CN107862412A - A kind of data processing method and device - Google Patents
A kind of data processing method and device Download PDFInfo
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Abstract
The invention discloses a kind of data processing method and device, methods described includes：Using Kettle instruments, business datum is extracted from ERP operation systems；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and obtain data results；The data results are shown by SpotView.It can be seen that the present invention realizes the processing to the business datum in ERP operation systems.
Description
Technical field
The present invention relates to technical field of data processing, more particularly to a kind of data processing method and device.
Background technology
Traditional retail business, kept accounts by manual form, the end of month uniformly collects to general headquarters again carries out special messenger's accounting, and information passes
Pass slowly, yield poor results, it is not prompt enough for the control of shops's situation.Demand based on market development, retail ERP system meet the tendency of and
It is raw.It is well known that existing retail ERP operation systems, only trade company provide the form displaying of available data resource, not
It is related to the depth excavation to existing big data resource.But with the arrival of big data information age, the complexity of market environment
The polytropy of diversity and customer demand, enterprise want that just business must be found from existing data message immediately following the trend in epoch
Machine, seek new foothold.
Therefore, it is badly in need of a kind of scheme that can be handled the business datum in ERP operation systems.
The content of the invention
In order to solve the above technical problems, the embodiments of the invention provide a kind of data processing method and device, technical scheme
It is as follows：
A kind of data processing method, including：
Using Kettle instruments, business datum is extracted from ERP operation systems；
Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and
Obtain data results；
The data results are shown by SpotView.
Preferably, the data results are shown, including：
By way of chart, indicator or text control, the data results are shown.
Preferably, it is characterised in that also include：
The page for showing the data results is embedded into business intelligence framework.
Preferably, using data mining algorithm corresponding with the type of the business datum, the business datum is carried out
Analysis, and before obtaining data results, in addition to：
The business datum is changed, to eliminate the exception or error information in the business datum, obtains target
Business datum；
The target service data are loaded onto data warehouse；
Correspondingly, using data mining algorithm corresponding with the type of the business datum, the business datum is carried out
Analysis, and data results are obtained, including：
Using data mining algorithm corresponding with the type of the target service data, the target service data are carried out
Analysis, and obtain data results.
Preferably, in addition to：
Judge whether to receive the access request of user, the access request is used to access the data results, institute
Stating access request includes the displaying type of the data results；
If so, in response to the access request, meet the data results for showing type to user displaying.
A kind of data processing equipment, including：
Extracting unit, for utilizing Kettle instruments, business datum is extracted from ERP operation systems；
Data analysis unit, for using data mining algorithm corresponding with the type of the business datum, to the industry
Business data are analyzed, and obtain data results；
First display unit, for being shown the data results by SpotView.
Preferably, the first display unit, including：
First displaying subelement, for by way of chart, indicator or text control, showing the data analysis knot
Fruit.
Preferably, in addition to：
Embedded unit, for the page for showing the data results to be embedded into business intelligence framework.
Preferably, in addition to：
Converting unit, for using data mining algorithm corresponding with the type of the business datum, to the business number
According to being analyzed, and before obtaining data results, the business datum is changed, to eliminate in the business datum
Exception or error information, obtain target service data；
The target service data are loaded onto data warehouse；
Correspondingly, data analysis unit, including：
Data analysis subelement, it is right for using data mining algorithm corresponding with the type of the target service data
The target service data are analyzed, and obtain data results.
Preferably, in addition to：
Judging unit, for judging whether to receive the access request of user, the access request is used to access the number
According to analysis result, the access request includes the displaying type of the data results；
Second display unit, for when the judging unit determine receive the access request of user when, in response to described
Access request, the data results of the displaying type are met to user displaying.
Technical scheme provided in an embodiment of the present invention, using Kettle instruments, business number is extracted from ERP operation systems
According to；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and is counted
According to analysis result；The data results are shown.It can be seen that the present invention is realized to the business in ERP operation systems
The processing of data.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, without having to pay creative labor, may be used also
To obtain other accompanying drawings according to these accompanying drawings.
A kind of a kind of schematic flow sheet for data processing method that Fig. 1 is provided by the embodiment of the present invention；
A kind of another schematic flow sheet for data processing method that Fig. 2 is provided by the embodiment of the present invention；
A kind of a kind of structural representation for data processing equipment that Fig. 3 is provided by the embodiment of the present invention；
A kind of another structural representation for data processing equipment that Fig. 4 is provided by the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.Based on this
Embodiment in invention, the every other reality that those of ordinary skill in the art are obtained under the premise of creative work is not made
Example is applied, belongs to the scope of protection of the invention.
Referring to Fig. 1, Fig. 1 is a kind of a kind of implementation process figure of data processing method provided in an embodiment of the present invention, institute
The method of stating includes：
Step S101, using Kettle instruments, business datum is extracted from ERP operation systems；
Kettle is the one kind for the ETL instruments increased income, and java writes, and can be transported on Window, Linux or Unix system
OK, data pick-up efficient stable.
The business datum extracted from ERP operation systems can be Customer Information, membership information, the supplier letter of trade company
The initial data such as breath, inventory information or transaction journal.
Step S102, using data mining algorithm corresponding with the type of the business datum, the business datum is entered
Row analysis, and obtain data results；
Data mining algorithm refers to the related information in excavation mass data, specifically, can be to the business datum of user
User is clustered using data mining algorithm, user is divided into 4 classifications, and the transaction data of user can also be utilized
Analysis is predicted to the transaction data in following shop, this namely valuable data result.
Data mining algorithm includes forecast analysis and cluster analysis two parts, wherein, forecast analysis has used mixed linear
Regression algorithm, cluster analysis have used k-means clustering algorithms.
Mixed linear regression algorithm：
The purpose of linear regression is the linear relationship between output vector Y and input feature vector X to be obtained, and obtains linear regression
Coefficient θ, that is, Y=X θ.Wherein Y is prediction result, and its dimension is m × 1, and X is model data, i.e. historical data, its dimension
For m × n, and θ dimension is n × 1.M representative sample numbers, the dimension of n representative sample features.
In order to try to achieve optimal linear regression coeffficient θ, a loss function J (θ) is defined, by minimizing loss function,
To try to achieve optimal linear regression coeffficient θ, in order to prevent over-fitting, we have done regularization to common linear regression, with one
Individual weight parameter ρ balances the proportion of regularization, forms a brand-new loss function J (θ) as follows：
Wherein α is regularization hyper parameter, and ρ is norm weight hyper parameter.
Loss function is optimized by reference axis descent method, obtains optimal linear regression coeffficient θ, and then obtain prediction result
Y。
K-means clustering algorithms：
An element set D is given, that is, extracts the data set after over cleaning, wherein each element has n
Observable attribute, D is divided into k subset using certain algorithm, it is desirable to which distinctiveness ratio to the greatest extent may be used between the element of each intra-subset
Can be low, and the element distinctiveness ratio of different subsets is as high as possible.Wherein, each subset is a cluster.
The calculating process of k averages (k-means) algorithm is very directly perceived：
1st, k element is taken at random from D, the respective center as k cluster.
2nd, remaining element is calculated respectively to the distinctiveness ratio at k cluster center, incorporates these elements into distinctiveness ratio respectively most
Low cluster.
3rd, according to cluster result, the respective center of k cluster is recalculated, computational methods are to take all elements in cluster each to tie up
The arithmetic average of degree.
4th, whole elements in D are clustered again according to new center.
5th, the 4th step is repeated, until cluster result no longer changes.
6th, result is exported.
Step S103, the data results are shown by SpotView.
, it is necessary to which data results are showed into user after data results are obtained.
Specifically, data results can be shown using SpotView, it is advanced due to containing in SpotView
Instrument board form and abundant VCL, data results can be shown in the form of rich and varied,
It is different from conventional simple exhibiting data reporting form, in the present embodiment the displaying of data results will using bar chart, line chart,
The different forms such as pie chart, mulberries figure, indicator are showed.Meanwhile SpotView is powerful and exploitation is quick, Neng Goushi
Maximum value is now obtained at lower cost.
In technical scheme provided in an embodiment of the present invention, using Kettle instruments, business number is extracted from ERP operation systems
According to；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and is counted
According to analysis result；The data results are shown.It can be seen that the present invention is realized to the business in ERP operation systems
The processing of data.
Referring to Fig. 2, Fig. 2 is a kind of another implementation process figure of data processing method provided in an embodiment of the present invention,
Methods described includes：
Step S201, using Kettle instruments, business datum is extracted from ERP operation systems；
Kettle is the one kind for the ETL instruments increased income, and java writes, and can be transported on Window, Linux or Unix system
OK, data pick-up efficient stable.
The business datum extracted from ERP operation systems can be Customer Information, membership information, the supplier letter of trade company
The initial data such as breath, inventory information or transaction journal.
Step S202, the business datum is changed, to eliminate the exception or error information in the business datum,
Obtain target service data；
Step S203, the target service data are loaded onto data warehouse；
Step S201 and step S203 be accomplished that extraction (extract) to business datum, conversion (transform) and
Load (load).
In general, some redundancies are included in original business datum, or even include the information of presence mistake, in order to
The accuracy of data results is improved, generally use ETL technologies are cleaned to data.In addition, when data volume is every 2~3 years
Between will be doubled and redoubled, these data contain huge commercial value, and enterprise is of interest generally only accounts in total amount of data
2%~4% or so.Therefore, enterprise does not still utilize already present data resource maximumlly, so that wasting more
Time and fund, also lose formulate key business decision-making best opportunity.Then, how enterprise is by various technological means,
And information, knowledge are converted the data into, into the main bottleneck for improving its core competitiveness.And ETL is then main one
Individual technological means.In the present invention, initial data is extracted and cleaned using Kettle instruments, the process of data pick-up is sealed
Component one by one is dressed up, by invocation component, to realize the extraction of data.
Step S204, using data mining algorithm corresponding with the type of the target service data, to the target industry
Business data are analyzed, and obtain data results；
Data mining algorithm refers to the related information in excavation mass data, specifically, can be to the business datum of user
User is clustered using data mining algorithm, user is divided into 4 classifications, and the transaction data of user can also be utilized
Analysis is predicted to the transaction data in following shop, this namely valuable data result.
Data mining algorithm includes forecast analysis and cluster analysis two parts, wherein, forecast analysis has used mixed linear
Regression algorithm, cluster analysis have used k-means clustering algorithms.
Mixed linear regression algorithm：
The purpose of linear regression is the linear relationship between output vector Y and input feature vector X to be obtained, and obtains linear regression
Coefficient θ, that is, Y=X θ.Wherein Y is prediction result, and its dimension is m × 1, and X is model data, i.e. historical data, its dimension
For m × n, and θ dimension is n × 1.M representative sample numbers, the dimension of n representative sample features.
In order to try to achieve optimal linear regression coeffficient θ, a loss function J (θ) is defined, by minimizing loss function,
To try to achieve optimal linear regression coeffficient θ, in order to prevent over-fitting, we have done regularization to common linear regression, with one
Individual weight parameter ρ balances the proportion of regularization, forms a brand-new loss function J (θ) as follows：
Wherein α is regularization hyper parameter, and ρ is norm weight hyper parameter.
Loss function is optimized by reference axis descent method, obtains optimal linear regression coeffficient θ, and then obtain prediction result
Y。
K-means clustering algorithms：
An element set D is given, that is, extracts the data set after over cleaning, wherein each element has n
Observable attribute, D is divided into k subset using certain algorithm, it is desirable to which distinctiveness ratio to the greatest extent may be used between the element of each intra-subset
Can be low, and the element distinctiveness ratio of different subsets is as high as possible.Wherein, each subset is a cluster.
The calculating process of k averages (k-means) algorithm is very directly perceived：
1st, k element is taken at random from D, the respective center as k cluster.
2nd, remaining element is calculated respectively to the distinctiveness ratio at k cluster center, incorporates these elements into distinctiveness ratio respectively most
Low cluster.
3rd, according to cluster result, the respective center of k cluster is recalculated, computational methods are to take all elements in cluster each to tie up
The arithmetic average of degree.
4th, whole elements in D are clustered again according to new center.
5th, the 4th step is repeated, until cluster result no longer changes.
6th, result is exported.
Step S205, the data results are shown by SpotView；
, it is necessary to which data results are showed into user after data results are obtained.
Specifically, data results can be shown using SpotView, it is advanced due to containing in SpotView
Instrument board form and abundant VCL, data results can be shown in the form of rich and varied,
It is different from conventional simple exhibiting data reporting form, in the present embodiment the displaying of data results will using bar chart, line chart,
The different forms such as pie chart, mulberries figure, indicator are showed.Meanwhile SpotView is powerful and exploitation is quick, Neng Goushi
Maximum value is now obtained at lower cost.
Step S206, the page for showing the data results is embedded into business intelligence framework；
After the page of data results is imported in business intelligence system framework, redirecting for interface is completed, when user steps on
Land business intelligence system, you can inquiry data results page presentation, the display platform of whole system include pc ends and movement
Client, i.e. trade company can inquire about data results in web page or mobile phone terminal, convenient and swift, even if travelling outside,
The state of development of company can be controlled at any time, and make a policy in time.Data evil spirit is incorporated in business intelligence system framework simultaneously
Side, can preferably lift Consumer's Experience.
Step S207, judge whether to receive the access request of user, if so, performing step S208；
The access request is used to access the data results, and the access request includes the data results
Displaying type；
Step S208, in response to the access request, the data analysis of the displaying type is met to user displaying
As a result.
Can there is a variety of exhibition method, user can select data according to demand used by no data results
The exhibition method of analysis result, the flexibility of data display is added, improves Consumer's Experience.
In technical scheme provided in an embodiment of the present invention, using Kettle instruments, business number is extracted from ERP operation systems
According to；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and is counted
According to analysis result；The data results are shown.It can be seen that the present invention is realized to the business in ERP operation systems
The processing of data.
Referring to Fig. 3, Fig. 3 is a kind of structural representation of data processing equipment provided in an embodiment of the present invention, the device
The implementation procedure of method, the device include in embodiment corresponding to the course of work reference picture 1 of each unit in structural representation：
Extracting unit 310, for utilizing Kettle instruments, business datum is extracted from ERP operation systems；
Data analysis unit 320, for using data mining algorithm corresponding with the type of the business datum, to described
Business datum is analyzed, and obtains data results；
First display unit 330, for being shown the data results by SpotView.
In technical scheme provided in an embodiment of the present invention, using Kettle instruments, business number is extracted from ERP operation systems
According to；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and is counted
According to analysis result；The data results are shown.It can be seen that the present invention is realized to the business in ERP operation systems
The processing of data.
Referring to Fig. 4, Fig. 4 is a kind of structural representation of data processing equipment provided in an embodiment of the present invention, the device
The implementation procedure of method, the device include in embodiment corresponding to the course of work reference picture 1 of each unit in structural representation：
Extracting unit 410, for utilizing Kettle instruments, business datum is extracted from ERP operation systems；
Converting unit 420, for using data mining algorithm corresponding with the type of the business datum, to the business
Data are analyzed, and before obtaining data results, the business datum are changed, to eliminate the business datum
In exception or error information, obtain target service data；
Data analysis subelement 430, for using data mining algorithm corresponding with the type of the target service data,
The target service data are analyzed, and obtain data results；
First displaying subelement 440, for by way of chart, indicator or text control, showing the data point
Analyse result；
Embedded unit 450, for the page for showing the data results to be embedded into business intelligence framework；
Judging unit 460, for judging whether to receive the access request of user, the access request is used to accessing described
Data results, the access request include the displaying type of the data results；
Second display unit 470, for when the judging unit determine receive the access request of user when, in response to institute
Access request is stated, the data results of the displaying type are met to user displaying.
In technical scheme provided in an embodiment of the present invention, using Kettle instruments, business number is extracted from ERP operation systems
According to；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and is counted
According to analysis result；The data results are shown.It can be seen that the present invention is realized to the business in ERP operation systems
The processing of data.
Term " first ", " second ", " the 3rd " " in description and claims of this specification and above-mentioned accompanying drawing
The (if present)s such as four " are for distinguishing similar object, without for describing specific order or precedence.It should manage
The data that solution so uses can exchange in the appropriate case, so as to embodiments of the invention described herein for example can with except
Order beyond those for illustrating or describing herein is implemented.In addition, term " comprising " and " having " and theirs is any
Deformation, it is intended that cover it is non-exclusive include, for example, containing the process of series of steps or unit, method, system, production
Product or equipment are not necessarily limited to those steps clearly listed or unit, but may include not list clearly or for this
The intrinsic other steps of a little process, method, product or equipment or unit.
For device or system embodiment, because it essentially corresponds to embodiment of the method, so related part referring to
The part explanation of embodiment of the method.Device or system embodiment described above is only schematical, wherein described
The unit illustrated as separating component can be or may not be physically separate, and the part shown as unit can be with
It is or may not be physical location, you can with positioned at a place, or can also be distributed on multiple NEs.Can
To select some or all of module therein to realize the purpose of this embodiment scheme according to the actual needs.This area is common
Technical staff is without creative efforts, you can to understand and implement.
In several embodiments provided by the present invention, it should be understood that disclosed system, apparatus and method, do not having
Have more than in the spirit and scope of the present invention, can realize in other way.Current embodiment is a kind of exemplary
Example, should not be taken as limiting, given particular content should in no way limit the purpose of the present invention.For example, the unit or
The division of subelement, only a kind of division of logic function, can there are other dividing mode, such as multiple lists when actually realizing
First or multiple subelements combine.In addition, multiple units can with or component can combine or be desirably integrated into another and be
System, or some features can be ignored, or not perform.
In addition, the schematic diagram of described system, apparatus and method and different embodiments, without departing from the scope of the present invention
It is interior, it can combine or integrate with other systems, module, techniques or methods.Another, shown or discussed mutual coupling
Close or direct-coupling or communication connection can be by some interfaces, the INDIRECT COUPLING or communication connection of device or unit, can be with
It is electrical, mechanical or other forms.
Described above is only the embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
- A kind of 1. data processing method, it is characterised in that including：Using Kettle instruments, business datum is extracted from ERP operation systems；Using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, and obtains Data results；The data results are shown by SpotView.
- 2. according to the method for claim 1, it is characterised in that the data results are shown, including：By way of chart, indicator or text control, the data results are shown.
- 3. according to the method for claim 2, it is characterised in that also include：The page for showing the data results is embedded into business intelligence framework.
- 4. according to the method for claim 1, it is characterised in that dug using data corresponding with the type of the business datum Algorithm is dug, the business datum is analyzed, and before obtaining data results, in addition to：The business datum is changed, to eliminate the exception or error information in the business datum, obtains target service Data；The target service data are loaded onto data warehouse；Correspondingly, using data mining algorithm corresponding with the type of the business datum, the business datum is analyzed, And data results are obtained, including：Using data mining algorithm corresponding with the type of the target service data, the target service data are divided Analysis, and obtain data results.
- 5. according to the method for claim 4, it is characterised in that also include：Judge whether to receive the access request of user, the access request is used to access the data results, the visit Ask that request includes the displaying type of the data results；If so, in response to the access request, meet the data results for showing type to user displaying.
- A kind of 6. data processing equipment, it is characterised in that including：Extracting unit, for utilizing Kettle instruments, business datum is extracted from ERP operation systems；Data analysis unit, for using data mining algorithm corresponding with the type of the business datum, to the business number According to being analyzed, and obtain data results；First display unit, for being shown the data results by SpotView.
- 7. device according to claim 6, it is characterised in that the first display unit, including：First displaying subelement, for by way of chart, indicator or text control, showing the data results.
- 8. device according to claim 7, it is characterised in that also include：Embedded unit, for the page for showing the data results to be embedded into business intelligence framework.
- 9. device according to claim 6, it is characterised in that also include：Converting unit, for using data mining algorithm corresponding with the type of the business datum, the business datum is entered Row analysis, and before obtaining data results, the business datum is changed, it is different in the business datum to eliminate Normal or error information, obtains target service data；The target service data are loaded onto data warehouse；Correspondingly, data analysis unit, including：Data analysis subelement, for using data mining algorithm corresponding with the type of the target service data, to described Target service data are analyzed, and obtain data results.
- 10. device according to claim 9, it is characterised in that also include：Judging unit, for judging whether to receive the access request of user, the access request is used to access the data point Result is analysed, the access request includes the displaying type of the data results；Second display unit, for when the judging unit determine receive the access request of user when, in response to the access Request, the data results of the displaying type are met to user displaying.
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| CN201711128827.0A CN107862412A (en) | 2017-11-15 | 2017-11-15 | A kind of data processing method and device |
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| CN201711128827.0A CN107862412A (en) | 2017-11-15 | 2017-11-15 | A kind of data processing method and device |
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