CN111752988A

CN111752988A - Automatic data analysis method and device

Info

Publication number: CN111752988A
Application number: CN201910252195.1A
Authority: CN
Inventors: 温英彬
Original assignee: Beijing Qihoo Technology Co Ltd
Current assignee: Beijing Qihoo Technology Co Ltd
Priority date: 2019-03-29
Filing date: 2019-03-29
Publication date: 2020-10-09

Abstract

The invention provides an automatic data analysis method and a device, wherein the method comprises the following steps: acquiring different dimensional data and different index data from a preset database, and generating an analysis rule according to the dimensional data and the index data; selecting a plurality of analysis rules related to the items to be analyzed, and combining the selected plurality of analysis rules into an analysis template aiming at the items to be analyzed; carrying out anomaly analysis on the items to be analyzed by using analysis rules in the analysis template to obtain analysis results; and if the analysis result is that the item to be analyzed does not accord with the corresponding analysis rule, sending the analysis result to a preset service staff through a mail. The analysis rules are combined into the analysis template, and the data items are analyzed by using the analysis template, so that the single-point monitoring (namely, the data items are analyzed from a single dimension, and at the moment, one rule corresponds to one analysis template) and the overall analysis (namely, the data items are analyzed from multiple dimensions) can be both met.

Description

Automatic data analysis method and device

Technical Field

The invention relates to the technical field of data analysis, in particular to an automatic data analysis method and device.

Background

In the prior art, the conventional service index fluctuation checking concept mainly includes first ensuring that data synchronization calculation is free of abnormality (such as checking interface data synchronization, checking data warehouse calculation, and checking application layer calculation), second analyzing single dimensions and combined dimensions to find abnormal dimensions, and finally summarizing final conclusions. If manual analysis is adopted in the process, even simple business problems also take 1-2 days, and when the business problems occur again, the checking process needs to be repeated, which wastes time and labor.

There are two main solutions to the above problems: one is a mail report, and the other is a data quality checking platform. However, since the aperture and the analysis thought of each service index may be different, a large number of programs need to be developed by adopting the email report, especially for monitoring only a single dimension index, the development cost is too high, and the email is sent regardless of abnormal data fluctuation, but abnormal data is not alarmed, and the risk of overlooking is existed. In addition, most of conventional business analysis adopts an analysis report form, while most of data quality check platforms are oriented to single-point monitoring (single rule monitoring), and analysis monitoring cannot be performed according to the idea of the analysis report (the analysis report is generally multi-dimensional and multi-index analysis and various complex combined dimension analysis).

Disclosure of Invention

In view of the above, the present invention has been made to provide an automatic data analysis method and apparatus that overcomes or at least partially solves the above problems.

According to an aspect of the present invention, there is provided an automatic data analysis method, including:

acquiring different dimension data and different index data from a preset database, and generating an analysis rule according to the dimension data and the index data;

selecting a plurality of analysis rules related to the items to be analyzed, and combining the selected plurality of analysis rules into an analysis template aiming at the items to be analyzed;

carrying out anomaly analysis on the item to be analyzed by using an analysis rule in the analysis template to obtain an analysis result;

and if the analysis result is that the item to be analyzed does not accord with the corresponding analysis rule, sending the analysis result to a preset service staff through a mail.

Optionally, after performing anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template and obtaining an analysis result, the method further includes:

configuring the analysis results to a visualization platform;

acquiring a link of a visual interface in the visual platform, and sending the link to the preset business personnel through an email;

and when the link receives the click operation of the preset business personnel, calling a visual interface in a visual platform, and displaying an analysis result on the visual interface.

Optionally, generating an analysis rule according to the dimension data and the index data includes:

setting attribute information for judging whether the items to be analyzed meet the analysis rules or not according to the dimension data and the index data;

and constructing a corresponding analysis rule based on the dimension data, the index data and the attribute information of the analysis rule.

Optionally, the attribute information includes a comparison time and a lift type.

Optionally, the attribute information further includes at least one of a lower threshold, an upper threshold, and a ranking limit.

Optionally, before performing anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template, the method further includes:

configuring the relevant information of the dimension data to a dimension information table which is created in advance;

configuring the related information of the index data to a pre-established index information table;

configuring the relevant information of the analysis rule to a rule information table which is established in advance;

configuring the related information of the analysis template to a pre-established template information table;

and establishing a corresponding relation between the plurality of analysis rules and the analysis templates combined by the analysis rules, and configuring the corresponding relation information to a pre-established template rule corresponding relation table.

Optionally, the related information of the dimension data includes a dimension ID, a dimension name, and a field name;

the related information of the index data comprises an index ID, an index name and a field name;

the related information of the analysis rule comprises a rule ID, a dimension ID of dimension data corresponding to the analysis rule, an index ID of corresponding index data and attribute information of the analysis rule;

the related information of the analysis template comprises a template ID;

the correspondence information includes a relationship ID, a template ID, and a rule ID of an analysis rule corresponding to the analysis template.

Optionally, performing anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template, including:

sequentially acquiring rule IDs of a plurality of analysis rules corresponding to the analysis template according to the template rule corresponding relation table;

calling a corresponding rule information table according to the rule IDs which are sequentially obtained, and extracting the dimension ID, the index ID and the attribute information of the analysis rule from the corresponding rule information table;

extracting relevant information of other dimension data and relevant information of other index data from the corresponding dimension information table and index information table respectively according to the dimension ID and the index ID;

and carrying out anomaly analysis on the item to be analyzed according to the extracted relevant information of the dimension data, the relevant information of the index data and the attribute information.

Optionally, before sending the analysis result to the preset service staff by mail, the method further includes:

taking the business personnel related to the project to be analyzed as the preset business personnel, and establishing a recipient list according to the preset business personnel;

setting the sending time of the mail, and determining the mail subject according to the item to be analyzed;

and configuring the sending time of the mail, the mail subject, the recipient list and the template ID of the analysis template into a pre-created mail information table.

Optionally, sending the analysis result to a preset service staff by a mail, including:

configuring the analysis result into a preset conclusion template to obtain conclusion report information;

and when the sending time of the mail is reached, sending the conclusion report information to business personnel in the recipient list through the mail.

Optionally, the different dimensional data comprises at least one of: brand dimension, version dimension, model dimension, firmware version dimension.

Optionally, the different metric data comprises at least one of: the number of active users, the number of downloading users, the number of online users and the number of sub-streaming users.

According to another aspect of the present invention, there is also provided an automatic data analysis apparatus, comprising:

the generating module is suitable for acquiring different dimensional data and different index data from a preset database and generating an analysis rule according to the dimensional data and the index data;

the combination module is suitable for selecting a plurality of analysis rules related to the items to be analyzed and combining the selected analysis rules into an analysis template aiming at the items to be analyzed;

the analysis module is suitable for carrying out abnormity analysis on the item to be analyzed by utilizing the analysis rule in the analysis template to obtain an analysis result;

and the sending module is suitable for sending the analysis result to a preset service staff through a mail if the analysis result is that the item to be analyzed does not accord with the corresponding analysis rule.

Optionally, the apparatus further comprises:

the first configuration module is used for performing abnormity analysis on the item to be analyzed by using the analysis rule in the analysis template through the analysis module to obtain an analysis result, and then configuring the analysis result to a visualization platform;

the sending module is suitable for obtaining a link of a visual interface in the visual platform and sending the link to the preset business personnel through a mail;

and the calling module is suitable for calling a visual interface in the visual platform when the link receives the click operation of the preset business personnel, and displaying the analysis result on the visual interface.

Optionally, the generating module is further adapted to:

Optionally, the apparatus further comprises a second configuration module adapted to, before performing anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template,

the related information of the analysis template comprises a template ID;

Optionally, the analysis module is further adapted to:

Optionally, the second configuration module is further adapted to:

before the sending module sends the analysis result to a preset service person through a mail, the service person related to the project to be analyzed is used as the preset service person, and a recipient list is established according to the preset service person;

Optionally, the sending module is further adapted to:

According to yet another aspect of the present invention, there is also provided a computer storage medium having computer program code stored thereon, which, when run on a computing device, causes the computing device to perform the automatic data analysis method of any of the above embodiments.

In accordance with yet another aspect of the present invention, there is also provided a computing device comprising: a processor; a memory storing computer program code; the computer program code, when executed by the processor, causes the computing device to perform the automatic data analysis method of any of the embodiments above.

In the embodiment of the invention, the analysis rule is generated according to the dimension data and the index data in the preset database, the analysis template for the item to be analyzed is combined by using a plurality of analysis rules related to the item to be analyzed, the analysis rule in the analysis template can be further used for carrying out abnormal analysis on the item to be analyzed, and if the analysis result shows that the item to be analyzed does not accord with the corresponding analysis rule, the analysis result can be sent to the preset service personnel through a mail. Therefore, the analysis rules are combined into the analysis template, and the data items are analyzed by using the analysis template, so that the single-point monitoring (namely, the data items are analyzed from a single dimension, and one rule corresponds to one analysis template) and the overall analysis (namely, the data items are analyzed from multiple dimensions) can be met. A single analysis rule can also be configured into a plurality of different analysis templates, so that the analysis rule can be repeatedly utilized, and the rule development and calculation cost is reduced. Furthermore, when the analysis result is sent, the content of all the analysis results can be selected to be sent, and only the abnormal alarm content can be sent, so that the abnormal point in the service can be directly positioned, and the service personnel can be prevented from neglecting and checking the mail.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1 shows a flow diagram of a method of automated data analysis according to one embodiment of the invention;

FIG. 2 illustrates a schematic structural diagram of various information tables according to one embodiment of the present invention;

FIG. 3 shows a schematic structural diagram of an automated data analysis apparatus according to one embodiment of the present invention;

FIG. 4 shows a schematic structural diagram of an automatic data analysis apparatus according to another embodiment of the present invention;

fig. 5 shows a schematic configuration diagram of an automatic data analysis apparatus according to still another embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

In order to solve the above technical problems, an embodiment of the present invention provides an automatic data analysis method. FIG. 1 shows a flow diagram of a method of automated data analysis according to one embodiment of the invention. Referring to fig. 1, the method includes at least steps S102 to S108.

Step S102, dimension data of different dimensions of the service data and index data of different indexes are obtained from a preset database, and an analysis rule is generated according to the dimension data and the index data.

The pre-set database (e.g., data warehouse) in this step is used to provide basic data support, including a variety of basic data for subsequent analysis of the item to be analyzed.

And step S104, selecting a plurality of analysis rules related to the items to be analyzed, and combining the selected plurality of analysis rules into an analysis template aiming at the items to be analyzed.

In this step, the items to be analyzed may be items to be analyzed of an application, such as items to be analyzed of a cell phone assistant, items to be analyzed of a security guard, and the like. For example, the item to be analyzed is the number of active users of the mobile phone assistant, and a plurality of analysis rules related to the number of active users of the mobile phone assistant may be selected from the plurality of analysis rules generated in step S102.

And step S106, carrying out abnormity analysis on the item to be analyzed by utilizing the analysis rule in the analysis template to obtain an analysis result.

And step S108, if the analysis result is that the item to be analyzed does not accord with the corresponding analysis rule, sending the analysis result to a preset service staff through an email.

In this step, since the analysis template may be composed of a plurality of analysis rules, and each analysis rule has a corresponding analysis result, different analysis results may be obtained for different analysis rules, and the analysis result sent to the preset service person may only include an abnormal data content part in the analysis results, or may include related data of all the analysis results.

The embodiment of the invention combines the analysis rules into the analysis template, and analyzes the data items by using the analysis template, thereby not only meeting the requirements of single-point monitoring (namely analyzing the data items from a single dimension, and one rule corresponds to one analysis template at the time) but also meeting the requirements of overall analysis (namely analyzing the data items from multiple dimensions). A single analysis rule can also be configured to a plurality of different analysis templates, so that the analysis rule can be repeatedly utilized, and the rule development and calculation cost is reduced. Furthermore, when the analysis result is sent, the abnormal point in the service can be directly positioned by sending the abnormal alarm content, and the service personnel can be prevented from neglecting and checking the mail.

In an embodiment of the present invention, the analysis result may be configured in an interface manner, and the analysis result is configured to the visualization platform, so that the analysis result is displayed to the service personnel more intuitively. Specifically, after the analysis result is configured to the visualization platform, the link of the visualization interface in the visualization platform is obtained, and the link is sent to the preset business personnel through the mail. And when the link receives the click operation of a preset business person, calling a visual interface in the visual platform, and displaying an analysis result on the visual interface.

In addition, the embodiment of the invention can also configure the analysis template to the visual platform, and each analysis rule corresponding to the analysis template corresponds to one visual graph on the visual interface, so that a set of display contents of the visual analysis process is integrally formed, and further, the analysis result and the link corresponding to the display contents of the visual analysis process are sent to the corresponding business personnel through the mail. In the process of visual analysis, different indexes or data obtained by analysis and the like can be visually displayed in the form of charts, such as trend charts, pie charts and bar charts.

Referring to step S102 above, in an embodiment of the present invention, when the analysis rule is generated according to the dimension data and the index data, attribute information used for determining whether the item to be analyzed meets the analysis rule may be further set according to the dimension data and the index data, and a corresponding analysis rule is constructed based on the dimension data, the index data, and the attribute information of the analysis rule.

In this embodiment, the attribute information may include a comparison time, such as a ring ratio or a parity, such as a comparison of the data of the last seven days, a comparison of the data of the next day, a comparison of the data of the previous day, and the like; the lifting type can monitor the rising and the falling independently, and can also monitor the rising and the falling within the time interval range, and the like. Of course, the attribute information may also include a lower threshold; an upper threshold; and ranking limits, such as excessive dimensionality, which can take at least one of the dimensions at the top of the comprehensive ranking, and the like.

In the embodiment of the present invention, the different dimension data may include a brand dimension, a version dimension, a model dimension, a firmware version dimension, and the like. The different index data may include the number of active users, the number of downloaded users, the number of online users, the number of sub-streaming users, and so on.

For example, the dimension data is a brand dimension, the index data is the number of active users, the attribute information includes that the number of comparison days is 7 days, the lifting type is descending, the upper threshold value is 0 (because the type is descending), the lower threshold value is 30%, and the top value is 100000 (i.e., only the number of active users is analyzed for a mainstream brand greater than 10 ten thousand), so that the analysis rule constructed according to the above information can be used for analyzing the number of active users of the brand, and the number of the descending users is not more than 30% compared with the number of active users of the brand within 7 days.

In an embodiment of the present invention, for convenience, the analysis rule in the analysis template is used to perform anomaly analysis on the item to be analyzed. After different dimension data and different index data are acquired from a preset database, relevant information of the dimension data, the index data, the generated analysis rules and the like can be configured into different information tables which are created in advance.

Specifically, the related information of the dimension data may be configured to a dimension information table created in advance. The related information of the index data is configured to the index information table created in advance. And configuring the related information of the analysis rule to a rule information table which is created in advance. And configuring the related information of the analysis template to a pre-created template information table. And establishing a corresponding relation between the plurality of analysis rules and the analysis templates combined by the analysis rules, and further configuring the corresponding relation information to a pre-established template rule corresponding relation table.

Referring to fig. 2, in the embodiment of the present invention, the related information of the dimension data in the dimension information table includes a dimension ID, a dimension name, a field name, a table name, and the like.

The related information of the index data in the index information table includes an index ID, an index name, a field name, and the like.

The related information of the analysis rule in the rule information table includes a rule ID, a dimension ID of dimension data corresponding to the analysis rule, an index ID of corresponding index data, attribute information of the analysis rule, and the like.

The related information of the analysis template in the template information table includes a template ID, a template name, a visual link (i.e. a link of a visual interface in a visual platform), and the like.

The information of the correspondence in the template rule correspondence table includes a relationship ID, a template ID, a rule ID of an analysis rule corresponding to the analysis template, and the like, and the relationship ID may be used to indicate a relationship between a certain template ID and certain rule IDs or a certain rule ID. Since the rule template is composed according to a plurality of analysis rules, the template ID, the corresponding rule ID, and the relationship ID between the analysis template and the plurality of analysis rules are stored in the template rule correspondence table. And each analysis rule corresponding to the analysis template can be found through the template rule corresponding relation table.

Further, as shown in fig. 2, each information table also records the creation time and update time of the information table. Although in fig. 2, table names are not shown in any of the other information tables except the index information table, in practice, table names may be included in the other information tables, and since each information table is also stored in the database, each information table includes its own table name for the convenience of identifying each information table.

Referring to step S106, in an embodiment of the present invention, when the analysis rule in the analysis template is used to perform the anomaly analysis on the items to be analyzed, the analysis template corresponds to a plurality of analysis rules, and therefore, the analysis rule in the analysis template is sequentially used to perform the anomaly analysis on the items to be analyzed, so that the items to be analyzed can be analyzed from multiple dimensions by using different indexes.

Firstly, a rule ID of an analysis rule corresponding to an analysis template is obtained according to a template rule corresponding relation table. That is, a rule ID corresponding to the template ID of the analysis template is acquired according to the template rule correspondence table.

And then, calling a corresponding rule information table according to the obtained rule ID, and extracting the dimension ID, the index ID and the attribute information of the analysis rule from the called rule information table.

And further, extracting relevant information of other dimension data and relevant information of other index data, such as extracting dimension data, table names and field names of index data, from the corresponding dimension information table and index information table respectively according to the extracted dimension ID and index ID.

And finally, carrying out anomaly analysis on the items to be analyzed according to the extracted relevant information of the dimension data, the relevant information of the index data and the attribute information. And then, sequentially and circularly executing the steps until the last analysis rule corresponding to the analysis template.

In this embodiment, when performing exception analysis on a to-be-analyzed item, information such as extracted information related to dimensional data, extracted information related to index data, and extracted attribute information may be formed into a Structured Query Language (SQL), and an analysis result is obtained by operating the SQL.

In an embodiment of the present invention, since the analysis result is finally sent to the service staff in the form of a mail, the mail may also be configured in advance, and specifically, the related information of the mail may be configured in a pre-created mail information table, and further, when the analysis result is sent to the preset service staff by the mail, the mail may be sent according to the content in the mail information table.

Firstly, a service person related to a project to be analyzed is used as a preset service person, and a recipient list is established according to the preset service person.

Then, the sending time of the mail is set, and the mail subject is determined according to the item to be analyzed.

And finally, configuring the sending time of the mail, the mail subject, the recipient list and the template ID of the analysis template into a pre-created mail information table. In addition, referring to fig. 2, a mail ID, a creation time of the information table, and an update time are also configured in the mail information table. One mail ID may correspond to one template ID, that is, mail information corresponding to one analysis template may be configured for one analysis template, such as the sending time of the mail, the mail subject, the recipient list, and the like.

If the analysis result shows that the item to be analyzed does not conform to at least one analysis rule in the analysis template, the sending time, the mail subject and the recipient list of the mail in the mail information table can be called, and when the sending time of the mail is reached, the analysis result, the link of the visual interface and other information are sent to each business person in the recipient list.

Referring to step S108 above, in an embodiment of the present invention, in order to make the analysis result sent to the service personnel easier for the service personnel to understand, the content of the analysis result may be summarized first, and then the summarized content is sent out by an email. Specifically, the embodiment of the present invention may preset a conclusion template, obtain corresponding conclusion report information by configuring the analysis result in the conclusion template, and send the conclusion report information to the service staff in the recipient list through the email when the sending time of the email is reached. In an embodiment of the present invention, when the analysis result is configured to the conclusion template, in order to facilitate business personnel to know the abnormal condition of the item to be analyzed in time, only the abnormal data that does not satisfy the analysis rule in the analysis result may be configured to the conclusion template to form the final conclusion report information.

In this embodiment, the relevant information of the conclusion template may also be pre-configured in the template information table, and then, after the analysis result is obtained, the conclusion template is called from the template information table and the analysis result is configured in the conclusion template.

It has been described above that a preset database (e.g., a preset data warehouse) contains a variety of basic data for analyzing items to be analyzed, i.e., analysis point-related data, and an application layer of the data warehouse develops a data table about the analysis point-related data at the time of creation of the data warehouse. The data related to the analysis points in the data warehouse can be reused subsequently for different items to be analyzed.

By way of a specific embodiment, when an item to be analyzed is a fluctuation of an active user for analysis of a mobile assistant application program, analysis points that need to perform exception analysis on the item to be analyzed may be roughly classified into a shallow analysis and a deep analysis. The shallow layer analysis aims to solve the problem that a user suddenly increases and decreases, and data fluctuation caused by data synchronization, calculation, dotting, product updating and operation strategies can be timely found. The deep analysis aims at analyzing the problem that the active users slowly decline and analyzing the reason of real loss of the users.

The shallow layer analysis mainly comprises three analysis points of self-checking, online user analysis and active user analysis.

Self-checking, and the specific analysis content comprises anti-cheating, qdas comparison, data synchronization and data calculation. Wherein, anti-cheating includes: the data fluctuation before anti-cheating is combined with the blacklist to be checked (attention needs to be paid to the influence of the kustory plug-in), and whether the data fluctuation is the blacklist can be positioned by combining history comparison; and each plug-in unit of the blacklist fluctuates, the plug-in unit with abnormal fluctuation needs to search specific rules, and specific problems are positioned through the rules. Compared with qdas, the fluctuation trend and amplitude can indicate that the dotting is not problematic to a certain extent. The data synchronization comprises the following steps: log collection questions, by querying the data center; and (5) solving the synchronous lysc problem of the shbt, comparing the sizes of the files on two sides, and warning by a mail at present. The data calculation comprises the following steps: checking a program running log; vertical collation data (from the bottom layer to the application layer).

And (3) online user analysis, wherein the specific analysis content comprises online general trend and online multi-dimensional analysis, and the online multi-dimensional analysis comprises analysis from dimensions such as brands, models, channels, solid versions and newly added users.

And analyzing the active users, wherein the specific analysis content comprises an active general trend and active multi-dimensional analysis, and the active multi-dimensional analysis comprises analysis from dimensions such as brands, models, channels, starting modes, solid versions and newly added users.

The deep analysis mainly comprises analysis of users in the sub-stream and analysis of other reasons.

The sub-stream user analysis mainly comprises a working day sub-stream for analyzing each behavior of a working day before loss, and a resting day sub-stream for analyzing each behavior of a resting day before loss.

Other reasons include mainly: the user requirements cannot be met, for example, the user searches for a mobile phone assistant but does not download the mobile phone assistant; the functions include functions of a popup window, push, charge protection, cleaning, floating ball and the like of a mobile phone assistant; the competitive products are analyzed according to the installation list of the application program; the user changes the mobile phone and analyzes according to the year of the mobile phone of the user; occupying memory space, and analyzing from the memory of the mobile phone of the user; the user has no requirement, such as no download or low download frequency.

In order to more clearly embody the embodiment of the present invention, the configuration process of the information table in the present invention is described with a specific embodiment, in which the information table is combined with the analysis point for analyzing the fluctuation of the active users.

First, the dimension data and the index data in the analysis points described above are respectively arranged in the dimension information table and the index information table. For example, the information such as a brand dimension Chinese name, a corresponding table name in a data warehouse, a corresponding field name and the like is configured in a dimension information table, and the information such as a Chinese name of an active user number index, a corresponding data warehouse field and the like is configured in an index information table. In addition, a dimension ID and an index ID are assigned to each of the dimension data and the index data, and the dimension ID and the index ID are also assigned to the dimension information table and the index information table, respectively.

It should be noted that, in the embodiment of the present invention, different dimension data and different index data in a preset database are obtained, an analysis rule is generated according to the obtained dimension data and index data, and then a plurality of analysis rules related to an item to be analyzed are selected from the generated analysis rules and combined into an analysis template. The analysis method can also be used for directly acquiring the dimension data and the index data related to the items to be analyzed when the data is acquired from the preset database, so that the analysis rules generated according to the acquired dimension data and the index data are the analysis rules related to the analysis items, and at the moment, part of the analysis rules can be selected to be combined into the analysis template, or all the analysis rules can be selected to be combined into the analysis template. This embodiment describes the latter case, and combines analysis templates directly using all of the generated analysis rules.

Then, analysis rules are generated according to the dimension data, the index data and the set attribute information, information such as rule ID is distributed to each analysis rule, and relevant information of the analysis rules is configured in a rule information table.

Further, a plurality of analysis rules are combined into an analysis template for the item to be analyzed, information such as a template ID is assigned to the analysis template, and information related to the analysis template is arranged in a template information table. The template information table can also be configured with information such as links of a visual interface, conclusion templates for summarizing analysis results in the following process, and the like.

Further, a correspondence relationship is established between the analysis template and the corresponding analysis rule, a relationship ID is generated, and information such as the relationship ID, the template ID, and the rule ID is arranged in the template rule correspondence table.

And finally, configuring information such as the mail title, the recipient list, the sending time and the like, and allocating a mail ID for the mail so as to configure the related information of the mail and the template ID of the analysis template corresponding to the mail into a mail information table.

The information configuration method and the information configuration device can configure corresponding information to the corresponding information table, can also perform interface configuration based on the visual interface of the visual platform, and can enable a user to visually see the configuration process of the information so as to facilitate the configuration of the information.

Based on the same inventive concept, an embodiment of the present invention further provides an automatic data analysis apparatus, and fig. 3 shows a schematic structural diagram of the automatic data analysis apparatus according to an embodiment of the present invention. Referring to fig. 3, the automatic data analysis apparatus 300 includes a generation module 310, a combination module 320, an analysis module 330, and a transmission module 340.

Now, the functions of the components or devices of the automatic data analysis apparatus 300 according to the embodiment of the present invention and the connection relationship between the components will be described:

the generating module 310 is adapted to obtain different dimensional data and different index data from a preset database, and generate an analysis rule according to the dimensional data and the index data;

a combination module 320, coupled to the generation module 310, adapted to select a plurality of analysis rules related to the item to be analyzed, and combine the selected plurality of analysis rules into an analysis template for the item to be analyzed;

the analysis module 330 is coupled with the combination module 320 and is adapted to perform anomaly analysis on the items to be analyzed by using the analysis rules in the analysis template to obtain an analysis result;

and the sending module 340 is coupled with the analysis module 330 and adapted to send the analysis result to a preset service staff through a mail if the analysis result indicates that the item to be analyzed does not conform to the corresponding analysis rule.

In an embodiment of the invention, the different dimension data includes at least one of a brand dimension, a version dimension, a model dimension, a firmware version dimension, and the like.

In an embodiment of the present invention, the different index data includes at least one of an active user number, a download user number, an online user number, a sub-streaming user, and the like.

Another automatic data analysis device is provided in the embodiment of the present invention, and fig. 4 is a schematic structural diagram of an automatic data analysis device according to an embodiment of the present invention. Referring to fig. 4, the automatic data analysis apparatus 300 includes a first configuration module 350 and a call module 360 in addition to a generation module 310, a combination module 320, an analysis module 330 and a transmission module 340.

The first configuration module 350 is coupled to the analysis module 330 and the sending module 340, respectively, and after the analysis module 330 performs anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template to obtain an analysis result, the analysis result is configured to the visualization platform.

And the sending module 340 is adapted to obtain the link of the visual interface in the visual platform and send the link to the preset service staff through the mail.

The calling module 360 is coupled with the sending module 340 and is adapted to call a visual interface in the visual platform when the link receives a click operation of a preset service worker, and display an analysis result on the visual interface.

Another automatic data analysis device is provided in the embodiment of the present invention, and fig. 5 is a schematic structural diagram of an automatic data analysis device according to an embodiment of the present invention. Referring to fig. 5, the automatic data analysis apparatus 300 includes a second configuration module 370 in addition to the above-described modules.

The second configuration module 370, coupled to the analysis module 330, is adapted to configure the relevant information of the dimension data to the pre-created dimension information table before performing anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template. And configuring the related information of the index data to a pre-created index information table. And configuring the related information of the analysis rule to a rule information table which is created in advance. And configuring the related information of the analysis template to a pre-created template information table. Establishing corresponding relation between a plurality of analysis rules and the analysis templates combined by the analysis rules, and configuring corresponding relation information to a pre-established template rule corresponding relation table.

In this embodiment, the generating module 310 is further adapted to set attribute information for determining whether the item to be analyzed conforms to the analysis rule according to the dimension data and the index data. And then constructing a corresponding analysis rule based on the dimension data, the index data and the attribute information of the analysis rule.

In an embodiment of the invention, the attribute information includes a comparison time and a lift type.

In another embodiment of the present invention, the attribute information may include at least one of a lower threshold, an upper threshold, a ranking limit, and the like, in addition to the comparison time and the type of ascent and descent.

In an embodiment of the present invention, the related information of the dimension data includes a dimension ID, a dimension name, a field name, and the like. The related information of the index data includes an index ID, an index name, a field name, and the like. The related information of the analysis rule includes a rule ID, a dimension ID of dimension data corresponding to the analysis rule, an index ID of corresponding index data, attribute information of the analysis rule, and the like. The related information of the analysis template includes a template ID and the like. The correspondence information includes a relationship ID, a template ID, and a rule ID of an analysis rule corresponding to the analysis template.

In an embodiment of the present invention, the analysis module 330 is further adapted to sequentially obtain rule IDs of a plurality of analysis rules corresponding to the analysis template according to the template rule correspondence table. And then calling a corresponding rule information table according to the rule IDs acquired in sequence, and extracting the dimension ID, the index ID and the attribute information of the analysis rule from the corresponding rule information table. And then, extracting the related information of other dimension data and the related information of other index data from the corresponding dimension information table and index information table respectively according to the dimension ID and the index ID. And finally, carrying out anomaly analysis on the items to be analyzed according to the extracted relevant information of the dimension data, the relevant information of the index data and the attribute information.

In an embodiment of the present invention, the second configuration module 370 is further adapted to, before the sending module 340 sends the analysis result to the preset service staff by email, regard the service staff related to the item to be analyzed as the preset service staff, and establish the recipient list according to the preset service staff. Setting the sending time of the mail and determining the mail subject according to the items to be analyzed. And configuring the sending time of the mail, the mail subject, the recipient list and the template ID of the analysis template into a pre-created mail information table.

In an embodiment of the present invention, the sending module 340 is further adapted to configure the analysis result into a preset conclusion template to obtain conclusion report information. And when the sending time of the mail is reached, sending the conclusion report information to business personnel in the recipient list through the mail.

According to any one or a combination of the above preferred embodiments, the following advantages can be achieved by the embodiments of the present invention:

in the embodiment of the invention, analysis rules are generated according to the dimension data and the index data in the preset database, a plurality of analysis rules related to the item to be analyzed are combined into an analysis template aiming at the item to be analyzed, the analysis rules in the analysis template can be further utilized to carry out abnormity analysis on the item to be analyzed, and if the analysis result shows that the item to be analyzed does not accord with the corresponding analysis rules, the analysis result can be sent to preset service personnel through a mail. Therefore, the analysis rules are combined into the analysis template, and the data items are analyzed by using the analysis template, so that the single-point monitoring (namely, the data items are analyzed from a single dimension, and one rule corresponds to one analysis template) and the overall analysis (namely, the data items are analyzed from multiple dimensions) can be met. A single analysis rule can also be configured into a plurality of different analysis templates, so that the analysis rule can be repeatedly utilized, and the rule development and calculation cost is reduced. Furthermore, when the analysis result is sent, the content of all the analysis results can be selected to be sent, and only the abnormal alarm content can be sent, so that the abnormal point in the service can be directly positioned, and the service personnel can be prevented from neglecting and checking the mail.

It is clear to those skilled in the art that the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and for the sake of brevity, further description is omitted here.

In addition, the functional units in the embodiments of the present invention may be physically independent of each other, two or more functional units may be integrated together, or all the functional units may be integrated in one processing unit. The integrated functional units may be implemented in the form of hardware, or in the form of software or firmware.

Those of ordinary skill in the art will understand that: the integrated functional units, if implemented in software and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computing device (e.g., a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention when the instructions are executed. And the aforementioned storage medium includes: u disk, removable hard disk, Read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disk, and other various media capable of storing program code.

Alternatively, all or part of the steps of implementing the foregoing method embodiments may be implemented by hardware (such as a computing device, e.g., a personal computer, a server, or a network device) associated with program instructions, which may be stored in a computer-readable storage medium, and when the program instructions are executed by a processor of the computing device, the computing device executes all or part of the steps of the method according to the embodiments of the present invention.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments can be modified or some or all of the technical features can be equivalently replaced within the spirit and principle of the present invention; such modifications or substitutions do not depart from the scope of the present invention.

The embodiment of the invention also provides A1 and an automatic data analysis method, which comprises the following steps:

A2, the method according to A1, wherein the method further comprises the following steps of after performing anomaly analysis on the item to be analyzed by using the analysis rules in the analysis template and obtaining an analysis result:

configuring the analysis results to a visualization platform;

A3, the method according to A1, wherein the generating of analysis rules according to the dimension data and the index data includes:

A4, the method according to A3, wherein the attribute information includes a contrast time and a lift type.

A5, the method according to A4, wherein the attribute information further includes:

at least one of a lower threshold, an upper threshold, a ranking limit.

A6, the method according to A3, wherein before the abnormal analysis of the item to be analyzed by the analysis rules in the analysis template, the method further comprises:

A7, the method according to A6, wherein,

the relevant information of the dimension data comprises a dimension ID, a dimension name and a field name;

the related information of the analysis template comprises a template ID;

A8, the method according to A7, wherein the abnormal analysis of the item to be analyzed by the analysis rules in the analysis template comprises:

A9, the method according to A7, wherein before sending the analysis result to the preset service staff by mail, the method further comprises:

A10, the method according to A9, wherein the sending the analysis result to the preset service staff by mail comprises:

A11, the method according to any one of A1-A10, wherein the different dimensional data includes at least one of: brand dimension, version dimension, model dimension, firmware version dimension.

A12, the method according to any one of A1-A10, wherein the different metric data comprises at least one of: the number of active users, the number of downloading users, the number of online users and the number of sub-streaming users.

B13, an automatic data analysis device, comprising:

B14, the device according to B13, wherein further comprising:

B15, the apparatus of B13, wherein the generating module is further adapted to:

B16, the device according to B15, wherein the attribute information includes contrast time and lift type.

B17, the apparatus according to B16, wherein the attribute information further includes:

at least one of a lower threshold, an upper threshold, a ranking limit.

B18, the device according to B15, wherein the device further comprises a second configuration module adapted to perform anomaly analysis on the item to be analyzed by using the analysis rules in the analysis template,

B19, the device according to B18, wherein,

the related information of the analysis template comprises a template ID;

B20, the apparatus according to B19, wherein the analysis module is further adapted to:

B21, the apparatus of B20, wherein the second configuration module is further adapted to:

B22, the apparatus of B21, wherein the transmitting module is further adapted to:

B23, the apparatus according to any one of B13-B22, wherein the different dimensional data includes at least one of: brand dimension, version dimension, model dimension, firmware version dimension.

B24, the device according to any one of B13-B22, wherein the different metric data comprise at least one of: the number of active users, the number of downloading users, the number of online users and the number of sub-streaming users.

C25, a computer storage medium storing computer program code which, when run on a computing device, causes the computing device to perform the automatic data analysis method of any one of a1-a 12.

D26, a computing device, comprising: a processor; a memory storing computer program code; the computer program code, when executed by the processor, causes the computing device to perform the automated data analysis method of any of a1-a 12.

Claims

1. An automated data analysis method, comprising:

2. The method of claim 1, wherein after performing anomaly analysis on the item to be analyzed by using the analysis rule in the analysis template to obtain an analysis result, the method further comprises:

configuring the analysis results to a visualization platform;

3. The method of claim 1, wherein generating an analysis rule from the dimensional data and metric data comprises:

4. The method of claim 3, wherein the attribute information includes a contrast time and a lift type.

5. The method of claim 4, wherein the attribute information further comprises:

at least one of a lower threshold, an upper threshold, a ranking limit.

6. The method of claim 3, wherein before performing the anomaly analysis on the item to be analyzed by using the analysis rules in the analysis template, the method further comprises:

7. The method of claim 6, wherein,

the related information of the analysis template comprises a template ID;

8. An automated data analysis apparatus comprising:

9. A computer storage medium having computer program code stored thereon which, when run on a computing device, causes the computing device to perform the automated data analysis method of any of claims 1-7.

10. A computing device, comprising: a processor; a memory storing computer program code; the computer program code, when executed by the processor, causes the computing device to perform the automatic data analysis method of any of claims 1-7.