CN115099921A - Financial data generation method and system based on block chain technology - Google Patents
Financial data generation method and system based on block chain technology Download PDFInfo
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Abstract
The invention relates to the technical field of financial data generation, and particularly discloses a financial data generation method and a system based on a block chain technology, wherein the method comprises the steps of obtaining regional labels of all branch stores, and establishing a mutually connected sales parameter table corresponding to all branch stores according to the regional labels; obtaining sales data of each branch in real time based on the sales parameter table, and counting the sales data in each sales parameter table to obtain a block data chain taking the area label as an index; and correcting the block data chain according to the pushing resources to obtain financial data. Based on the block chain technology, a data sharing platform is built, only sales time and sales products are obtained, computing equipment of each branch store independently reads and packages sales data provided by each branch store to generate a data block chain, and then theoretical states are determined according to pushed resources to perform correction operation; the sales data is obtained on the basis of not relating to excessive branch store operation states.
Description
Technical Field
The invention relates to the technical field of financial data generation, in particular to a financial data generation method and system based on a block chain technology.
Background
The existing offline physical stores are a plurality of chain or franchised stores, the franchised stores have unity and certain independence, and the unity is that the franchised stores share a set of management modes, a formula and the like, or other unified characteristic points; the independence means that the branch stores and the main store are possibly mutually independent, and the main store and the branch stores are not in a superior-inferior relationship;
according to the unification, the innovation process is mastered by a main shop, innovation is made by the main shop, and branch shops follow up; the innovation process of the main store needs to acquire the sales data of each branch, but due to the independence, each branch is unwilling to give the main store the authority to acquire the sales data;
for example, one cooperation mode is supply in a main store, independent pricing of branch stores, 5 yuan of price sold by the main store to the branch stores, 20 yuan of price sold by the branch stores may be sold, if the main store knows that the branch stores sell 20 yuan, the price is increased, 10 yuan is increased from 5 yuan, and the branch stores are obviously in a weak position in the pricing process; therefore, the branch stores can regard the sales data as the trade secret and cannot report the trade secret to the main store, so that the innovation process of the main store is influenced; for another example, some branch stores hold some activities which can be responded to, so that the sales volume of the product is greatly increased, the innovation of the branch stores is realized, and the branch stores are generally not required to be found by the head office;
therefore, how to acquire the sales data of the branch stores under the condition of not relating to the operation state of the branch stores per se and providing a basis for innovation is the technical problem to be solved by the technical scheme of the invention.
Disclosure of Invention
The present invention provides a method and a system for generating financial data based on a block chain technique, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
a method of financial data generation based on blockchain techniques, the method comprising:
acquiring regional labels of all branch stores, and establishing a mutually connected sales parameter list corresponding to all branch stores according to the regional labels; the sales parameter table includes a sales time item, a sales product item, and a sales income item;
obtaining sales data of each branch in real time based on the sales parameter table, and counting the sales data in each sales parameter table to obtain a block data chain taking the area label as an index;
and acquiring push resources, correcting the block data chain according to the push resources, and taking the corrected block data chain as financial data.
As a further scheme of the invention: the step of acquiring the regional labels of the branch stores and establishing the mutually connected sales parameter tables corresponding to the branch stores according to the regional labels comprises the following steps:
reading a target area of a pushed resource, and acquiring an area label of the target area; the target area of the pushed resource is a preset value;
acquiring branch numbers and position information of branches in the target area, establishing an empty sales parameter table, and inserting the branch numbers into the sales parameter table;
determining a connection diagram according to the area label and the position information, and establishing a connection relation between each node in the connection diagram and each sales parameter table; the connection graph is an undirected weightless graph, the node values are branch numbers, and the edge values and the distances between the branches have a mapping relation.
As a further scheme of the invention: the step of acquiring the sales data of each branch in real time based on the sales parameter table, counting the sales data in each sales parameter table, and obtaining a block data chain with the area tag as an index comprises the following steps:
the generated sales parameter table is sent to a corresponding branch store, and the sales time, the sales products and the sales profits of the branch store are recorded in real time based on the sales parameter table; wherein the sales revenue is determined only by the sales product; the sales profits corresponding to different sales products are determined values preset by a head office;
traversing all sales time items in the sales parameter table by a preset time starting point and a preset time period, and extracting data items of the sales time contained in the time period;
calculating the number of the extracted data items, packing the extracted data items and inserting a time tag generated by a time starting point and a time period when the number of the data items reaches a preset number threshold value to obtain a data block, and connecting the obtained data block with a stored block data chain; updating the time starting point according to the time information of the last data item;
and when the number of the data items is less than a preset number threshold value, prolonging the time period.
As a further scheme of the invention: when the number of the data items reaches a preset number threshold, packing the extracted data items and inserting a time tag generated by a time starting point and a time period to obtain a data block, wherein the step of connecting the obtained data block with the stored block data chain comprises the following steps:
when the number of the data items reaches a preset number threshold, reading a time starting point and a time period, and generating a time tag;
reading a chain tail time point corresponding to a data block at the tail of a block data chain, and judging whether the chain tail time point exceeds the tail time of the time tag or not;
when the time point of the chain tail exceeds the tail of the time tag, packing the extracted data items, inserting the time tag to obtain a data block, updating the block data chain according to the head time of the time tag in the obtained data block, and taking the tail time in the time tag as a new time starting point;
and when the chain tail time point does not exceed the tail part of the time tag, reading the chain tail time point as a new time starting point.
As a further scheme of the invention: the step of acquiring the push resource, modifying the block data chain according to the push resource, and using the modified block data chain as financial data includes:
inquiring the pushed resources and feedback information of the area according to the area label; the feedback information comprises access number, praise number, collection number and forwarding number;
inputting the feedback information into a preset linear calculation formula, and calculating the effective number of the pushed resources;
reading a flow conversion rate obtained by pre-statistics, and calculating theoretical passenger flow according to the flow conversion rate and the effective number;
reading a connection diagram, and distributing theoretical passenger flow volume according to the theoretical passenger flow proportion at each branch shop of the connection diagram based on the theoretical passenger flow proportion to obtain the theoretical passenger flow volume of each branch shop;
acquiring passenger flow time distribution characteristics of each branch store, and distributing theoretical passenger flow of each branch store according to the passenger flow time distribution characteristics to obtain the theoretical passenger flow of each branch store in each time period; the passenger flow time distribution characteristics are used for representing the passenger flow distribution characteristics of any branch store in different time periods within one time period;
and correcting each data block in the block data chain according to the theoretical passenger flow of each branch store in each time period, and taking the corrected block data chain as financial data.
As a further scheme of the invention: when the number of the data items reaches a preset number threshold, packing the extracted data items and inserting a time tag generated by a time starting point and a time period to obtain a data block, further comprising:
when the number of the data items reaches a preset number threshold value, sequentially inquiring branch stores corresponding to the data items to generate a data distribution array; the subscript of the data distribution array is the position information of branch stores, and the value of the data distribution array is the number of data strips;
comparing the data distribution array with a data distribution array corresponding to a previous data block, and calculating the data change rate of each branch;
and (4) counting the data change rate of each branch store to obtain the change curve of each branch store.
The technical scheme of the invention also provides a financial data generation system based on the block chain technology, which is characterized by comprising the following steps:
the template generation module is used for acquiring the regional labels of all branch stores and establishing a mutually connected sales parameter table corresponding to all branch stores according to the regional labels; the sales parameter table includes a sales time item, a sales product item, and a sales income item;
the data statistics module is used for acquiring sales data of each branch in real time based on the sales parameter table, and performing statistics on the sales data in each sales parameter table to obtain a block data chain with the regional labels as indexes;
and the data correction module is used for acquiring the push resources, correcting the block data chain according to the push resources and taking the corrected block data chain as financial data.
As a further scheme of the invention: the template generation module comprises:
the area tag query unit is used for reading a target area of the pushed resource and acquiring an area tag of the target area; the target area of the pushed resource is a preset value;
the empty table establishing unit is used for acquiring branch numbers and position information of branches in the target area, establishing an empty sales parameter table and inserting the branch numbers into the sales parameter table;
the connection relation establishing unit is used for determining a connection diagram according to the area label and the position information and establishing the connection relation between each node in the connection diagram and each sales parameter table; the connection graph is an undirected weightless graph, the node values are branch numbers, and the edge values and the distances between the branches have a mapping relation.
As a further scheme of the invention: the data statistics module comprises:
the sales data acquisition unit is used for sending the generated sales parameter table to the corresponding branch store and recording the sales time, the sales products and the sales profits of the branch store in real time based on the sales parameter table; wherein the sales revenue is determined only by the sales product; the sales profits corresponding to different sales products are determined values preset by a head office;
the data extraction unit is used for traversing all the sales time items in the sales parameter table by a preset time starting point and a preset time period, and extracting the data items of which the sales time is contained in the time period;
the data packing unit is used for calculating the number of the extracted data items, packing the extracted data items and inserting the time tags generated by the time starting points and the time periods when the number of the data items reaches a preset number threshold value to obtain data blocks, and connecting the obtained data blocks with the stored block data chains; updating the time starting point according to the time information of the last data item;
and the time updating unit is used for prolonging the time period when the number of the data items is smaller than a preset number threshold value.
As a further scheme of the invention: the data packing unit includes:
the tag generation subunit is used for reading a time starting point and a time period and generating a time tag when the number of the data items reaches a preset number threshold;
the time ratio subunit is used for reading a chain tail time point corresponding to a data block at the tail of the block data chain and judging whether the chain tail time point exceeds the tail time of the time tag or not;
a block updating subunit, configured to, when the chain tail time point exceeds the tail of the time tag, pack the extracted data items, insert the time tag to obtain a data block, update the block data chain according to the head time of the time tag in the obtained data block, and use the tail time in the time tag as a new time starting point;
and the block inserting subunit is used for reading the chain tail time point as a new time starting point when the chain tail time point does not exceed the tail part of the time tag.
Compared with the prior art, the invention has the beneficial effects that: based on the block chain technology, a data sharing platform is built, only sales time and sales products are obtained, computing equipment of each branch store independently reads and packages sales data provided by each branch store to generate a data block chain, a theoretical state is determined according to pushed resources, and the data block chain is corrected; the sales data is obtained on the basis of not relating to excessive branch store operation states.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 is a block diagram of a method for generating financial data based on a blockchain technique.
Fig. 2 is a first sub-flow block diagram of a financial data generation method based on the blockchain technique.
Fig. 3 is a second sub-flow block diagram of a financial data generation method based on the blockchain technique.
Fig. 4 is a third sub-flow block diagram of a financial data generation method based on the blockchain technique.
Fig. 5 is a block diagram of the financial data generating system based on the blockchain technique.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
Fig. 1 is a flowchart of a financial data generating method based on a blockchain technique, and in an embodiment of the present invention, a financial data generating method based on a blockchain technique includes steps S100 to S300:
step S100: acquiring regional labels of all branch stores, and establishing a sales parameter table which is connected with each other and corresponds to each branch store according to the regional labels; the sales parameter table includes a sales time item, a sales product item, and a sales income item;
each branch is provided with a consumption recording device, and the recorded consumption information contains financial data required by a main store; wherein, the time of sale item, the product of sale item and the income of sale item are three items which are relatively important;
step S200: obtaining sales data of each branch in real time based on the sales parameter table, and counting the sales data in each sales parameter table to obtain a block data chain taking the area label as an index;
each branch store obtains the sales data of each branch store based on the generated sales parameter table, and the sales data are counted to obtain the sales data of one region; it should be noted that the main store is different from the branch stores, and when the branch stores obtain the sales data, many information can be obtained, such as when a certain product is sold, whether the client to be sold is a member or a non-member, and what kind of price the product is sold, but the main store only obtains three data, namely, the time of sale, the product to be sold, and the sales income;
the sales product and the sales income correspond to each other, and the income of one product is fixed for a main store, for example, the cost of one cup of milk tea is 2 yuan, the price of each branch store is 8 yuan, the income is 6 yuan, and the income is not considered for the number of yuan sold by each branch store;
furthermore, in one area, the sales data of each branch store is uniformly stored based on the blockchain technology, and the computing node can be a computing processing device in any branch store; a platform is built between the nodes, data acquired by each node is uploaded to the platform, and computing processing equipment of each branch store can download the data and package the data to generate data blocks;
step S300: and acquiring a pushing resource, correcting the block data chain according to the pushing resource, and taking the corrected block data chain as financial data.
In the technical scheme of the invention, the classification mode of the region takes the push resources as reference, and most of the existing push resources have a relatively stable feedback rate, for example, a certain numerical relationship exists between the praise number of a promotion video and the amount of customers which can be brought by the promotion video, and the numerical relationship is stable; therefore, the passenger flow conditions of the branch stores in the area can be roughly acquired according to the pushed resources, the generated block chain is subjected to data correction according to the acquired passenger flow conditions, and the factors of the branch stores can be eliminated to a certain extent to obtain the data which the head office wants to acquire.
Fig. 2 is a first sub-flow block diagram of a financial data generating method based on a block chain technique, where the step of acquiring regional labels of the branches and establishing a sales parameter table corresponding to the branches according to the regional labels includes:
step S101: reading a target area of a pushed resource, and acquiring an area label of the target area; the target area of the pushed resource is a preset value;
push resources in different areas are slightly different, for example, some push videos are characterized by using dialects, which have very strong regional colors; determining a region to be detected by taking the pushed resource as a reference;
step S102: acquiring branch numbers and position information of branches in the target area, establishing an empty sales parameter table, and inserting the branch numbers into the sales parameter table;
different branch stores in different areas correspond to different sales parameter tables, the sales parameter tables play a buffering role, information which is required to be acquired by a main store is acquired based on the sales parameter tables, then the information is counted, and block chain data which are not divided into blocks are generated;
step S103: determining a connection diagram according to the area label and the position information, and establishing a connection relation between each node in the connection diagram and each sales parameter table; the connection graph is an undirected weightless graph, the node values are branch numbers, and the edge values and the distances between the branches have a mapping relation;
the connection diagram can be understood as a simplified version of a map showing the relationship between the branches in the form of a diagram data structure, each branch in the map being connected to a sales parameter table.
Fig. 3 is a second sub-flow block diagram of a financial data generating method based on a block chain technique, where the step of obtaining sales data of each branch in real time based on the sales parameter table, counting the sales data in each sales parameter table, and obtaining a block data chain with a regional label as an index includes steps S201 to S204:
step S201: sending the generated sales parameter table to a corresponding branch store, and recording the sales time, the sales products and the sales profits of the branch store in real time based on the sales parameter table; wherein the sales revenue is determined only by the sales product; the sales profits corresponding to different sales products are determined values preset by a head office;
the process of recording the sales time, the sales products and the sales profits of the branch in real time based on the sales parameter table is very simple, is a template application process, and acquires information to be acquired according to a template;
step S202: traversing all sales time items in the sales parameter table by a preset time starting point and a preset time period, and extracting data items of the sales time contained in the time period;
step S202 is a process of counting data in all sales schedules, and the time starting point and the time period define a time range, for example, the time starting point is 11: 40, the time period is 20 minutes, then the process of step S202 is to extract 11: 40 to 12: 00 all data items in the time range;
step S203: calculating the number of the extracted data items, packing the extracted data items and inserting a time tag generated by a time starting point and a time period when the number of the data items reaches a preset number threshold value to obtain a data block, and connecting the obtained data block with a stored block data chain; updating the time starting point according to the time information of the last data item;
calculating the acquired data items, and if the number of the data items reaches a certain degree, packaging the counted data items and connecting the data items to a block data chain; it is conceivable that, at 11: 40 to 12: 00, it is possible to operate in the time range of 11: 50 has reached the packing requirement, then after the data is packed, the time start is changed to 11: 50, again for a period of 20 minutes, continuing at 11: 50 to 12: acquiring and packaging data within the time range of 10; this process is repeated;
step S204: when the number of the data items is smaller than a preset number threshold value, prolonging the time period;
if at 12: 00, the packing requirement has not been met, then the time period is extended by a period, that is, at 11: 40 to 12: 20, acquiring data in a time range; it is worth mentioning that these time ranges serve as time tags for the data blocks.
Further, when the number of data items reaches a preset number threshold, packing the extracted data items and inserting a time tag generated by a time start point and a time period to obtain a data block, and connecting the obtained data block with a stored block data chain includes:
when the number of the data items reaches a preset number threshold, reading a time starting point and a time period, and generating a time tag;
reading a chain tail time point corresponding to a data block at the tail of a block data chain, and judging whether the chain tail time point exceeds the tail time of the time tag or not;
when the time point of the chain tail exceeds the tail of the time tag, packing the extracted data items, inserting the time tag to obtain a data block, updating the block data chain according to the head time of the time tag in the obtained data block, and taking the tail time in the time tag as a new time starting point;
and when the chain tail time point does not exceed the tail part of the time tag, reading the chain tail time point as a new time starting point.
The above content specifically describes the packaging process of the data block, and because the computing devices of the branch stores are independent of each other and the packaging nodes are also independent of each other, the performance of the computing devices is different from that of the idle state, in the common packaging process, some computing devices are faster, some computing devices are slower, and the content packaged by the computing devices with the fastest speed is connected to the existing data link.
In the process, the speed is reflected by the time point, the two important time points are respectively the chain tail time point of the data chain and the tail time in the time label of the new data block, and the new data block can be judged by comparing the two time points.
It is worth mentioning that some computing devices may miss the packaging process, for example, 11: 40 to 11: 50, but some faster computing device misses some data, it generates longer timestamps, such as 11: 40 to 11: 51; therefore, when the time range corresponding to the time tag of the data block packaged by another computing device is shorter, the data of the data block is more complete, and at this time, the data chain needs to be updated.
Fig. 4 is a block diagram of a third sub-flow of a financial data generating method based on a blockchain technique, where the step of acquiring a push resource, modifying the blockchain according to the push resource, and using the modified blockchain as financial data includes:
step S301: inquiring the push resources and feedback information of the area according to the area label; the feedback information comprises access number, praise number, collection number and forwarding number;
the method comprises the following steps that a variety of pushed resources are available, in the prior art, documents and short videos are mainly used, feedback information of a user can be obtained through the documents or the short videos, the feedback information comprises browsing duration, browsing times and the like, in the technical scheme of the invention, four data are mainly commented, namely access number, praise number, collection number and forwarding number, wherein the access number is passive and is used as a base number, and the praise number, the collection number and the forwarding number are dominant by the user and can reflect the preference degree of the user;
step S302: inputting the feedback information into a preset linear calculation formula, and calculating the effective number of the pushed resources;
the three behaviors of praise, collection and forwarding represent preferences of users in different degrees, and the three numerical values are unified by means of a preset linear calculation formula, so that an effective number reflecting the preference degree of the users can be obtained;
step S303: reading a flow conversion rate obtained by pre-statistics, and calculating a theoretical passenger flow according to the flow conversion rate and the effective number;
the method comprises the steps that a traffic conversion rate is counted at regular time by a promotion service business to serve as known data; according to the flow conversion rate and the calculated effective number, the theoretical passenger flow can be calculated;
step S304: reading a connection diagram, and distributing theoretical passenger flow volume according to the theoretical passenger flow proportion at each branch shop of the connection diagram based on the theoretical passenger flow proportion to obtain the theoretical passenger flow volume of each branch shop;
the connection diagram is a simplified version of map, which contains the position information of each branch, the community state around each branch can be determined according to the position information and the existing map service, and the theoretical people flow proportion between the partitions can be determined according to the community state, the theoretical people flow proportion is used for representing the location dominance of each branch, for example, the people flow of the branch arranged in the downtown is generally larger than the people flow of the branch arranged in the effective area; the theoretical passenger flow volume is distributed according to the theoretical passenger flow proportion, and then the theoretical passenger flow volume of each branch shop can be obtained; the theoretical passenger flow is only a theoretical value obtained based on pushing resources, and a large difference exists between the theoretical value and the actual situation.
Step S305: acquiring passenger flow time distribution characteristics of each branch store, and distributing theoretical passenger flow of each branch store according to the passenger flow time distribution characteristics to obtain the theoretical passenger flow of each branch store in each time period; the passenger flow time distribution characteristics are used for representing the passenger flow distribution characteristics of any branch store in different time periods within one time period;
the theoretical passenger flow of one branch store is distributed according to time periods, the passenger flow of the branch store is probably less at the working time of a working day, and the passenger flow is larger at the late peak time period; therefore, the theoretical pedestrian volume of each branch needs to be secondarily distributed according to the time distribution characteristics;
step S306: correcting each data block in the block data chain according to the theoretical passenger flow of each branch store in each time period, and taking the corrected block data chain as financial data;
the block data chain is corrected according to the theoretical passenger flow, so that the influence of the reasons of each branch store on the sales data can be reduced to a certain extent; specifically, in the same time period, the real passenger flow volume corresponding to the sales data in the block data chain is calculated, the real passenger flow volume is compared with the theoretical passenger flow volume, deviation ratios can be calculated, the deviation ratios are compared with a plurality of preset deviation threshold values, the deviation degree of the passenger flow volume of a certain branch store can be determined, the deviation degree reflects the influence of each branch store, and the sales data in the block data chain can be adjusted based on the deviation degrees.
Specifically, for the adjustment mode, the block data chain does not contain branch store information, and only the sales time, the sales products and the sales profits are needed, the deviation degrees of the passenger flow volumes of all branch stores are counted, the deviation degree in one area is calculated, and the data in the block data chain is randomly deleted or duplicated and expanded according to the deviation degree. Wherein the operation corresponding to each deviation degree is preset.
As a preferred embodiment of the technical solution of the present invention, when the number of data items reaches a preset number threshold, the step of packing the extracted data items and inserting the time tag generated by the time start point and the time period to obtain the data block further includes:
when the number of the data items reaches a preset number threshold value, sequentially inquiring branch stores corresponding to the data items to generate a data distribution array; the subscript of the data distribution array is the position information of branch stores, and the value of the data distribution array is the number of data strips;
comparing the data distribution array with a data distribution array corresponding to a previous data block, and calculating the data change rate of each branch;
and (4) counting the data change rate of each branch store to obtain the change curve of each branch store.
In one example of the technical scheme of the invention, when the sales data in the sales parameter table corresponding to each branch is extracted, which branches generate each data item in a data block are calculated in real time, and then on the basis of the branches, each branch is calculated to provide several data items in the data block; the operation is carried out on each data block, the change condition of each branch can be obtained, and the state of each branch can be controlled according to the change condition;
it should be noted that, the above technical solution needs to be established on the basis that the main store has the management authority of the branch store, and if the main store does not have the management authority of the branch store, the branch store corresponding to the data item cannot be queried.
Example 2
Fig. 5 is a block diagram of a component structure of a financial data generating system based on a blockchain technology, in an embodiment of the present invention, a financial data generating system based on a blockchain technology includes:
the template generation module 11 is used for acquiring regional labels of all branch stores, and establishing a mutually connected sales parameter table corresponding to each branch store according to the regional labels; the sales parameter table includes a sales time item, a sales product item, and a sales income item;
the data statistics module 12 is configured to obtain sales data of each branch in real time based on the sales parameter table, and perform statistics on the sales data in each sales parameter table to obtain a block data chain using the area tag as an index;
and the data correction module 13 is configured to acquire a push resource, correct the block data chain according to the push resource, and use the corrected block data chain as financial data.
Further, the template generating module 11 includes:
the area label query unit is used for reading a target area of the pushed resource and acquiring an area label of the target area; the target area of the pushed resource is a preset value;
the empty table establishing unit is used for acquiring branch numbers and position information of all branches in the target area, establishing an empty sales parameter table and inserting the branch numbers into the sales parameter table;
the connection relation establishing unit is used for determining a connection diagram according to the area label and the position information and establishing the connection relation between each node in the connection diagram and each sales parameter table; the connection graph is an undirected weightless graph, the node values are branch numbers, and the edge values and the distances between the branches have a mapping relation.
Specifically, the data statistics module 12 includes:
the sales data acquisition unit is used for sending the generated sales parameter table to a corresponding branch store and recording the sales time, the sales products and the sales profits of the branch store in real time based on the sales parameter table; wherein the sales revenue is determined only by the sales product; the sales profits corresponding to different sales products are determined values preset by a head office;
the data extraction unit is used for traversing all the sales time items in the sales parameter table by a preset time starting point and a preset time period, and extracting the data items of which the sales time is contained in the time period;
the data packing unit is used for calculating the number of the extracted data items, packing the extracted data items and inserting the time tags generated by the time starting points and the time periods when the number of the data items reaches a preset number threshold value to obtain data blocks, and connecting the obtained data blocks with the stored block data chains; updating the time starting point according to the time information of the last data item;
and the time updating unit is used for prolonging the time period when the number of the data items is smaller than a preset number threshold value.
Further, the data packing unit includes:
the tag generation subunit is used for reading a time starting point and a time period and generating a time tag when the number of the data items reaches a preset number threshold;
the time ratio subunit is used for reading a chain tail time point corresponding to a data block at the tail of the block data chain and judging whether the chain tail time point exceeds the tail time of the time tag or not;
the block updating subunit is configured to, when the time point of the tail of the chain exceeds the tail of the time tag, pack the extracted data item, insert the time tag to obtain a data block, update the block data chain according to the head time of the time tag in the obtained data block, and use the tail time in the time tag as a new time starting point;
and the block inserting subunit is used for reading the chain tail time point as a new time starting point when the chain tail time point does not exceed the tail part of the time tag.
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 and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A method for generating financial data based on a block chain technique, the method comprising:
acquiring regional labels of all branch stores, and establishing a sales parameter table which is connected with each other and corresponds to each branch store according to the regional labels; the sales parameter table includes a sales time item, a sales product item, and a sales income item;
obtaining sales data of each branch in real time based on the sales parameter table, and counting the sales data in each sales parameter table to obtain a block data chain with the area tags as indexes;
and acquiring a pushing resource, correcting the block data chain according to the pushing resource, and taking the corrected block data chain as financial data.
2. The method of claim 1, wherein the step of obtaining regional labels of the branches and establishing the sales parameter tables corresponding to the branches according to the regional labels comprises:
reading a target area of a pushed resource, and acquiring an area label of the target area; the target area of the pushed resource is a preset value;
acquiring branch numbers and position information of branches in the target area, establishing an empty sales parameter table, and inserting the branch numbers into the sales parameter table;
determining a connection diagram according to the area label and the position information, and establishing a connection relation between each node in the connection diagram and each sales parameter table; the connection graph is an undirected weightless graph, the node values are branch numbers, and the edge values and the distances between the branches have a mapping relation.
3. The method of claim 1, wherein the step of obtaining sales data of each branch in real time based on the sales parameter table, counting the sales data in each sales parameter table, and obtaining a blockchain indexed by regional labels comprises:
the generated sales parameter table is sent to a corresponding branch store, and the sales time, the sales products and the sales profits of the branch store are recorded in real time based on the sales parameter table; wherein the sales revenue is determined only by the sales product; the sales profits corresponding to different sales products are determined values preset by a head office;
traversing all sales time items in the sales parameter table by a preset time starting point and a preset time period, and extracting data items of the sales time contained in the time period;
calculating the number of the extracted data items, packing the extracted data items and inserting a time tag generated by a time starting point and a time period when the number of the data items reaches a preset number threshold value to obtain a data block, and connecting the obtained data block with a stored block data chain; updating the time starting point according to the time information of the last data item;
and when the number of the data items is less than a preset number threshold value, prolonging the time period.
4. A method according to claim 3, wherein when the number of data items reaches a predetermined number threshold, the extracted data items are packed and inserted with time tags generated by a time start and a time period to obtain data blocks, and the step of linking the obtained data blocks to the existing blockchain comprises:
when the number of the data items reaches a preset number threshold, reading a time starting point and a time period, and generating a time tag;
reading a chain tail time point corresponding to a data block at the tail of a block data chain, and judging whether the chain tail time point exceeds the tail time of the time tag or not;
when the time point of the chain tail exceeds the tail of the time tag, packing the extracted data items, inserting the time tag to obtain a data block, updating the block data chain according to the head time of the time tag in the obtained data block, and taking the tail time in the time tag as a new time starting point;
and when the chain tail time point does not exceed the tail part of the time tag, reading the chain tail time point as a new time starting point.
5. The method of claim 1, wherein the step of obtaining a push resource, modifying the blockchain according to the push resource, and using the modified blockchain as the financial data comprises:
inquiring the push resources and feedback information of the area according to the area label; the feedback information comprises access number, praise number, collection number and forwarding number;
inputting the feedback information into a preset linear calculation formula, and calculating the effective number of the pushed resources;
reading a flow conversion rate obtained by pre-statistics, and calculating a theoretical passenger flow according to the flow conversion rate and the effective number;
reading a connection diagram, and distributing theoretical passenger flow volume according to the theoretical passenger flow proportion at each branch shop of the connection diagram based on the theoretical passenger flow proportion to obtain the theoretical passenger flow volume of each branch shop;
acquiring the passenger flow time distribution characteristics of each branch store, and distributing the theoretical passenger flow volume of each branch store according to the passenger flow time distribution characteristics to obtain the theoretical passenger flow volume of each branch store in each time period; the passenger flow time distribution characteristics are used for representing the passenger flow distribution characteristics of any branch store in different time periods within one time period;
and correcting each data block in the block data chain according to the theoretical passenger flow of each branch store in each time period, and taking the corrected block data chain as financial data.
6. The method of claim 4, wherein when the number of data items reaches a predetermined number threshold, the step of packing the extracted data items and inserting a time tag generated by a time start point and a time period into the data items to obtain a data block further comprises:
when the number of the data items reaches a preset number threshold value, sequentially inquiring branch stores corresponding to the data items to generate a data distribution array; subscripts of the data distribution array are position information of branch stores, and values of the data distribution array are data numbers;
comparing the data distribution array with a data distribution array corresponding to a previous data block, and calculating the data change rate of each branch;
and (4) counting the data change rate of each branch store to obtain the change curve of each branch store.
7. A system for generating financial data based on a blockchain technique, the system comprising:
the template generation module is used for acquiring the regional labels of all branch stores and establishing a mutually connected sales parameter table corresponding to all branch stores according to the regional labels; the sales parameter table includes a sales time item, a sales product item, and a sales income item;
the data statistics module is used for acquiring sales data of each branch in real time based on the sales parameter table, and performing statistics on the sales data in each sales parameter table to obtain a block data chain with the regional labels as indexes;
and the data correction module is used for acquiring the pushing resources, correcting the block data chain according to the pushing resources and taking the corrected block data chain as financial data.
8. A system for generating financial data according to claim 7 in which the template generation module comprises:
the area label query unit is used for reading a target area of the pushed resource and acquiring an area label of the target area; the target area of the pushed resource is a preset value;
the empty table establishing unit is used for acquiring branch numbers and position information of all branches in the target area, establishing an empty sales parameter table and inserting the branch numbers into the sales parameter table;
the connection relation establishing unit is used for determining a connection diagram according to the area label and the position information and establishing the connection relation between each node in the connection diagram and each sales parameter table; the connection graph is an undirected weightless graph, the node values are branch numbers, and the edge values and the distances between the branches have a mapping relation.
9. A system for generating financial data according to the block chain technique of claim 7 wherein the data statistics module comprises:
the sales data acquisition unit is used for sending the generated sales parameter table to the corresponding branch store and recording the sales time, the sales products and the sales profits of the branch store in real time based on the sales parameter table; wherein the sales revenue is determined only by the sales product; the sales profits corresponding to different sales products are determined values preset by a head office;
the data extraction unit is used for traversing all the sales time items in the sales parameter table by a preset time starting point and a preset time period, and extracting the data items of which the sales time is contained in the time period;
the data packing unit is used for calculating the number of the extracted data items, packing the extracted data items and inserting the time tags generated by the time starting points and the time periods when the number of the data items reaches a preset number threshold value to obtain data blocks, and connecting the obtained data blocks with the stored block data chains; updating the time starting point according to the time information of the last data item;
and the time updating unit is used for prolonging the time period when the number of the data items is smaller than a preset number threshold value.
10. A system for generating financial data according to claim 9 in which the data packing unit comprises:
the tag generation subunit is used for reading a time starting point and a time period and generating a time tag when the number of the data items reaches a preset number threshold;
the time ratio subunit is used for reading a chain tail time point corresponding to a data block at the tail of the block data chain and judging whether the chain tail time point exceeds the tail time of the time tag or not;
the block updating subunit is configured to, when the time point of the tail of the chain exceeds the tail of the time tag, pack the extracted data item, insert the time tag to obtain a data block, update the block data chain according to the head time of the time tag in the obtained data block, and use the tail time in the time tag as a new time starting point;
and the block inserting subunit is used for reading the chain tail time point as a new time starting point when the chain tail time point does not exceed the tail part of the time tag.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10207958A (en) * | 1997-01-28 | 1998-08-07 | Tsubasa Syst Kk | Sales analysis device and program recording medium |
| CN107423998A (en) * | 2017-03-27 | 2017-12-01 | 北京二零四八科技有限公司 | A kind of visualization sales data management method and system based on SaaS platforms |
| CN108734028A (en) * | 2018-05-24 | 2018-11-02 | 中国联合网络通信集团有限公司 | Data managing method, block chain node based on block chain and storage medium |
| CN112862556A (en) * | 2019-11-27 | 2021-05-28 | 杭州妈妈去哪儿网络科技有限公司 | Management system and management method applied to mother-infant chain store |
| CN114022201A (en) * | 2021-11-01 | 2022-02-08 | 广州玺明机械科技有限公司 | Milk tea sales data statistics device based on high in clouds |
-
2022
- 2022-07-15 CN CN202210828685.3A patent/CN115099921A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10207958A (en) * | 1997-01-28 | 1998-08-07 | Tsubasa Syst Kk | Sales analysis device and program recording medium |
| CN107423998A (en) * | 2017-03-27 | 2017-12-01 | 北京二零四八科技有限公司 | A kind of visualization sales data management method and system based on SaaS platforms |
| CN108734028A (en) * | 2018-05-24 | 2018-11-02 | 中国联合网络通信集团有限公司 | Data managing method, block chain node based on block chain and storage medium |
| CN112862556A (en) * | 2019-11-27 | 2021-05-28 | 杭州妈妈去哪儿网络科技有限公司 | Management system and management method applied to mother-infant chain store |
| CN114022201A (en) * | 2021-11-01 | 2022-02-08 | 广州玺明机械科技有限公司 | Milk tea sales data statistics device based on high in clouds |
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