the optimal goods source and corresponds to the commodity may be affected by the change of the item selection data.
Fig. 3 is a flowchart illustrating a process of acquiring, according to an exemplary embodiment, a store range affecting an optimal source corresponding to a product corresponding to cause data, and as a preferred implementation, referring to fig. 3, in an embodiment of the present invention, the cause data includes inventory data, and the acquiring, according to the cause data, the store range affecting the optimal source corresponding to the product corresponding to the cause data includes:
s301: and analyzing the commodity and store information corresponding to the inventory data according to the inventory records.
Specifically, when it is recognized that the cause data included in the business data is the stock data, when it is determined that the stock data has changed, it is first necessary to analyze the commodity and store information corresponding to the stock data from the stock record. Here, the inventory records include information of goods, stores, merchants, and the like, and in the specific analysis, the goods and store information corresponding to the inventory data may be queried in the inventory records according to the service identifier representing the goods, stores, or merchants carried in the inventory data.
S302: and acquiring the selection data corresponding to the store according to the commodity and the store information.
Specifically, according to the commodity and store information obtained in the above steps, the item selection data corresponding to the store is obtained, and in specific implementation, a pre-constructed store-sales organization relation table may be queried to obtain item selection data of all valid stores.
S303: and acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the inventory data according to the selected data corresponding to the stores.
Specifically, preset commodity planning data (such as prior commodity planning data) is inquired according to the acquired item data corresponding to the store, and the store range affecting the optimal source corresponding to the commodity corresponding to the item data is acquired, that is, the store affecting the optimal source corresponding to the commodity may be affected by the acquired change of the item data.
Fig. 4 is a flowchart illustrating a process of analyzing the commodity and store information corresponding to the inventory data according to the inventory records according to an exemplary embodiment, and referring to fig. 4, as a preferred implementation, in an embodiment of the present invention, the analyzing the commodity and store information corresponding to the inventory data according to the inventory records includes:
s401: analyzing the inventory location and the commodity information in the inventory data, and judging whether the inventory location belongs to a preset goods source location of the logistics store, if so, executing steps S402 to S403, otherwise, executing steps S404 to S406.
Specifically, firstly, the received inventory data is analyzed, the inventory location and the commodity information in the inventory data are analyzed, and then whether the inventory location belongs to a preset goods source location of the logistics store is judged. In specific implementation, a mode of judging whether the inventory location conforms to a preset inventory source location configuration item of the logistics store can be adopted.
S402: and if the current position information belongs to the corresponding position information, acquiring the corresponding position information of the stock location.
Specifically, if the inventory location meets the preset goods source location of the logistics door storeroom, the corresponding storage location information of the inventory location is obtained. Here, the storage location refers to a location where goods (i.e., merchandise) are stored. In order to facilitate finding the goods in warehouse management, a management mode of 'positioning four' is usually adopted for storing the goods, namely: library, shelf, layer, bit. The warehouse means that the goods are stored in a warehouse of several numbers, the shelf means that the goods are stored in a shelf of several numbers of the warehouse of several numbers, the layer means that the goods are stored in the layer of several numbers of the shelf of several numbers, and the position means that the goods are stored in the position of several numbers of the layer of several numbers of the shelf of several numbers.
S403: and acquiring store information corresponding to the inventory location according to the library location information and a preset corresponding relation table of the library locations and stores.
Specifically, in the embodiment of the present invention, a correspondence table between the library location and the store needs to be maintained in advance, and the correspondence table is mainly used for recording the correspondence between the library location and the store. After the specific storage position information is acquired, the corresponding relation table of the storage position and the store is inquired according to the storage position information, and store information corresponding to the storage location is acquired.
S404: and if the inventory location does not belong to a preset goods source location of the logistics store, judging whether the inventory location belongs to the preset goods source location of the logistics store.
Specifically, if the inventory location is determined to be not in accordance with the preset logistics store source location, it is continuously determined whether the inventory location belongs to the preset store source location, and in the specific determination, a manner of determining whether the inventory location is in accordance with the preset store source location configuration item may be adopted.
S405: and if the current position information belongs to the corresponding position information, acquiring the corresponding position information of the stock location.
Specifically, similarly, if the inventory location meets the preset store source location, the corresponding location information of the inventory location is obtained. The library position information can refer to the above contents, and is not described in detail here.
S406: and acquiring store information corresponding to the inventory location according to the inventory location information and a preset city and location corresponding relation table.
Specifically, in the embodiment of the present invention, a city and location correspondence table needs to be maintained in advance, and is mainly used for recording the city and location correspondence. After the specific storage position information is obtained, the corresponding relation table of the city and the place is inquired according to the place code of the storage position information, and store information corresponding to the storage place is obtained.
As a preferred implementation manner, in an embodiment of the present invention, after the obtaining of the library location information corresponding to the inventory location, the method further includes:
and verifying whether the storage position information belongs to a preset goods source storage position of the logistics store.
Specifically, after the information of the stock location corresponding to the stock location is obtained, it is also required to verify whether the information of the stock location belongs to a preset source stock location of the logistics store, if the information of the stock location belongs to the preset source stock location, the next operation is continued, otherwise, the flow is directly ended. The preset goods source storage positions of the logistics door storeroom comprise storage positions starting from 7, 8, 9 and A, B, C, G, H, I, so that whether the storage position information belongs to one of the storage positions can be verified, if yes, the verification is passed, and otherwise, the verification is not passed. Here, it should be noted that the first library of 7, 8, and 9 corresponds to a regular library, the first library of A, B, C corresponds to a special library, and the first library of G, H, I corresponds to a package vendor library.
As a preferred implementation manner, in an embodiment of the present invention, after the obtaining of the library location information corresponding to the inventory location, the method further includes:
and verifying whether the storage position information belongs to a preset store source storage position of the store.
Specifically, after the information of the storage location corresponding to the storage location is obtained, it is also required to verify whether the information of the storage location belongs to a preset store source storage location, if the information of the storage location belongs to the preset store source storage location, the next operation is continued, otherwise, the flow is directly ended.
As a preferred implementation manner, in an embodiment of the present invention, the cause data includes price data, and the obtaining, according to the cause data, a store range that affects an optimal source of goods corresponding to the product corresponding to the cause data includes:
and inquiring preset commodity planning data according to the price data, and acquiring a store range which influences the optimal goods source and corresponds to the commodity corresponding to the price data.
Specifically, when it is identified that the cause data included in the service data is price data, similarly, preset commodity planning data (such as prior commodity planning data) is queried according to the price data, and a store range affecting the optimal source corresponding to the commodity corresponding to the price data is obtained, that is, the store affecting the optimal source corresponding to the commodity may be affected by obtaining the change of the option data.
The following is a specific application scenario of the standardized processing method for service data provided by the embodiment of the present invention:
in this scene, including self-service sales preparation platform and sales platform, wherein self-service sales preparation platform mainly is used for carrying out standardized processing with the sales preparation data in advance, and wherein self-service sales preparation platform mainly includes:
the system comprises a commodity planning management System (SCCP) for uploading selected item data, wherein the data structure of the selected item data is 'merchant + delivery store + commodity';
a self-supporting price system (PTS) for mainly managing price data of commodities;
a self-management inventory system (SIMS) for managing inventory data of commodities;
and the service data standardization platform (SSDS) is used for calculating the dynamic data by adopting a pre-constructed model to generate the optimal goods source information of the corresponding commodity.
The user can respectively modify, newly add, delete and the like the option data, the stock data and the price data through a commodity planning management System (SCCP), a self-owned price system (PTS) and a self-owned stock system (SIMS). When a user operates one or more of the option data, the inventory data and the price data through a commodity planning management System (SCCP), a self-operated price system (PIS) and a self-operated inventory system (SIMS) to change one or more of the option data, the inventory data and the price data (i.e., cause data to change), the commodity planning management System (SCCP), the self-operated price system (PIS) or the self-operated inventory system (SIMS) pushes information of the change of the option data, the inventory data or the price data to a service data standardization platform (SSDS). Because the option data, the inventory data and the price data are all the cause data, after the service data standardization platform (SSDS) receives the information that the option data, the inventory data or the price data changes, the operation of calculating the cause data by using the pre-constructed model to generate the optimal source information of the commodity corresponding to the cause data is automatically triggered, and the specific calculation process can refer to the above contents and is not repeated one by one.
As a preferred implementation manner, the information composition of the optimal source information in the embodiment of the present invention includes "commodity + store + merchant + store + price". After the service data standardization platform (SSDS) calculates the optimal source information, the self-service sales preparation platform pushes the optimal source information to the sales platform, and the sales platform updates the data such as the inventory and price of corresponding commodities according to the optimal source information so that the target platform can select the optimal source for shipment when the commodities are shipped, the sales platform is helped to position the shipment position more quickly, and the profit rate of operation is improved.
Fig. 5 is a schematic structural diagram of a service data normalization processing apparatus according to an exemplary embodiment, and referring to fig. 5, the apparatus includes:
the data judgment module is used for identifying the cause data in the received service data and judging whether the cause data changes;
the information calculation module is used for calculating the dynamic data by adopting a pre-constructed model if the dynamic data changes, and generating the optimal source information of the commodity corresponding to the dynamic data, wherein the optimal source information comprises an optimal delivery address;
and the information pushing module is used for pushing the optimal goods source information to the target platform so that the target platform can select the optimal goods source when delivering goods.
As a preferred implementation manner, in an embodiment of the present invention, the information calculating module includes:
the range acquisition unit is used for acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the dynamic factor data according to the dynamic factor data;
and the information calculation unit is used for calculating the store range and the cause data by adopting a pre-constructed model to acquire the optimal goods source information of the commodity.
As a preferred implementation manner, in an embodiment of the present invention, the range obtaining unit includes:
and the first query unit is used for querying preset commodity planning data according to the option data and acquiring the store range which affects the optimal goods source and corresponds to the commodity corresponding to the option data.
As a preferred implementation manner, in an embodiment of the present invention, the range obtaining unit further includes:
the data analysis unit is used for analyzing the commodity and store information corresponding to the inventory data according to the inventory records;
the first acquisition unit is used for acquiring the item data corresponding to the store according to the commodity and the store information;
and the second acquisition unit is used for acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the inventory data according to the selection data corresponding to the stores.
As a preferred implementation manner, in an embodiment of the present invention, the data parsing unit includes:
the data analysis subunit is used for analyzing the inventory location and the commodity information in the inventory data;
the first judgment subunit is used for judging whether the inventory location belongs to a preset goods source location of a logistics door storeroom;
the first acquisition subunit is used for acquiring the storage position information corresponding to the storage location;
and the second acquisition subunit is used for acquiring store information corresponding to the inventory location according to the store information and a preset corresponding relation table between the store and the store.
As a preferred implementation manner, in an embodiment of the present invention, the data analysis unit further includes:
and the first verification subunit is used for verifying whether the storage position information belongs to a preset goods source storage position of the logistics store.
As a preferred implementation manner, in an embodiment of the present invention, the data analysis unit further includes:
the second judging subunit is used for judging whether the inventory location belongs to a preset store source location of the logistics store if the inventory location does not belong to the preset store source location of the logistics store;
the third acquisition subunit is used for acquiring the storage position information corresponding to the storage location;
and the fourth acquisition subunit is used for acquiring store information corresponding to the inventory location according to the inventory location information and a preset city and location corresponding relation table.
As a preferred implementation manner, in an embodiment of the present invention, the data analysis unit further includes:
and the second verification subunit is used for verifying whether the storage position information belongs to a preset store source storage position.
As a preferred implementation manner, in an embodiment of the present invention, the range obtaining unit further includes:
and the second query unit is used for querying preset commodity planning data according to the price data and acquiring the store range which influences the optimal goods source and corresponds to the commodity corresponding to the price data.
In summary, the technical solution provided by the embodiment of the present invention has the following beneficial effects:
1. according to the business data standardization processing method and device provided by the embodiment of the invention, the cause data in the received business data is identified, whether the cause data changes is judged, if the cause data changes, the cause data is calculated by adopting a pre-established model, the optimal source information of the commodity corresponding to the cause data is generated, and the optimal source information is pushed to a target platform so that the target platform can select the optimal source when delivering the goods, so that the business preparation data is standardized, the sales platform is helped to position the delivery position more quickly, and the profit rate of operation is improved;
2. according to the business data standardization processing method and device provided by the embodiment of the invention, the pre-constructed model is adopted to calculate the dynamic data to generate the optimal goods source information of the goods corresponding to the dynamic data, the automatic calculation and source searching (namely the goods source information) service is realized instead of manpower, the platform response speed is greatly improved, and the maintenance workload of business personnel is reduced.
It should be noted that: the standardized processing device for service data provided in the foregoing embodiment is only illustrated by the division of the functional modules when triggering a data standard service, and in practical applications, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the service data standardization processing device and the service data standardization processing method provided by the above embodiments belong to the same concept, that is, the device is based on the data importing method of the graph database, and the specific implementation process thereof is detailed in the method embodiments and will not be described herein again.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A standardized processing method of service data is characterized in that the method comprises the following steps:
identifying the cause data in the received service data, and judging whether the cause data changes;
if the dynamic factor data changes, calculating the dynamic factor data by adopting a pre-constructed model to generate optimal source information of the commodity corresponding to the dynamic factor data, wherein the optimal source information comprises an optimal delivery address;
and pushing the optimal goods source information to a target platform so that the target platform can select the optimal goods source when delivering goods.
2. The method for standardizing processing business data according to claim 1, wherein the calculating the cause data by using a pre-constructed model to generate the optimal source information of the commodity corresponding to the cause data comprises:
acquiring a store range which influences the optimal goods source and corresponds to the goods corresponding to the dynamic factor data according to the dynamic factor data;
and calculating the store range and the cause data by adopting a pre-constructed model to obtain the optimal source information of the commodity.
3. The method for standardizing processing business data according to claim 2, wherein the cause data includes option data, the option data includes commodity, store, source information of a merchant, and correspondence between the commodity, the store, and the source information of the merchant, and the obtaining of the store range affecting the optimal source corresponding to the commodity corresponding to the cause data according to the cause data includes:
and inquiring preset commodity planning data according to the selection data, and acquiring a store range which influences the optimal goods source and corresponds to the commodity corresponding to the selection data.
4. The method for standardizing processing business data according to claim 2, wherein the cause data includes stock data, and the obtaining of the store range affecting the optimal source of the goods corresponding to the cause data according to the cause data includes:
analyzing commodity and store information corresponding to the inventory data according to inventory records;
acquiring the item selection data corresponding to the store according to the commodity and the store information;
and acquiring the store range which influences the optimal goods source and corresponds to the goods corresponding to the inventory data according to the selected data corresponding to the stores.
5. The method for standardizing processing business data according to claim 4, wherein the analyzing the commodity and store information corresponding to the inventory data according to the inventory record comprises:
analyzing the inventory location and the commodity information in the inventory data, and judging whether the inventory location belongs to a preset goods source location of a logistics door storeroom;
if the current position information belongs to the corresponding position information, acquiring corresponding position information of the stock location;
and acquiring store information corresponding to the inventory location according to the library location information and a preset corresponding relation table of the library locations and stores.
6. The method for standardized processing of business data according to claim 5, wherein after the obtaining of the corresponding stock location information, the method further comprises:
and verifying whether the storage position information belongs to a preset goods source storage position of the logistics store.
7. The method for standardizing processing business data as claimed in claim 4, wherein the analyzing the commodity and store information corresponding to the stock data according to the stock record further comprises:
if the inventory location does not belong to a preset logistics door store source location, judging whether the inventory location belongs to the preset logistics door store source location;
if the current position information belongs to the corresponding position information, acquiring corresponding position information of the stock location;
and acquiring store information corresponding to the inventory location according to the inventory location information and a preset city and location corresponding relation table.
8. The method for standardized processing of business data according to claim 7, wherein after the obtaining of the corresponding stock location information, the method further comprises:
and verifying whether the storage position information belongs to a preset store source storage position of the store.
9. The method for standardizing processing business data according to claim 2, wherein the cause data includes price data, and the obtaining of the store range affecting the optimal source of the goods corresponding to the cause data according to the cause data includes:
and inquiring preset commodity planning data according to the price data, and acquiring a store range which influences the optimal goods source and corresponds to the commodity corresponding to the price data.
10. A device for processing standardized traffic data according to any one of claims 1 to 9, wherein the device comprises:
the data judgment module is used for identifying the cause data in the received service data and judging whether the cause data changes;
the information calculation module is used for calculating the dynamic data by adopting a pre-constructed model if the dynamic data changes, and generating the optimal source information of the commodity corresponding to the dynamic data, wherein the optimal source information comprises an optimal delivery address;
and the information pushing module is used for pushing the optimal goods source information to the target platform so that the target platform can select the optimal goods source when delivering goods.
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