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CN108460077B - Index analysis method, system and computer readable storage medium - Google Patents

Index analysis method, system and computer readable storage medium Download PDF

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Publication number
CN108460077B
CN108460077B CN201810005100.1A CN201810005100A CN108460077B CN 108460077 B CN108460077 B CN 108460077B CN 201810005100 A CN201810005100 A CN 201810005100A CN 108460077 B CN108460077 B CN 108460077B
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target
source data
information
index
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CN108460077A (en
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谭奇
高俊秀
沈维海
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Beijing ByteDance Network Technology Co Ltd
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Beijing ByteDance Network Technology Co Ltd
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    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • G06F16/2458Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462Approximate or statistical queries

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Abstract

The invention relates to an index analysis method, a system and a computer readable storage medium, wherein the method comprises the following steps: the method comprises the steps of obtaining an analysis theme corresponding to an index to be analyzed, wherein the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, each configuration information comprises source data information configured by a user and a target change parameter, aiming at each analysis mode, obtaining at least one value of the target change parameter according to the source data information configured by the user and the target change parameter which are included in the analysis mode, and outputting the at least one value of the target change parameter obtained according to the analysis theme. According to the method and the device, a multi-layer analysis framework can be established according to the analysis theme, the index to be analyzed is automatically analyzed, and the index analysis efficiency is improved.

Description

Index analysis method, system and computer readable storage medium
Technical Field
To a method, system, and computer-readable storage medium for index analysis.
Background
In practical applications, an index of a certain object fluctuates with time, for example, the index of the playing amount of a certain movie changes constantly, or the index of the population number of a certain city changes, and the index needs to be analyzed in order to find out the reason for the fluctuation of the index of the certain object.
In the prior art, when index analysis is performed, the analysis process is rigid and cannot be flexibly configured from the acquisition of analysis data, the calculation in the analysis process and the generation of a final analysis result, so that the efficiency of analyzing indexes in the prior art is low.
Disclosure of Invention
Embodiments of the present invention provide an index analysis method, system and computer-readable storage medium, so as to solve the problem in the prior art that the configuration rigidity of an analysis index is low.
The embodiment of the invention adopts the following technical scheme:
the embodiment of the invention provides an index analysis method, which comprises the following steps:
obtaining an analysis theme corresponding to an index to be analyzed, wherein the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, and each configuration information comprises source data information configured by a user and a target change parameter;
aiming at each analysis mode, acquiring at least one numerical value of a target change parameter according to source data information configured by a user and the target change parameter in the analysis mode;
and outputting at least one value of the target variation acquired for each analysis mode.
The embodiment of the invention provides an index analysis system, which comprises an acquisition module, an analysis module and an output module, wherein:
the analysis system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an analysis theme corresponding to an index to be analyzed, the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, and each configuration information comprises source data information configured by a user and a target change parameter;
the analysis module is used for acquiring at least one numerical value of a target change parameter according to source data information configured by a user and the target change parameter in each analysis mode;
and the output module is used for outputting at least one numerical value of the target change parameter acquired aiming at each analysis mode. An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the index analysis method.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
in the embodiment of the invention, an analysis theme corresponding to an index to be analyzed is obtained, wherein the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, each configuration information comprises source data information configured by a user and a target change parameter, at least one numerical value of the target change parameter is obtained for each analysis mode according to the source data information configured by the user and the target change parameter which are included in the analysis mode, and the at least one numerical value of the target change parameter obtained for each analysis mode is output.
On one hand, the index to be analyzed can be automatically analyzed according to the analysis theme, so that the index analysis efficiency is improved;
on the other hand, since the analysis subject includes different analysis strategies including different analysis modes, the index to be analyzed can be analyzed from different levels, which results in higher accuracy of the analysis result.
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Fig. 1 is a schematic flow chart of an index analysis method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the structure of data in the analysis topic provided by the embodiment of the invention;
FIG. 3 is a schematic flow chart of another index analysis method provided in the embodiment of the present invention;
FIG. 4 is a schematic flow chart of another index analysis method provided in the embodiment of the present invention;
fig. 5 is a schematic structural diagram of an index analysis system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The technical scheme provided by the embodiment of the invention is described in detail below with reference to the accompanying drawings.
In order to solve the problem of low efficiency of index analysis in the prior art, the embodiment of the invention provides an index analysis method.
The execution main body of the method may be, but is not limited to, a user terminal such as a mobile phone, a tablet computer, or a Personal Computer (PC), or an Application (APP) running on the user terminal, or may also be a device such as a server.
For convenience of description, the following description will be made of an embodiment of the method, taking the execution subject of the method as a PC as an example. It is understood that the execution of the method by the PC is only an exemplary illustration and should not be construed as a limitation of the method.
The specific flow diagram of the method is shown in fig. 1, and the method comprises the following steps:
and step S101, obtaining an analysis theme corresponding to the index to be analyzed.
The analysis subject comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, and each configuration information comprises source data information configured by a user and a target change parameter.
The index to be analyzed refers to an index of an object to be analyzed, for example, the index to be analyzed may be a playing amount of a certain movie, a population of a certain city, or a click rate of a certain website news.
The above dimensions refer to the angle used when analyzing a certain index of a certain object, for example, if the click rate of a certain news website is to be analyzed, the click rate of each type of news can be analyzed from different dimensions such as military type news, entertainment type news, and international type news, that is, from different angles such as military type news, entertainment type news, and international type news, and the click rate of the news of the website is further analyzed.
The source data information may include a target dimension, a target index, target date information, and the like.
The target variation may be a variation such as a difference, a variation rate, or a degree of interpretation.
The date information may be a specific date, such as 1/2017 or 10/2017, or may be a relative date, such as the previous day or seven days of the current date.
It should be noted that, an analysis topic may correspond to at least two analysis strategies, each analysis strategy includes at least one analysis mode, and the reason is that multiple analysis strategies need to be set because there are many factors affecting fluctuation of an index to be analyzed and different factors affect each other, and different analysis strategies set different analysis modes, so that the same index to be analyzed can be analyzed from multiple layers, and accuracy of an analysis index result is improved.
The configuration information in different analysis modes may be completely different or may be partially the same. The same strategy comprises a plurality of different modes, the same mode can be contained by different strategies, and the configuration is very flexible. Data in the same mode can be analyzed and utilized by a plurality of strategies, and the data utilization rate is greatly improved.
The following illustrates a structure of data in an analysis topic, referring to fig. 2, fig. 2 is a schematic structural diagram of data in an analysis topic, where one analysis topic in fig. 2 includes contents of different levels, a layer above the analysis topic is 3 analysis strategies, respectively analysis strategies 1-3, taking an analysis strategy 2 as an example, a layer above the analysis strategy 2 is 3 analysis modes, respectively analysis modes 1-3, taking an analysis mode 1 as an example, and a layer above the analysis mode 1 is source data information and target change parameters.
Specifically, in the embodiment of the present invention, a corresponding relationship between each index of each object and an analysis topic may be established in advance, and an analysis mode corresponding to an index to be analyzed is obtained according to the corresponding relationship.
It should be noted that sometimes, an analysis theme corresponding to the index to be analyzed may be created in advance, the analysis theme corresponding to the index to be analyzed is obtained according to a preset time period, and then a subsequent operation is performed to analyze the index to be analyzed.
In addition, before analyzing the index to be analyzed, an analysis topic may be created, and then the index to be analyzed may be analyzed according to the analysis topic, so before performing step 101, an analysis topic corresponding to the index to be analyzed may be generated. In practical application, different users have different emphasis points when analyzing the index to be analyzed, for example, some users focus on the influence of different factors on the analysis server on the index to be analyzed, and some users focus on the influence of different factors on the mobile terminal on the index to be analyzed, and if the analysis result meets the user requirement, the analysis strategy meets the user requirement, and an analysis topic generation method is provided below, where the method includes:
the method comprises the steps of obtaining at least one piece of configuration information corresponding to an index to be analyzed, generating at least one analysis mode according to the at least one piece of configuration information and at least one analysis mode template, generating at least one analysis strategy according to the at least one analysis mode and at least one preset analysis strategy template, and generating an analysis topic according to the at least one analysis strategy and a preset analysis topic template.
Two methods for acquiring at least one configuration information corresponding to an index to be analyzed are as follows:
the first method comprises the following steps: at least one configuration information input by a user is received. The user may input the at least one configuration information to the PC via an input device such as a keyboard, microphone, or the like.
The second method comprises the following steps: and responding to a selection instruction of a user, and selecting a target dimension, a target index, a target change parameter and target date information corresponding to the selection instruction of the user from a plurality of candidate information respectively corresponding to the dimension, the index, the change parameter and the date information.
In generating the analysis pattern, the analysis policy, and the analysis topic, the PC may add information corresponding to the user's operation to each template in response to the user's operation, thereby generating the analysis pattern, the analysis policy, and the analysis topic. The same analysis mode can be added into a plurality of preset analysis strategy templates, so that the utilization rate of data information can be improved, the operation of a user is reduced as much as possible, the time is saved, and the generation efficiency of the analysis strategies is improved. In addition, in the process of generating the analysis strategy, the process of configuring information by a user and the process of triggering the PC to add different information into different templates are simple and flexible to operate, so that the generation process of the analysis theme is simple, and the generation efficiency is high.
The user mentioned above refers to a legitimate user, that is, the identity of the user is legitimate. In order to improve the security of the index analysis method, avoid lawless persons from configuring information as much as possible, or avoid lawless persons from stealing the analysis result as much as possible, and judge whether a user is a legal user in advance, in the embodiment of the invention, whether the user is a legal user can be checked by the following method:
acquiring identity authentication information input by a user, judging whether the identity authentication information is the same as preset identity authentication information or not, and if so, judging that the user is a legal user; otherwise, the user is judged to be an illegal user.
Step S102, aiming at each analysis mode, obtaining at least one numerical value of the target change parameter according to the source data information configured by the user and the target change parameter included in the analysis mode.
In this case, at least one value of the target change parameter refers to a value of the target dimension, a target index, and a target change parameter corresponding to the target date information, for example, if the target date information refers to yesterday and the previous day, the target dimension refers to entertainment type news, the target index refers to click rate, and the target change parameter refers to change rate, the target value refers to a value of the entertainment type news, the click rate, and the change rate corresponding to yesterday and the previous day.
The following briefly describes how an embodiment of the present invention performs step 102:
and acquiring source data according to source data information aiming at each analysis mode, wherein the source data refers to data corresponding to date information, target dimensionality and target indexes, acquiring a calculation method corresponding to a target change parameter according to a preset corresponding relation between the change parameter and the calculation method and the target change parameter, and acquiring at least one value of the target change parameter according to the source data and the calculation method.
The method for acquiring the source data comprises the following steps:
and for each analysis mode, generating acquisition source data request information according to the source data information, wherein the acquisition source data request information comprises target dimensions, target indexes and target date information, and sending the acquisition source data request information to the appointed at least one database, so that the appointed at least one database returns data corresponding to the acquisition source data request information according to the acquisition source data request information after receiving the acquisition source data request information, receives the data returned by the appointed at least one database, and takes the received data as source data. The at least one designated database may include a Hive, Mysql, or Hbase database.
It should be noted that, in order to avoid the calculation result from being incorrect as much as possible and improve the accuracy of the calculation result as much as possible, after the source data is acquired according to the source data information for each analysis mode, before at least one value of the target variation parameter is acquired according to the source data and the calculation method, the following operations may be further performed:
detecting state information of source data, wherein the state information of the source data comprises data integrity and data date information; when the state information of the source data is detected to be normal, acquiring at least one numerical value of a target change parameter according to the acquired source data and a calculation method; and when the state information of the source data is detected to be abnormal, the source data is acquired again. The data date information here is the same as the target date information.
Step S103, outputting at least one value of the target variation acquired for each analysis mode.
In the embodiment of the invention, the calculation result can be output in any form of characters, graphs, sounds and the like. In order to facilitate the user to query the calculation result, a receiving object, such as a mobile phone number or a mailbox, may be set in advance, and then, when step S103 is executed, at least one value obtained from the target variation parameter may be output to the receiving object set in advance in any form, such as a text, a graph, or a sound.
It should be noted that, in order to obtain richer analysis results and improve the accuracy of the analysis results as much as possible, each analysis mode may further include abnormal data range information, and then, for each analysis mode, after calculating at least one value of the target variation parameter according to the source data information and the target variation parameter, the following operations may also be performed:
and judging whether at least one value of the target change parameter is abnormal or not according to at least one value of the target change parameter and the abnormal value range information aiming at each analysis mode, acquiring a judgment result, and outputting the judgment result acquired aiming at each analysis mode.
The judgment result may be output in any form such as a character, a graph, or a voice. In order to facilitate the user to query the calculation result, a receiving object, such as a mobile phone number or a mailbox, may be set in advance, and then the determination result may be output to the receiving object set in advance in any form, such as a text, a graph, or a sound.
In addition, when the judgment result is output, if the judgment result has an abnormal result, reminding information can be output to remind a user that the abnormal judgment result exists in the judgment result, so that the user can check and process the abnormal judgment result in time.
The embodiment of the invention also provides another index analysis method which is executed on the index analysis platform. The index analysis platform is used for analyzing the index to be analyzed and can comprise a configuration module, an acquisition module, an analysis module and a display module. The existence form of the platform may be a browser form or an application form, which is not limited in any way by the embodiment of the present invention. The schematic flow chart of the index analysis method can be seen in fig. 3, and the method comprises the following steps:
step S201, a configuration module acquires configuration information configured by a user and generates an analysis theme corresponding to the index to be analyzed.
Step S202, the acquisition module acquires source data from at least one appointed database according to the analysis subject.
The at least one designated database may include a Hive, Mysql, or Hbase database.
And step S203, the analysis module analyzes the index to be analyzed according to the source data and the analysis theme to generate an analysis result.
And step S204, the display module displays the analysis result.
In addition, in order to make the reader understand the index analysis method provided in the embodiment of the present invention more easily, the embodiment of the present invention further provides another specific index analysis method, which is executed on the above-mentioned index analysis platform, and a flow diagram of the method is shown in fig. 4, where the method includes the following steps:
step S301, acquiring identity information input by a user.
Step S302, judging whether the identity information input by the user is legal information.
If yes, go to step 303, otherwise, end the process.
Step S303, in response to a creation instruction of the user, creating an analysis topic corresponding to the index to be analyzed.
The creating instruction may be an instruction generated by displaying a creating control in a double-click or single-click index analysis platform of a user.
The analysis topic may include a name of the index to be analyzed, information of a user who needs to obtain an analysis result corresponding to the analysis topic information, and information of a user who creates the analysis topic. The information of the user may include at least one of a name, an identification number, a telephone number, and a mailbox of the user.
For example, if the index of the number of questions and answers of an APP is to be analyzed, the name of the created analysis topic may be "the number of questions and answers of an APP".
Step S304, responding to a first adding instruction of a user, and adding at least one analysis strategy in the analysis topic.
The first adding instruction may be an instruction generated by adding an analysis policy control displayed in a double-click or single-click index analysis platform of a user.
Each analysis policy may include a name of the analysis policy, information of a user who needs to obtain an analysis result corresponding to the analysis policy, and information of a user who creates the analysis policy.
Along the above example, if the number of analysis strategies is two, one of the analysis strategies may be named "question number analysis" and the other may be "answer number analysis".
Step S305, in response to a second adding instruction of the user, adding at least one analysis mode in each analysis strategy.
The second adding instruction may be an instruction generated by a user through double-clicking or clicking an adding analysis mode control displayed in the index analysis platform.
Continuing with the above example, an analysis policy of "question number analysis" may include 4 analysis modes, names of the 4 analysis modes may respectively be "operating system question number cycle ratio change rate", "certain APP question number cycle ratio change rate", and an analysis policy of "answer number analysis" may include 4 analysis modes, and the 4 analysis modes may respectively be "operating system answer number cycle ratio change rate", "certain APP answer number cycle ratio change rate", and "certain APP answer number cycle ratio change rate".
Step S306, adding configuration information in each analysis mode in response to a third addition instruction of the user.
Each configuration information may include a name of the target dimension, a name of the target index, a name of the target variation parameter, and target date information. In general, either the ring ratio target variation parameter or the year target variation parameter is calculated, and then the target date information is relatively, either adjacent dates or dates separated by a preset time period.
Continuing with the above example, after step S306 is completed, the data contained in an analysis topic can be represented by the following table:
Figure GDA0002675253910000081
Figure GDA0002675253910000091
step S307, analyzing the index to be analyzed according to each analysis mode included in the analysis theme, and obtaining an analysis result.
Step S308, displaying the analysis result.
In addition, in the embodiment of the present invention, in order to solve the problem of low efficiency of analyzing an index in the prior art, a structural schematic diagram of the system is shown in fig. 4, and the system includes an obtaining module 401, an analyzing module 402, and an output module 403, where:
the obtaining module 401 is configured to obtain an analysis topic corresponding to an index to be analyzed, where the analysis topic includes at least one analysis policy, each analysis policy includes at least one analysis mode, each analysis mode includes configuration information, and each configuration information includes source data information configured by a user and a target change parameter.
An analysis module 402, configured to, for each analysis mode, obtain at least one value of a target variation parameter according to source data information configured by a user and the target variation parameter included in the analysis mode.
An output module 403, configured to output at least one value of the target variation obtained for each analysis mode.
In an implementation scenario, before obtaining an analysis topic corresponding to an index to be analyzed, the system further includes a generation module configured to:
acquiring at least one configuration information corresponding to an index to be analyzed;
generating the at least one analysis pattern according to the at least one piece of configuration information and at least one analysis pattern template;
generating the at least one analysis strategy according to the at least one analysis mode and at least one preset analysis strategy template;
and generating the analysis theme according to the at least one analysis strategy and a preset analysis theme template.
In one implementation scenario, the source data information includes a target dimension, a target index, and target date information.
In an implementation scenario, the analysis module 402 is specifically configured to:
for each analysis mode, acquiring source data according to the source data information, wherein the source data refers to data corresponding to the date information, the target dimension and the target index;
acquiring a calculation method corresponding to the target change parameter according to a corresponding relation between a preset change parameter and the calculation method and according to the target change parameter;
and acquiring at least one value of the target change parameter according to the source data and the calculation method.
In an implementation scenario, the analysis module 402 is specifically configured to:
generating acquisition source data request information according to the source data information aiming at each analysis mode, wherein the acquisition source data request information comprises the target dimension, the target index and the target date information;
sending the acquisition source data request information to at least one appointed database, so that the appointed database returns data corresponding to the acquisition source data request information according to the acquisition source data request information after receiving the acquisition source data request information;
and receiving data returned by the at least one designated database, and taking the received data as the source data.
In one implementation scenario, the system further includes a detection module to:
detecting state information of the source data, wherein the state information of the source data comprises data integrity and data date information; then
The obtaining module 401 is specifically configured to:
and when the state information of the source data is detected to be normal, acquiring at least one numerical value of the target change parameter according to the acquired source data and the calculation method.
In an implementation scenario, each analysis mode further includes abnormal value range information, then
The analysis module 402 is further configured to:
for each analysis mode, judging whether at least one value of the target change parameter is abnormal or not according to at least one value of the target change parameter and the abnormal value range information, and obtaining a judgment result;
the output module 403 is further configured to output a determination result obtained for each analysis mode.
In one implementation scenario, the user is a legitimate user.
In an implementation scenario, the obtaining module 401 is specifically configured to:
and acquiring an analysis theme corresponding to the index to be analyzed according to a preset time period.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is capable of implementing any one of the index analysis methods described above when executed by a processor.
In the embodiment of the invention, an analysis theme corresponding to an index to be analyzed is obtained, wherein the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, each configuration information comprises source data information configured by a user and a target change parameter, for each analysis mode, at least one value of the target change parameter is obtained according to the source data information configured by the user and the target change parameter which are included in the analysis mode, and the obtained at least one value of the target change parameter for each analysis mode is output, on one hand, the index to be analyzed can be automatically analyzed according to the analysis theme, and the efficiency of index analysis is improved; on the other hand, since the analysis topic may include different analysis strategies including different analysis modes, the index to be analyzed may be analyzed from different levels, so that the accuracy of index analysis is high.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (19)

1. An index analysis method, characterized in that the method comprises:
obtaining an analysis theme corresponding to an index to be analyzed, wherein the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, the configuration information comprises source data information configured by a user and a target change parameter, the same analysis strategy is allowed to comprise a plurality of different analysis modes, the same analysis mode is allowed to be comprised by different analysis strategies, and data of the same analysis mode is allowed to be utilized by a plurality of different analysis strategies;
for each analysis mode, acquiring at least one numerical value of a target change parameter according to source data information configured by a user and the target change parameter in the analysis mode;
outputting at least one numerical value of the target variation parameter acquired for each analysis mode;
the source data information comprises a target dimension, a target index and target date information; at least one value of the target variable is: the numerical values of the target dimension, the target index and the target variation parameter correspond to the target date information;
the obtaining, for each analysis mode, at least one value of a target variation parameter according to source data information configured by a user and the target variation parameter included in the analysis mode includes: and acquiring source data according to the source data information, and acquiring at least one value of a target change parameter according to the source data and the target change parameter.
2. The method of claim 1, wherein prior to obtaining an analysis topic corresponding to an indicator to be analyzed, the method further comprises:
acquiring at least one configuration information corresponding to an index to be analyzed;
generating the at least one analysis pattern according to the at least one piece of configuration information and at least one analysis pattern template;
generating the at least one analysis strategy according to the at least one analysis mode and at least one preset analysis strategy template;
and generating the analysis theme according to the at least one analysis strategy and a preset analysis theme template.
3. The method of claim 1, wherein the source data information comprises a target dimension, a target indicator, and target date information.
4. The method of claim 3, wherein for each analysis mode, obtaining at least one value of the target variation parameter according to the source data information configured by the user and the target variation parameter included in the analysis mode specifically includes:
the source data refers to data corresponding to the target dimension and the target index corresponding to the date information;
aiming at each analysis mode, acquiring a calculation method corresponding to the target change parameter according to the corresponding relation between the preset change parameter and the calculation method and the target change parameter;
and acquiring at least one value of the target change parameter according to the source data and the calculation method.
5. The method of claim 4, wherein said obtaining source data from said source data information for said each analysis mode comprises:
generating acquisition source data request information according to the source data information aiming at each analysis mode, wherein the acquisition source data request information comprises the target dimension, the target index and the target date information;
sending the acquisition source data request information to at least one appointed database, so that the appointed database returns data corresponding to the acquisition source data request information according to the acquisition source data request information after receiving the acquisition source data request information;
and receiving data returned by the at least one designated database, and taking the received data as the source data.
6. The method of claim 4, wherein after acquiring source data from the source data information for each of the analysis modes, before acquiring at least one value of the target variation from the source data and the calculation method, the method further comprises:
detecting state information of the source data, wherein the state information of the source data comprises data integrity and data date information; then
Obtaining at least one value of the target variation parameter according to the source data and the calculation method, specifically comprising:
and when the state information of the source data is detected to be normal, acquiring at least one numerical value of the target change parameter according to the acquired source data and the calculation method.
7. The method of claim 1, wherein each analysis mode further comprises abnormal value range information, then
After calculating at least one value of the target variation parameter according to the source data information and the target variation parameter for each analysis mode, the method further includes:
for each analysis mode, judging whether at least one value of the target change parameter is abnormal or not according to at least one value of the target change parameter and the abnormal value range information, and obtaining a judgment result;
and outputting the judgment result obtained for each analysis mode.
8. The method of claim 1, wherein the user is a legitimate user.
9. The method of claim 1, wherein obtaining an analysis topic corresponding to an index to be analyzed specifically comprises:
and acquiring an analysis theme corresponding to the index to be analyzed according to a preset time period.
10. An index analysis system, the system comprising:
the analysis module is used for acquiring an analysis theme corresponding to an index to be analyzed, wherein the analysis theme comprises at least one analysis strategy, each analysis strategy comprises at least one analysis mode, each analysis mode comprises configuration information, each configuration information comprises source data information and a target change parameter configured by a user, the same analysis strategy is allowed to comprise a plurality of different analysis modes, the same analysis mode is allowed to be comprised by different analysis strategies, and data of the same analysis mode is allowed to be utilized by the different analysis strategies;
the analysis module is used for acquiring at least one numerical value of a target change parameter according to source data information configured by a user and the target change parameter in each analysis mode;
the output module is used for outputting at least one numerical value of the target change parameter acquired aiming at each analysis mode;
the source data information comprises a target dimension, a target index and target date information; at least one value of the target variable is: the numerical values of the target dimension, the target index and the target variation parameter correspond to the target date information;
the analysis module is further to: and acquiring source data according to the source data information, and acquiring at least one value of a target change parameter according to the source data and the target change parameter.
11. The system of claim 10, wherein prior to obtaining an analysis topic corresponding to an indicator to be analyzed, the system further comprises a generation module to:
acquiring at least one configuration information corresponding to an index to be analyzed;
generating the at least one analysis pattern according to the at least one piece of configuration information and at least one analysis pattern template;
generating the at least one analysis strategy according to the at least one analysis mode and at least one preset analysis strategy template;
and generating the analysis theme according to the at least one analysis strategy and a preset analysis theme template.
12. The system of claim 10, wherein the source data information includes a target dimension, a target indicator, and target date information.
13. The system of claim 12, wherein the analysis module is specifically configured to:
the source data refers to data corresponding to the target dimension and the target index corresponding to the date information;
aiming at each analysis mode, acquiring a calculation method corresponding to the target change parameter according to the corresponding relation between the preset change parameter and the calculation method and the target change parameter;
and acquiring at least one value of the target change parameter according to the source data and the calculation method.
14. The system of claim 13, wherein the analysis module is specifically configured to:
generating acquisition source data request information according to the source data information aiming at each analysis mode, wherein the acquisition source data request information comprises the target dimension, the target index and the target date information;
sending the acquisition source data request information to at least one appointed database, so that the appointed database returns data corresponding to the acquisition source data request information according to the acquisition source data request information after receiving the acquisition source data request information;
and receiving data returned by the at least one designated database, and taking the received data as the source data.
15. The system of claim 13, further comprising a detection module to:
detecting state information of the source data, wherein the state information of the source data comprises data integrity and data date information; the acquisition module is specifically configured to:
and when the state information of the source data is detected to be normal, acquiring at least one numerical value of the target change parameter according to the acquired source data and the calculation method.
16. The system of claim 10, wherein each analysis mode further comprises outlier range information, the analysis module further configured to:
for each analysis mode, judging whether at least one value of the target change parameter is abnormal or not according to at least one value of the target change parameter and the abnormal value range information, and obtaining a judgment result;
the output module is further configured to output a determination result obtained for each analysis mode.
17. The system of claim 10, wherein the user is a legitimate user.
18. The system of claim 10, wherein the acquisition module is specifically configured to:
and acquiring an analysis theme corresponding to the index to be analyzed according to a preset time period.
19. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, is adapted to carry out the method of any one of claims 1 to 9.
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CN109918533B (en) * 2019-02-19 2024-05-28 珠海格力电器股份有限公司 Noise processing method and device
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Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8819042B2 (en) * 2010-04-23 2014-08-26 Bank Of America Corporation Enhanced data comparison tool
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CN105608132B (en) * 2015-12-16 2019-04-30 北京奇虎科技有限公司 It is a kind of that the method and apparatus of the customized service for generating chart are provided
CN105912699A (en) * 2016-04-25 2016-08-31 乐视控股(北京)有限公司 Data analysis method and device
CN107526832A (en) * 2017-09-05 2017-12-29 江苏电力信息技术有限公司 A kind of method for building the big data business model that technology is pulled based on the page

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
"医院数据分析与决策支持系统的研究与实现";陈龙辉;《中国优秀硕士学位论文全文数据库 信息科技辑》;20170315;第2017年卷(第3期);I138-3705 *

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