WO2012088760A1

WO2012088760A1 - Data analysis device and method therefor based on analysis factors calculated on demand

Info

Publication number: WO2012088760A1
Application number: PCT/CN2011/002166
Authority: WO
Inventors: 陆堃彪; 何发亮; 梁海琦
Original assignee: 中国银联股份有限公司
Priority date: 2010-12-27
Filing date: 2011-12-23
Publication date: 2012-07-05
Also published as: CN102541811A; CN102541811B

Abstract

The present invention provides a data analysis device and method therefor based analysis factors calculated on demand. The data analysis device based on analysis factors calculated on demand comprises a configuration module, a data extraction module, an analysis factor calculation module, a data analysis processing module, and an analysis result output module. The data analysis device and method based on analysis factors calculated on demand disclosed in the present invention can easily expand an analysis factor and an analysis rule to ensure real-timeliness and accuracy, and can calculate an analysis factor on demand, thereby significantly enhancing the work efficiency and performance of the system.

Description

Description Data analysis device and method based on on-demand calculation factor

The present invention relates to a data analysis apparatus and method, and more particularly to a data analysis apparatus and method based on an on-demand calculation factor. Background technique

At present, with the increasing demand for information data processing and the variety of business types in different fields, data analysis based on analysis factors (ie, the various analysis elements used in data analysis) is becoming more and more important.

In general, the basic principles of the existing analysis factor-based data analysis method and apparatus are as follows: extracting raw data from a data source; constructing based on the original data and based on pre-defined rules (the rules are predetermined based on each specific application) a data model and simultaneously calculating individual analysis factors; constructing an analysis model based on the analysis factor and according to a predetermined rule (the rule is predetermined based on each application requirement) and calculating an analysis result; transmitting the analysis result to the application The server is used for subsequent processing.

However, as the types of services become more and more abundant, more and more analysis factors need to be used in data analysis, and data analysis rules based on specific application requirements are also changing more frequently, which requires frequent analysis of factors and data. Analyze rules for dynamic adjustments. Therefore, the above prior art solutions have the following problems: When it is necessary to expand the analysis factor (that is, when the data analysis rule needs to use a new analysis factor), if the analysis factor is not within the preset analysis factor, it cannot be based on If the pre-set analysis factor is obtained through a simple operation, the system code must be manually modified, so that the system's real-time requirements cannot be met. At the same time, this method takes more time, so the maintenance cost increases, and the process is cumbersome and easy. Errors, which reduce the efficiency and performance of the entire system; in addition, when the data analysis rules need to be changed, the system code must also be manually modified;

In addition, in the existing technical solutions, the complete analysis factors that may participate in the analysis calculation are usually listed in the system design and development stage, and in the actual use stage, the calculation rules are

Confirmation Then calculate all molecular factors and then construct an analytical model. However, based on the change in demand, the two parts of the real-score factor (that is, the actual participation in the analysis calculations will change dynamically according to the demand). Therefore, the above prior art solutions also have the following problems: The process of calculating all the analysis factors consumes a large amount of calculation time and system resources (that is, the calculation of a part of the analysis factors is useless), thereby significantly reducing the overall performance of the system.

Therefore, there is a need to provide an analysis factor-based data analysis apparatus and method that is easy to expand, ensures real-time and accuracy, and can calculate an analysis factor as needed to improve system efficiency and performance. Summary of the invention

In order to solve the deficiencies of the above prior art solutions, the present invention proposes a data analysis apparatus and method based on an analysis factor of on-demand calculation.

The object of the invention is achieved by the following technical solutions:

A data analysis apparatus based on an analysis factor of an on-demand calculation, wherein the data analysis apparatus based on an analysis factor of on-demand calculation comprises:

a configuration module, the configuration module is configured to set the configuration file according to a user input; a data extraction module, the data extraction module is configured to extract the original data from a data source; an analysis factor calculation module, the analysis factor calculation module Generating a data model based on the raw data and the configuration file and calculating a value of at least one analysis factor actually required;

a data analysis processing module, configured to construct an analysis model based on the value of the at least one analysis factor actually required and the configuration file, and calculate an analysis result;

An analysis result output module, wherein the analysis result output module is configured to transmit the analysis result to an application server.

In the solution disclosed above, preferably, the analysis factor calculation module further includes:

An analysis factor selection unit, wherein the analysis factor screening unit is configured to analyze the data The processing module sends an analysis factor statistics request, and transmits response information from the data analysis processing module to the computing unit;

a calculating unit, configured to construct a data model according to the response information and calculate a value of at least one analysis factor actually needed;

The response information includes a list of identifiers of the analysis factors actually required.

In the solution disclosed above, preferably, the analysis model is based on at least one analysis rule instance of the analysis rule template.

In the solution disclosed above, preferably, the data analysis processing module further includes:

An analysis rule template setting unit, configured to set at least one analysis rule template according to a user input;

An analysis rule instance generating unit, configured to generate at least one analysis rule instance according to the configuration file;

An analysis factor recording unit, configured to record an identifier of an analysis factor used by the generated at least one analysis rule instance;

An analysis calculation unit is configured to construct an analysis model and calculate an analysis result according to the generated at least one analysis rule instance.

In the solution disclosed above, preferably, the configuration file includes configuration data of an analysis factor, and the configuration data of the analysis factor defines a mapping relationship between the original data and the analysis factor.

In the solution disclosed above, preferably, the configuration data of the analysis factor is in the form of an extensible markup language.

In the solution disclosed above, preferably, the configuration data of the analysis factor includes at least one of the following elements: an original data identifier, a statistical metric, a statistical dimension, a statistical manner, and a filter condition.

In the solution disclosed above, preferably, the configuration file includes configuration data of an analysis rule, and the configuration data of the analysis rule defines a mapping relationship between the analysis factor and the analysis model.

In the solution disclosed above, preferably, the configuration data of the analysis rule is in the form of an extensible markup language.

In the solution disclosed above, preferably, the analysis factor calculation module passes the analysis The factor data interface communicates the calculated value of the at least one analysis factor actually required to the data analysis processing module.

In the solution disclosed above, preferably, the analysis factor data interface adopts a hash map table (MAP) structure, wherein an output of the analysis factor data interface is a key-value of the calculated analysis factor (EY-VALUE) ).

In the solution disclosed above, preferably, the at least one analysis factor actually required is an element in the data model.

In the solution disclosed above, preferably, the analysis factor calculation module further includes an analysis factor statistical unit configured to perform statistical calculation on the value of the at least one analysis factor actually required.

In the solution disclosed above, preferably, the analysis factor statistical unit includes at least one of the following statistical operation modes: summation (S blue), minimum value (Min), and maximum value (Max).

In the solution disclosed above, preferably, the analysis model is a collection of logical decision rules associated with each other.

The object of the invention is also achieved by the following technical solutions:

A data analysis method based on an analysis factor of an on-demand calculation, the data analysis method based on an on-demand calculation factor includes the following steps:

( A1 ) Set the configuration file according to the user's input:

(A2) extracting raw data from a data source;

(A3) constructing a data model based on the original data and the configuration file and calculating a value of at least one analysis factor actually required;

(A4) constructing an analysis model based on the value of the at least one analysis factor actually required and the configuration file and calculating an analysis result;

(A5) transmitting the analysis result to the application server.

In the solution disclosed above, preferably, the step (A3) further comprises:

(B 1 ) acquiring information indicating an identifier of the at least one analysis factor actually required, and constructing a data model based on the information and calculating a value of at least one analysis factor actually required; The information includes a list of identifiers of the analysis factors that are actually required.

In the solution disclosed above, preferably, the step (A4) further comprises: (C1) setting at least one analysis rule template according to a user input;

(C2) generating at least one analysis rule instance according to the configuration file;

(C3) recording an identification of an analysis factor used by the generated at least one analysis rule instance (ie, maintaining a range of analysis factors actually involved in the data analysis calculation);

(C4) constructing an analysis model based on the generated at least one analysis rule instance and calculating the analysis result.

In the solution disclosed above, preferably, the configuration data of the analysis factor includes at least one of the following elements: an original data identifier, a statistical metric, a statistical dimension, a statistical manner: and a filter condition.

In the solution disclosed above, preferably, the method passes the calculated value of the at least one analysis factor actually required by the analysis factor data interface.

In the solution disclosed above, preferably, the analysis factor data interface adopts a hash map table (MAP) structure, wherein an output of the analysis factor data interface is a key-value of the calculated analysis factor (EY-VALUE) )„

In the solution disclosed above, preferably, the step (B1) further comprises: (Dl) Performing a statistical calculation on the value of at least one analysis factor required for the purchase. In the solution disclosed above, preferably, the statistical calculation includes at least one of the following statistical operation modes: summation (Sum), minimum value (Min), and maximum value (Max).

The data analysis apparatus and method based on the on-demand calculation analysis factor disclosed by the invention have the following advantages: easy to expand analysis factors and analysis rules; can ensure real-time and accuracy; can calculate analysis factors as needed, thereby significantly improving System efficiency and performance. DRAWINGS

The technical features and advantages of the present invention will be better understood by those skilled in the art from the drawings, wherein:

1 is a structural diagram of a data analysis device for calculating an analysis factor based on an on-demand according to an embodiment of the present invention;

2 is a flow chart of a data analysis method based on an on-demand calculation of an analysis factor, in accordance with an embodiment of the present invention;

1 is a block diagram of a data analysis apparatus that calculates an analysis factor based on an on-demand according to an embodiment of the present invention. As shown in FIG. 1, the data analysis apparatus 1 based on the on-demand calculation analysis factor disclosed in the present invention is used for data analysis based on original data and analysis rules in a configuration file. As shown in FIG. 1, the data analysis device 1 includes a configuration module 2, a data extraction module 3, an analysis factor calculation module 4, a data analysis processing module 5, and an analysis result output module 6. The configuration module 2 is configured to set the configuration file according to an input of a user. The data extraction module 3 is configured to extract the raw data from a data source. The analysis factor calculation module 4 is configured to construct a data model based on the original data and the configuration file and calculate a value of at least one analysis factor that is actually needed. The data analysis processing module 5 is configured to construct an analysis model and calculate an analysis result based on the value of the at least one analysis factor actually needed and the configuration file. The analysis result output module 6 is configured to transmit the analysis result to an application server (for example, security Detection server).

As shown in FIG. 1, preferably, in the data analysis apparatus based on the on-demand calculation analysis factor disclosed in the present invention, the analysis factor calculation module further includes a calculation unit 7 and an analysis factor screening unit 8. The analysis factor screening unit 8 is configured to send an analysis factor statistics request to the data analysis processing module 5, and transmit the response information from the data analysis processing module 5 to the calculation unit 7. The calculation unit 7 is configured to construct a data model based on the response information and calculate a value of the at least one analysis factor that is actually required. Preferably, the response information includes a list of identifications of the analysis factors actually required.

Preferably, in the data analysis apparatus based on the on-demand calculation analysis factor disclosed in the present invention, the analysis model is based on at least one analysis rule instance of the analysis rule template. The analysis rule template refers to some general data analysis rules, which are only used as the basis for the extension of the analysis rule instance, and do not participate in the calculation process of the data analysis; the analysis rule instance refers to the analysis rule that actually participates in the data analysis. It can be extended based on the analysis rule template, ie different analysis rule instances can be generated in real time based on different needs.

As shown in FIG. 1 , in the data analysis apparatus based on the on-demand calculation analysis factor disclosed in the present invention, the data analysis processing module 5 further includes an analysis rule template setting unit 9 and an analysis rule instance generation unit 10, The factor recording unit 11 and the analysis unit 12 are analyzed. The analysis rule template setting unit 9 is configured to set at least one analysis rule template according to the input of the user. The analysis rule instance generating unit 10 is configured to generate at least one analysis rule instance according to the configuration file. The analysis factor recording unit 11 is configured to record an identification of an analysis factor used by the generated at least one analysis rule instance (i.e., to maintain a range of analysis factors actually participating in the data analysis calculation). The analysis calculation unit 12 is configured to construct an analysis model and calculate an analysis result according to the generated at least one analysis rule instance.

Illustratively, in the data analysis apparatus based on the on-demand calculation analysis factor disclosed by the present invention, the basic process of calculating the analysis factor by the calculation unit 7 is as follows: based on the received response information (the response information includes an actual a list of identifiers of the required analysis factors, excluding the analysis factors not covered by the at least one analysis rule instance; calculating the analysis factors involved in the at least one analysis rule instance based on the received response information In (that is, the classification of the actual required analysis factors, batch calculation, thus avoiding multiple analysis rules The public numerators used by the examples are repeated multiple times); based on the received response information, the personalized analysis factors used in each of the at least one analysis rule instance are separately calculated (ie, non-publicly used Analysis factor).

Preferably, in the data analysis apparatus disclosed in the present invention, the configuration file includes configuration data of an analysis factor, and the configuration data of the analysis factor defines a mapping relationship (ie, a logical relationship) between the original data and the analysis factor.

Preferably, the configuration data of the analysis factor is in the form of XML (Extensible Markup Language).

Preferably, the configuration data of the analysis factor includes at least one of the following elements: an original data identifier, a statistical metric, a statistical dimension, a statistical mode, and a filter condition.

Preferably, in the data analysis apparatus disclosed by the present invention, the configuration file includes configuration data of an analysis rule, and the configuration data of the analysis rule defines a mapping relationship between an analysis factor and an analysis model (ie, a business rule) (ie, a logical relationship). ).

Preferably, the configuration data of the analysis rule is in the form of XML (Extensible Markup Language).

Preferably, in the data analysis apparatus disclosed by the present invention, the analysis factor calculation module 4 transmits the calculated value of the actually required at least one analysis factor to the data analysis processing module by analyzing the factor data interface. 5. Preferably, the analysis factor data interface adopts a hash map (MAP) structure, that is, the output of the analysis factor data interface is a key-value (KEY-VALUE) of the calculated analysis factor.

Preferably, in the data analysis apparatus disclosed in the present invention, the at least one analysis factor actually required is an element in the data model (i.e., a business model).

Preferably, in the data analysis device disclosed by the present invention, the analysis factor calculation module 4 further includes an analysis factor statistics unit for performing statistical calculation on the value of the at least one analysis factor actually required. The analysis factor statistical unit may include at least one of the following statistical operation modes: summation (Sum), minimum value (Min), maximum value (Max) _0, preferably, in the data analysis apparatus disclosed in the present invention. The analysis model is a collection of interrelated logical decision rules.

As shown in FIG. 1, the basic working principle of the data analysis device disclosed by the present invention is exemplarily The configuration is as follows: setting a configuration file by the configuration module 2 according to user input; the data extraction module 3 extracts original data from a data source; the analysis factor calculation module 4 is based on configuration data of an analysis factor in the configuration file (ie, user a set business model) and the raw data constructing a data model and calculating a value of at least one analysis factor actually needed; the analysis factor calculation module 4 calculating at least one of the actual needs calculated by analyzing the factor data interface The value of the analysis factor is passed to the data analysis processing module 5; the data analysis processing module 5 is based on the configuration data of the analysis rule in the profile (ie, the analysis rule of the rule engine set by the user) and the actual need The value of at least one analysis factor constructs an analysis model and calculates an analysis result; the analysis result output module 6 transmits the analysis result to an application server.

Illustratively, the data analysis apparatus disclosed herein is applied to security information interactions, such as financial risk management systems. The raw data may be, for example, transaction attribute information, merchant information, or the like. The application server may be a security detection server.

2 is a flow chart of a data analysis method based on an on-demand calculated analysis factor, in accordance with an embodiment of the present invention. As shown in FIG. 2, the data analysis method based on the dynamically expandable analysis factor disclosed in the present invention includes the following steps: (A1) setting a configuration file according to a user input: (A2) extracting original data from a data source; (A3) Constructing a data model based on the raw data and the configuration file and calculating a value of at least one analysis factor actually required; (A4) constructing an analysis based on the value of the at least one analysis factor actually required and the configuration file The model calculates the analysis result; (A5) transmits the analysis result to an application server (for example, a security detection server).

Preferably, in the data analysis method based on the on-demand calculation analysis factor disclosed in the present invention, the step (A3) further comprises: (B1) acquiring information indicating the identifier of the at least one analysis factor actually required. And constructing a data model based on the information and calculating a value of the at least one analysis factor that is actually needed. Preferably, the information includes a list of identifications of the analysis factors actually required.

Preferably, in the data analysis method based on the on-demand calculation analysis factor disclosed in the present invention, the analysis model is based on at least one analysis rule instance of the analysis rule template. The analysis rule template refers to some general data analysis rules, which are only used as analysis rules. The basis of the extension is not involved in the calculation process of data analysis; the analysis rule instance refers to an analysis rule that actually participates in data analysis, which can be extended based on the analysis rule template, that is, different generations can be generated based on different needs. An example of an analysis rule.

Preferably, in the data analysis method based on the on-demand calculation analysis factor disclosed in the present invention, the step (A4) further includes: (C1) setting at least one analysis rule template according to a user input; (C2) according to the The configuration file generates at least one analysis rule instance; (C3) records an identifier of an analysis factor used by the generated at least one analysis rule instance (ie, maintains a range of analysis factors actually involved in the data analysis calculation); (C4) generates according to the At least one analysis rule instance constructs an analysis model and calculates the analysis results.

Illustratively, in the data analysis method based on the on-demand calculation analysis factor disclosed in the present invention, the basic process of calculating the analysis factor is as follows: based on the acquired information (the information includes the identification of the actual required analysis factor a list), excluding an analysis factor that is not involved in the at least one analysis rule instance; calculating, based on the acquired information, an analysis factor involved in the at least one analysis rule instance (ie, combining the actual required analysis factors) Classification, multiple calculations; based on the acquired information, individualized analysis factors (ie, non-publicly used analysis factors) used in each of the at least one analysis rule instance are separately calculated.

Preferably, in the data analysis method disclosed in the present invention, the configuration file includes configuration data of an analysis factor, and the configuration data of the analysis factor defines a mapping relationship (ie, a logical relationship) between the original data and the analysis factor.

Preferably, in the data analysis method disclosed by the present invention, the configuration file includes configuration data of an analysis rule, and the configuration data of the analysis rule defines a mapping relationship between an analysis factor and an analysis model (ie, a business rule) (ie, a logical relationship). ).

Preferably, the configuration data of the analysis rule is an XML (Extensible Markup Language) form Style.

Preferably, in the data analysis method disclosed in the present invention, the calculated value of the at least one analysis factor actually required is transmitted through the analysis factor data interface. Preferably, the analysis factor data interface adopts a hash map table (MAP) structure, that is, the output of the analysis factor data interface is a key-value (KEY-VALUE) of the calculated analysis factor.

Preferably, in the data analysis method disclosed in the present invention, the at least one analysis factor actually required is an element in the data model (i.e., a business model).

Preferably, in the data analysis method disclosed in the present invention, the step (B1) further comprises: (D1) performing a statistical calculation on the value of the actually required at least one analysis factor. The statistical calculation includes at least one of the following statistical operation modes: summation (Sum), taking a minimum value (Min), and taking a maximum value (Max).

Preferably, in the data analysis method disclosed in the present invention, the analysis model is a set of logical decision rules associated with each other.

Although the invention has been described in terms of the preferred embodiments described above, the form of implementation is not limited to the embodiments described above. It will be appreciated that various changes and modifications can be made to the present invention without departing from the spirit and scope of the invention.

Claims

A data analysis apparatus based on an analysis factor of an on-demand calculation, wherein the data analysis apparatus based on an on-demand calculation factor comprises:

a configuration module, the configuration module is configured to set the configuration file according to a user input; a data extraction module, the data extraction module is configured to extract the original data from a data source; an analysis factor calculation module, the analysis factor calculation module Generating a number weighting model based on the raw data and the configuration file and calculating a value of at least one analysis factor actually required;

An analysis result output module, wherein the analysis result output module is configured to transmit the analysis result to an application server. Book

2. The data analysis apparatus according to claim 1, wherein the analysis factor calculation module further comprises: the management module sends an analysis factor statistical request, and the analysis processing is performed from the data. The response information of the module is transmitted to the computing unit;

a calculating unit, configured to construct a data model according to the response information and calculate a value of the at least one analysis factor that is actually needed;

The data analysis apparatus based on an analysis factor of an on-demand calculation according to claim 2, wherein the analysis model is based on at least one analysis rule instance of the analysis rule template. Characterized in that the data analysis unit is molded; including: , ,

An analysis rule template setting unit, configured to set at least one analysis rule template according to a user input; An analysis rule instance generating unit, configured to generate at least one analysis rule instance according to the configuration file;

5. The data analysis apparatus according to claim 4, wherein the configuration file includes configuration data of an analysis factor, and configuration data of the analysis factor defines original data and an analysis factor. Mapping relations.

6. The data analysis apparatus based on an analysis factor of an on-demand calculation according to claim 5, wherein the configuration data of the analysis factor is in the form of an extensible markup language.

7. The data analysis apparatus according to claim 6, wherein the configuration data of the analysis factor comprises at least one of the following elements: an original data identifier, a statistical metric, a statistical dimension, Statistical methods and filter conditions.

8. The data analysis apparatus according to claim 7, wherein the configuration file includes configuration data of an analysis rule, and configuration data of the analysis rule defines an analysis factor and an analysis model. Mapping relations.

9. The data analysis apparatus based on an analysis factor of an on-demand calculation according to claim 8, wherein the configuration data of the analysis rule is in the form of an extensible markup language.

10. The data analysis apparatus based on an on-demand calculation factor according to claim 9, wherein the analysis factor calculation module calculates the at least one analysis factor actually required by analyzing the factor data interface. The value is passed to the data analysis processing module.

11. The data analysis apparatus based on an on-demand calculation analysis factor according to claim 10, wherein the analysis factor data interface uses a hash map table (MAP) structure, wherein the analysis factor data interface The output is the calculated key-value of the analysis factor

( KEY- VALUE ).

12. The data analysis apparatus based on an on-demand calculation factor according to claim 11, wherein the at least one analysis factor actually required is in the data model Elements.

13. The data analysis apparatus according to claim 12, wherein the analysis factor calculation module further comprises an analysis factor statistical unit, wherein the analysis factor statistical unit is configured to use the actual The value of at least one of the required analysis factors is statistically calculated.

14. The data analysis based on the dynamically expandable analysis factor according to claim 13, at least one of: summation (Sum), taking a minimum value (Min), and taking a maximum value (Max). Apparatus, characterized in that the analysis module is a set of logical decision rules associated with each other

16. A data analysis method based on an analysis factor of an on-demand calculation, the data analysis method based on an on-demand calculation factor comprising the following steps:

( A1 ) Set the configuration file according to the user's input:

(A2) extracting raw data from a data source;

(A5) transmitting the analysis result to the application server.

The data analysis method of the analysis factor based on the on-demand calculation according to claim 16, wherein the step (A3) further comprises:

(B 1 ) acquiring information indicating an identifier of the at least one analysis factor actually required, and constructing a data model based on the information and calculating a value of the at least one analysis factor actually required;

Wherein the information includes a list of identifiers of the analysis factors actually required.

18. The data analysis method based on an analysis factor of an on-demand calculation according to claim 17, wherein the analysis model is based on at least one analysis rule instance of an analysis rule template.

19. The data analysis side of the analysis factor based on on-demand calculation according to claim 18. The method, wherein the step (A4) further comprises:

(C1) setting at least one analysis rule template according to user input;

20. The data analysis method based on an on-demand calculation factor according to claim 19, wherein the configuration file includes configuration data of an analysis factor, and configuration data of the analysis factor defines original data and an analysis factor. Mapping relations.

21. The data analysis method based on an analysis factor of an on-demand calculation according to claim 20, wherein the configuration data of the analysis factor is in the form of an extensible markup language.

22. The data analysis method of an analysis factor based on an on-demand calculation according to claim 21, wherein the configuration data of the analysis factor comprises at least one of the following elements: an original data identifier, a statistical metric, a statistical dimension, Statistical methods and filter conditions.

The data analysis method of an analysis factor based on an on-demand calculation according to claim 22, wherein the configuration file includes configuration data of an analysis rule, and configuration data of the analysis rule defines an analysis factor and an analysis model. Mapping relations.

24. The data analysis method based on an on-demand calculation factor according to claim 23, wherein the configuration data of the analysis rule is in the form of an extensible markup language.

25. The data analysis method based on an on-demand calculation factor according to claim 24, wherein the method passes the calculated value of the at least one analysis factor actually required by the analysis factor data interface.

26. The data analysis method based on an on-demand calculation factor according to claim 25, wherein the analysis factor data interface adopts a hash map table (MAP) structure, wherein an output of the analysis factor data interface Is the calculated key-value of the analysis factor

( KEY-VALUE ).

27. The data analysis method based on an on-demand calculation factor according to claim 26, wherein the at least one analysis factor actually required is in the data model Elements.

The data analysis method based on the analysis factor of the on-demand calculation according to claim 27, wherein the step (B1) further comprises:

(D1) performing a statistical calculation on the value of the at least one analysis factor actually required.

29. The data analysis method of an analysis factor based on an on-demand calculation according to claim 28, wherein the statistical calculation comprises at least one of the following statistical operation modes: summation (Sum), minimum value (Min) ), take the maximum value ( Max ) ₀

30. A data analysis method based on an analysis factor of an on-demand calculation according to claim 29, wherein said analysis model is a collection of logical decision rules associated with each other.