CN102521706A - KPI data analysis method and device for the same - Google Patents
KPI data analysis method and device for the same Download PDFInfo
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- CN102521706A CN102521706A CN2011104257942A CN201110425794A CN102521706A CN 102521706 A CN102521706 A CN 102521706A CN 2011104257942 A CN2011104257942 A CN 2011104257942A CN 201110425794 A CN201110425794 A CN 201110425794A CN 102521706 A CN102521706 A CN 102521706A
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Abstract
The invention discloses a KPI (Key Performance Indicator) data analysis method and a device for the same. The method comprises the following steps of: orderly obtaining the KPI data corresponding to the current business subject from a source database for each business subject to be analyzed; modeling the KPI data by using an analysis model matched with the KPI data, and computing the modeled KPI data through an algorithm matched with the KPI data to obtain a performance indicator; and feeding back the performance indicator when the performance indicator satisfies a predetermined condition. According to the technical scheme provided by the invention, by fully considering the generalization characteristics of 3G (The 3rd Generation Telecommunication) new services, deeply analyzing the network KPI, saving energy and tapping potential, effects of improving the utilization rate of network resource, promoting the client satisfaction and bringing higher service added value are all realized.
Description
Technical field
The present invention relates to the communications field, in particular to a kind of analytical approach and device of KPI data.
Background technology
In recent years, along with the rapid expanding of telecommunications industry, cause portfolio to heighten at aspects such as user, business and networks; In a period of time, remain the main source of income and benefit in view of existing communication network; The further investigation communication network, the phase-split network performance improves resource utilization; Wanting benefit to existing investment, is that each big operator keeps service and professional leading inevitable choice.For tackling competitive environment complicated and changeable, Carrier Requirements progressively changes to the management of refining, and needs further to improve the benefit of network, improves the perception to turn of the market and demand.
The existing analytical approach of operator is to be the network analysis system of core with the report database, is traditional, original and inflexible, can not satisfy the needs of the macro-management of decision-making level, effectively the network analysis work of each aspect of accurate guidance.At present general is the data warehouse OLAP on line analytical processing of typical application with the Customer Relation Management (CRM) in the world; With the database OLTP issued transaction technology [6-9] that with telecom business support system (OSS) is typical application; Also rest on certain technology of employing; From the problem of certain certain service layer of application point research, for example: adopt the association analysis technology, customer churn pattern in the research 3G network; Can't be to comprising key performance indicators (the Key Performance Indicator of key business figureofmerit, quality of service index, performance index etc.; Abbreviate KPI as) carry out comprehensive analysis, reach target to network performance and service quality comprehensive assessment, satisfy the needs that the service operation situation is weighed by operator.One comprehensive, solves the overall plan of carrier network performance comprehensively, also is in the theoretic discussion stage at present.
Summary of the invention
To the problem that can't carry out analysis-by-synthesis in the correlation technique to the KPI data that comprise key business figureofmerit, quality of service index, performance index etc., the invention provides a kind of analytical approach and device of KPI data, to address the above problem at least.
A kind of analytical approach of KPI data is provided according to an aspect of the present invention.
Analytical approach according to KPI data of the present invention comprises: successively to each professional theme to be analyzed, from source database, obtain the corresponding KPI data of current business theme; Use the analytical model that is complementary with the KPI data to the KPI data modeling, and the KPI data of the algorithm that is complementary of use and KPI data after to modeling are calculated and are obtained performance index; When performance index satisfy predetermined condition, the feedback performance index.
In said method, before from source database, obtaining the corresponding KPI data of current business theme, also comprise: the source data in the source database is divided into groups, obtain many group source datas; Carry out association analysis for each group source data, the matching probability size of obtaining according to association analysis sorts to the pairing professional theme of each group source data; Confirm professional theme to be analyzed according to ranking results.
In said method, from source database, obtain the corresponding key performance indicators KPI data of current business theme and comprise: from the metadata rule base, obtain this business theme corresponding dimension and KPI index according to the current business theme; From source database, obtain the KPI data corresponding according to dimension and KPI index with the current business theme.
In said method, use with analytical model that the KPI data are complementary the KPI data modeling is comprised: the analytical model to the KPI data are corresponding is analyzed, and the matching probability size of obtaining according to analysis sorts to the analytical model of correspondence; Choose first term analytical model after the ordering to the KPI data modeling.
In said method, the KPI data after using the algorithm that is complementary with the KPI data to modeling are calculated and obtained performance index and comprise: the analytical model corresponding algorithm is analyzed, and the matching probability size of obtaining according to analysis sorts to corresponding algorithm; Choosing first term algorithm after the ordering calculates the KPI data and obtains performance index.
In said method, when performance index satisfied predetermined condition, the feedback performance index comprised: performance index and pre-set threshold are compared; If performance index are greater than or equal to threshold value, feedback performance index then.
In said method; When performance index do not satisfy predetermined condition; Also comprise: use the new analytical model that is complementary with the KPI data again to the KPI data modeling, and the new algorithm that is complementary of use and KPI data calculates and obtains new performance index again to the KPI data after the modeling.
A kind of analytical equipment of KPI data is provided according to a further aspect in the invention.
Analytical equipment according to KPI data of the present invention comprises: first acquisition module, be used for being directed against successively each professional theme to be analyzed, and from source database, obtain the corresponding KPI data of current business theme; MBM is used to use the analytical model that is complementary with the KPI data to the KPI data modeling; Computing module, the KPI data after being used to use the algorithm that is complementary with the KPI data to modeling are calculated and are obtained performance index; Feedback module is used for when performance index satisfy predetermined condition, the feedback performance index.
In said apparatus, also comprise: second acquisition module, be used for the source data of source database is divided into groups, obtain many group source datas; Order module is used for carrying out association analysis for each group source data, and the matching probability size of obtaining according to association analysis sorts to the pairing professional theme of each group source data; Determination module is used for confirming professional theme to be analyzed according to ranking results.
In said apparatus, above-mentioned first acquisition module comprises: first acquiring unit is used for obtaining this business theme corresponding dimension and KPI index according to the current business theme from the metadata rule base; Second acquisition unit is used for obtaining the KPI data corresponding with the current business theme according to dimension and KPI index from source database.
In said apparatus, above-mentioned MBM comprises: first sequencing unit, be used for the corresponding analytical model of KPI data is analyzed, and the matching probability size of obtaining according to analysis sorts to the analytical model of correspondence; Modeling unit is used to choose first term analytical model after the ordering to the KPI data modeling.
In said apparatus, the aforementioned calculation module comprises: second sequencing unit, be used for the analytical model corresponding algorithm is analyzed, and the matching probability size of obtaining according to analysis sorts to corresponding algorithm; Computing unit is used to choose first term algorithm after the ordering and the KPI data are calculated is obtained performance index.
In said apparatus, above-mentioned feedback module comprises: comparing unit is used for performance index and pre-set threshold are compared; Feedback unit is used for when performance index are greater than or equal to threshold value, the feedback performance index.
Through the present invention, adopt to be directed against each professional theme to be analyzed successively, from source database, obtain the corresponding KPI data of current business theme; Use the analytical model that is complementary with the KPI data to the KPI data modeling, and the KPI data of the algorithm that is complementary of use and KPI data after to modeling are calculated and are obtained performance index; When performance index satisfied predetermined condition, the feedback performance index had solved the problem that can't carry out analysis-by-synthesis in the correlation technique to the KPI data that comprise key business figureofmerit, quality of service index, performance index etc.; And then the popularization characteristics of comprehensive consideration 3G new business have been reached; Through analysing in depth network key property performance indicators, go deep into energy-conservation taping the latent power, improve network resource utilization; Improve customer satisfaction, bring higher professional value-added effect.
Description of drawings
Accompanying drawing described herein is used to provide further understanding of the present invention, constitutes the application's a part, and illustrative examples of the present invention and explanation thereof are used to explain the present invention, do not constitute improper qualification of the present invention.In the accompanying drawings:
Fig. 1 is the analytical approach process flow diagram according to the KPI data of the embodiment of the invention;
Fig. 2 is a method flow diagram of from source database, gathering the KPI data according to the preferred embodiment of the invention;
Fig. 3 is a KPI method for monitoring performance process flow diagram according to the preferred embodiment of the invention;
Fig. 4 is the structured flowchart according to the analytical equipment of the KPI data of the embodiment of the invention; And
Fig. 5 is the structured flowchart of the analytical equipment of KPI data according to the preferred embodiment of the invention.
Embodiment
Hereinafter will and combine embodiment to specify the present invention with reference to accompanying drawing.Need to prove that under the situation of not conflicting, embodiment and the characteristic among the embodiment among the application can make up each other.
Fig. 1 is the analytical approach process flow diagram according to the KPI data of the embodiment of the invention.As shown in Figure 1, this method mainly comprises following processing:
Step S102:, from source database, obtain the corresponding KPI data of current business theme successively to each professional theme to be analyzed;
Above-mentioned professional theme can be the sign that needs the business of monitoring, for example, and short message service, Ring Back Tone service, MMS etc.
Step S104: use the analytical model that is complementary with the KPI data to the KPI data modeling, and the KPI data of the algorithm that is complementary of use and KPI data after to modeling are calculated and obtained performance index;
Step S106: when performance index satisfy predetermined condition, the feedback performance index.
In the correlation technique, can't carry out analysis-by-synthesis to the KPI data that comprise key business figureofmerit, quality of service index, performance index etc.Adopt method as shown in Figure 1; From source database, obtain the KPI data corresponding according to current professional theme with the current business theme; From model bank, choose the analytical model that is complementary most with the KPI data to the KPI data modeling, and from algorithms library, choose the algorithm that is complementary most with the KPI data KPI data after to modeling and calculate and obtain performance index; When above-mentioned performance index satisfy predetermined condition, performance index are fed back to the user, be convenient to the user and adjust.Solve the problem that to carry out analysis-by-synthesis in the correlation technique to the KPI data that comprise key business figureofmerit, quality of service index, performance index etc. thus, realized assisting operator to realize the effect that improves network resource utilization, improves customer satisfaction.
Need to prove; The present invention designs and has realized a kind of telecommunication intelligent data analysing method based on KPI; Through introducing data warehouse and multidimensional data analysis technology; Designed a key business processing model bank and an algorithmic tool storehouse simultaneously, and on this basis, realized telecommunication intelligent data analysing method based on KPI.In the operation process, the KPI that network performance is exerted a decisive influence defines, screens, gathers and monitors, and sets up a network performance analysis model based on KPI, is based on the crucial operation data of existing real network, analyses in depth network operation situation.
Preferably, before execution in step S102, need to confirm above-mentioned professional theme to be analyzed, can comprise following processing:
(1) source data in the source database is divided into groups, obtain many group source datas;
(2) carry out association analysis for each group source data, the matching probability size of obtaining according to association analysis sorts to the pairing professional theme of each group source data;
(3) confirm professional theme to be analyzed according to ranking results.
Preferably, above-mentioned steps S102 may further include following processing:
(1) from the metadata rule base, obtains this business theme corresponding dimension and KPI index according to the current business theme;
(2) from source database, obtain the KPI data corresponding according to dimension and KPI index with the current business theme.
Need to prove; The present invention is according to telecommunications industry specification; Need design a KPI system metadata rule base in advance; Start with from the dimension and the KPI index of KPI theme, take into full account characteristics such as correlativity professional between the KPI index and flow process property, from source database, obtain the KPI data corresponding with the current business theme.
Below in conjunction with Fig. 2 above-mentioned preferred implementation process is done further description.
Fig. 2 is a method flow diagram of from source database, gathering the KPI data according to the preferred embodiment of the invention.As shown in Figure 2, this KPI data acquisition comprises the selection of business diagnosis theme and the collection of KPI index and dimension data.Last process will be selected corresponding theme from the business diagnosis storehouse, back one process then will be gathered from professional source database and extracted corresponding KPI data.The KPI data acquisition is under the guidance of related business process model; To related subject; Utilize and extract the conversion loading appliance,, in the professional source database of existing operation, extract, be loaded into the Network performance monitoring database and prepare to analyze the KPI data that influence network performance.This method can comprise following treatment step:
Step S202: at first the service source database is analyzed, therefrom found relevant business diagnosis theme source data;
Step S204: analyze the theme selector switch professional theme source data is done association analysis,, pick out suitable analysis topic list LS (j) according to the matching probability size that association analysis is obtained; J={0,1,2; ..., and all weights in the sequence are mapped to 0, in the 1} territory;
Step S206: the business diagnosis theme, choose the first term LS (0) that analyzes theme selector switch output topic list among the step S04, as current optimal professional theme;
Need to prove; Generally, with the first term LS (0) of professional topic list as current optimal professional theme, still; Feed back to the user after analyzing to the first term LS (0) of current business topic list; And under the situation that the user can't adjust, then do not need again this first term LS (0) to be analyzed, but continue second LS (1) analyzed.The rest may be inferred, feeds back to the user if be directed against after LS (1) analyzes, and under the situation that the user can't adjust, then do not need this first term LS (1) to be analyzed again, but continue the 3rd LS (2) analyzed.
Step S208: from the metadata rule base, obtain the dimension and the KPI index of current business theme, wherein, above-mentioned dimension and KPI index request are accurate to the fine granularity that meets business need;
Step S210: from professional source database, import corresponding KPI data, accomplish the collection of KPI data.
Preferably, in step S104, use the said analytical model that is complementary with said KPI data can comprise following processing to said KPI data modeling:
(1) the corresponding analytical model of KPI data is analyzed, the matching probability size of obtaining according to analysis sorts to the analytical model of correspondence;
(2) choose first term analytical model after the ordering to the KPI data modeling;
(3) the analytical model corresponding algorithm is analyzed, the matching probability size of obtaining according to analysis sorts to corresponding algorithm;
(4) choosing first term algorithm after the ordering calculates the KPI data and obtains performance index.
Need to prove; The present invention is based on the angle of intelligence and multianalysis, to the requirement of KPI index according to aggregate analysis in to the KPI data analysis process; Based on the XML technology; Set up corresponding analytical model, realized striding manufacturer and professional inherent analyzing and processing ability, and can realize selection automatically the KPI model.In addition; The invention provides an integrated algorithm that satisfies the network intelligence data processing; Merged and comprised time series, association analysis, cluster analysis is at interior data analysing method; Particularly crucial is to handle the singularity aspect treatment effeciency time and memory source to integrated service, and these algorithms have been carried out corresponding improvement.
In preferred implementation process, can the passing threshold manner of comparison determine whether the performance index that get access to user feedback, for example:
(1) performance index and pre-set threshold are compared;
(2) if performance index are greater than or equal to threshold value, feedback performance index then.
In preferred implementation process; Step S106 can also comprise following processing: if performance index are less than threshold value; Then use the new analytical model that is complementary with the KPI data again to the KPI data modeling, and the new algorithm that is complementary of use and KPI data calculate and obtain new performance index again to the KPI data after the modeling.
Need to prove that above-mentioned threshold value is to confirm according to the median of the KPI data of above-mentioned collection, that is, the performance index that are greater than or equal to KPI data median are fed back to the user; To performance index less than KPI data median, then need reselect new analytical model and new algorithm is analyzed the KPI data of above-mentioned collection, obtain new performance index.
Below in conjunction with Fig. 3 above-mentioned preferred implementation is done further description.
Fig. 3 is a KPI method for monitoring performance process flow diagram according to the preferred embodiment of the invention.As shown in Figure 3; On the basis that the KPI data of above-mentioned collection are analyzed, from corresponding analytical model storehouse and algorithms library, select only analytical model and algorithm the KPI data are analyzed reckoning; Form online accent excellent with analysis report present to the user; So that the user is according to the performance of system, circulation feedback is adjusted relevant part, realizes the optimization of system performance.The treatment scheme of this method mainly comprises following treatment step:
Step S302:, from model bank, select the corresponding analytical model that is fit to the KPI data through using KPI Model Selection device;
Step S304:KPI algorithm selector switch is analyzed the algorithm in the model, and algorithm in the algorithms library is screened, and according to matching probability order from big to small, lists candidate algorithm CA (j); J={0,1,2; ..., and the weights in the sequence are mapped to 0, in the 1} territory;
Step S306: from step S304 candidate algorithm CA (j), pick out first term CA (0), as current optimal application algorithm, with the present analysis algorithm of doing the KPI data;
Step S308: with the performance index data after the KPI analyzing and processing, compare with the performance threshold K (i) of relevant KPI index in the system, wherein, i=index (certain KPI index);
Step S310: judge whether the performance index data after the KPI analyzing and processing reach the requirement of KPI metrics-thresholds;
Step S312: if do not reach the requirement of KPI metrics-thresholds, then, generate KPI and transfer excellent report, turn back to step S302, reselect model and algorithm not through the KPI monitoring;
Step S314: if reach the KPI metrics-thresholds,, combine, generate the KPI analysis result information and offer the user with related subject in the system with the performance index data after the KPI analyzing and processing.
Need to prove; Above-mentioned flow process mainly is according to the professional actual conditions of operation; Under the analysis theme of KPI instructs,, and data are sent in the system the gathering of the operation KPI data in the communication network, extract function; Store, analyze according to theme, the purpose of the variation tendency of the comprehensive observation of realization key index data, prediction etc.
Fig. 4 is the structured flowchart according to the analytical equipment of the KPI data of the embodiment of the invention.As shown in Figure 4, the analytical equipment of these KPI data mainly comprises: first acquisition module 10, be used for being directed against successively each professional theme to be analyzed, and from source database, obtain the corresponding KPI data of current business theme; MBM 20 is used to use the analytical model that is complementary with the KPI data to the KPI data modeling; Computing module 30, the KPI data after being used to use the algorithm that is complementary with the KPI data to modeling are calculated and are obtained performance index; Feedback module 40 is used for when performance index satisfy predetermined condition, the feedback performance index.
Adopt device as shown in Figure 4, first acquisition module 10 obtains the corresponding KPI data of current business theme successively to each professional theme to be analyzed from source database; MBM 20 uses the analytical model that is complementary with the KPI data to the KPI data modeling; KPI data after computing module 30 uses the algorithm that is complementary with the KPI data to MBM 20 modelings are calculated and are obtained performance index; When performance index satisfy predetermined condition, feedback module 40 feedback performance indexs.Thereby solved the problem that to carry out analysis-by-synthesis in the correlation technique to the KPI data that comprise key business figureofmerit, quality of service index, performance index etc., realized assisting operator to realize the effect that improves network resource utilization, improves customer satisfaction.
Preferably, as shown in Figure 5, said apparatus can also comprise: second acquisition module 50, be used for the source data of source database is divided into groups, and obtain many group source datas; Order module 60 is used for carrying out association analysis for each group source data, and the matching probability size of obtaining according to association analysis sorts to the pairing professional theme of each group source data; Determination module 70 is used for confirming professional theme to be analyzed according to ranking results.
Preferably, above-mentioned first acquisition module 10 can comprise: first acquiring unit 100 is used for obtaining this business theme corresponding dimension and KPI index according to the current business theme from the metadata rule base; Second acquisition unit 102 is used for obtaining the KPI data corresponding with the current business theme according to dimension and KPI index from source database.
Preferably, above-mentioned MBM 20 can comprise: first sequencing unit 200, be used for the corresponding analytical model of KPI data is analyzed, and the matching probability size of obtaining according to analysis sorts to the analytical model of correspondence; Modeling unit 202 is used to choose first term analytical model after the ordering to the KPI data modeling.
Preferably, aforementioned calculation module 30 can comprise: second sequencing unit 300, be used for the analytical model corresponding algorithm is analyzed, and the matching probability size of obtaining according to analysis sorts to corresponding algorithm; Computing unit 302 is used to choose first term algorithm after the ordering and the KPI data are calculated is obtained performance index.
Preferably, above-mentioned feedback module 40 can comprise: comparing unit 400 is used for performance index and pre-set threshold are compared; Feedback unit 402 is used for when performance index are greater than or equal to threshold value, the feedback performance index.
Need to prove that the preferred implementation that each unit in the said apparatus in each module and each module mutually combines specifically can repeat no more referring to the description of Fig. 1 to Fig. 3 here.
From above description; Can find out that the present invention has realized following technique effect: realize energy-conservation taping the latent power based on existing operation business datum, considered the popularization characteristics of 3G new business comprehensively; Merging existing optimum data analytical technology means analyzes the KPI data that network performance exerts a decisive influence; And set up network KPI performance analysis models the KPI data in the operation process are screened, monitored and gather, set up a network performance analysis model based on key index in the reality operation, realize analysing in depth the network operation; Improve network resource utilization, the target of improving customer satisfaction.
Obviously, it is apparent to those skilled in the art that above-mentioned each module of the present invention or each step can realize with the general calculation device; They can concentrate on the single calculation element; Perhaps be distributed on the network that a plurality of calculation element forms, alternatively, they can be realized with the executable program code of calculation element; Thereby; Can they be stored in the memory storage and carry out, and in some cases, can carry out step shown or that describe with the order that is different from here by calculation element; Perhaps they are made into each integrated circuit modules respectively, perhaps a plurality of modules in them or step are made into the single integrated circuit module and realize.Like this, the present invention is not restricted to any specific hardware and software combination.
The above is merely the preferred embodiments of the present invention, is not limited to the present invention, and for a person skilled in the art, the present invention can have various changes and variation.All within spirit of the present invention and principle, any modification of being done, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (13)
1. the analytical approach of key performance indicators KPI data is characterized in that, comprising:
To each professional theme to be analyzed, from source database, obtain the corresponding KPI data of current business theme successively;
Use the analytical model that is complementary with said KPI data to said KPI data modeling, and the said KPI data of the algorithm that is complementary of use and said KPI data after to modeling are calculated and are obtained performance index;
When said performance index satisfy predetermined condition, feed back said performance index.
2. method according to claim 1 is characterized in that, before from said source database, obtaining the corresponding said KPI data of current business theme, also comprises:
Source data in the said source database is divided into groups, obtain many group source datas;
Carry out association analysis for each group source data, the matching probability size of obtaining according to association analysis sorts to the pairing professional theme of each group source data;
Confirm said professional theme to be analyzed according to ranking results.
3. method according to claim 1 is characterized in that, from said source database, obtains the corresponding key performance indicators KPI data of current business theme and comprises:
From the metadata rule base, obtain this business theme corresponding dimension and KPI index according to said current business theme;
From said source database, obtain the said KPI data corresponding according to said dimension and said KPI index with said current business theme.
4. method according to claim 1 is characterized in that, uses the said analytical model that is complementary with said KPI data that said KPI data modeling is comprised:
Analytical model to said KPI data are corresponding is analyzed, and the matching probability size of obtaining according to analysis sorts to the analytical model of said correspondence;
Choose first term analytical model after the ordering to said KPI data modeling.
5. method according to claim 1 is characterized in that, the said KPI data after using the algorithm that is complementary with said KPI data to modeling are calculated and obtained said performance index and comprise:
Said analytical model corresponding algorithm is analyzed, and the matching probability size of obtaining according to analysis sorts to said corresponding algorithm;
Choosing first term algorithm after the ordering calculates said KPI data and obtains said performance index.
6. method according to claim 1 is characterized in that, when said performance index satisfy predetermined condition, feeds back said performance index and comprises:
Said performance index and pre-set threshold are compared;
If said performance index are greater than or equal to said threshold value, then feed back said performance index.
7. according to each described method in the claim 1 to 6, it is characterized in that, when said performance index do not satisfy predetermined condition, also comprise:
Use the new analytical model that is complementary with said KPI data again to said KPI data modeling, and the new algorithm that is complementary of use and said KPI data calculate and obtain new performance index again to the said KPI data after the modeling.
8. the analytical equipment of key performance indicators KPI data is characterized in that, comprising:
First acquisition module is used for being directed against successively each professional theme to be analyzed, from source database, obtains the corresponding KPI data of current business theme;
MBM is used to use the analytical model that is complementary with said KPI data to said KPI data modeling;
Computing module, the said KPI data after being used to use the algorithm that is complementary with said KPI data to modeling are calculated and are obtained performance index;
Feedback module is used for when said performance index satisfy predetermined condition, feeding back said performance index.
9. device according to claim 8 is characterized in that, said device also comprises:
Second acquisition module is used for the source data of said source database is divided into groups, and obtains many group source datas;
Order module is used for carrying out association analysis for each group source data, and the matching probability size of obtaining according to association analysis sorts to the pairing professional theme of each group source data;
Determination module is used for confirming said professional theme to be analyzed according to ranking results.
10. device according to claim 8 is characterized in that, said first acquisition module comprises:
First acquiring unit is used for obtaining this business theme corresponding dimension and KPI index according to said current business theme from the metadata rule base;
Second acquisition unit is used for obtaining the said KPI data corresponding with said current business theme according to said dimension and said KPI index from said source database.
11. device according to claim 8 is characterized in that, said MBM comprises:
First sequencing unit is used for the corresponding analytical model of said KPI data is analyzed, and the matching probability size of obtaining according to analysis sorts to the analytical model of said correspondence;
Modeling unit is used to choose first term analytical model after the ordering to said KPI data modeling.
12. device according to claim 8 is characterized in that, said computing module comprises:
Second sequencing unit is used for said analytical model corresponding algorithm is analyzed, and the matching probability size of obtaining according to analysis sorts to said corresponding algorithm;
Computing unit is used to choose first term algorithm after the ordering and said KPI data are calculated is obtained said performance index.
13. device according to claim 8 is characterized in that, said feedback module comprises:
Comparing unit is used for said performance index and pre-set threshold are compared;
Feedback unit is used for when said performance index are greater than or equal to said threshold value, feeding back said performance index.
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| CN113469547A (en) * | 2021-07-13 | 2021-10-01 | 上海齐屹信息科技有限公司 | Intelligent KPI (Key Performance indicator) assessment and reward distribution system and method based on big data |
| CN116579671A (en) * | 2023-07-14 | 2023-08-11 | 新亿成科技(江苏)有限公司 | Performance assessment method, system, terminal and storage medium for automatically matching indexes |
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Application publication date: 20120627 |