CN112632353A - Big data classification method for business management - Google Patents
Big data classification method for business management Download PDFInfo
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- CN112632353A CN112632353A CN202110019370.XA CN202110019370A CN112632353A CN 112632353 A CN112632353 A CN 112632353A CN 202110019370 A CN202110019370 A CN 202110019370A CN 112632353 A CN112632353 A CN 112632353A
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- 238000000034 method Methods 0.000 title claims abstract description 21
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- 238000003860 storage Methods 0.000 claims abstract description 13
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000000513 principal component analysis Methods 0.000 claims description 5
- 238000007726 management method Methods 0.000 abstract description 43
- 238000013500 data storage Methods 0.000 abstract description 6
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- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
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Abstract
The invention belongs to the technical field of big data management, in particular to a big data classification method for business management, which comprises the following steps: step S1, configuring a data feature extraction training set corresponding to the business management big data, satisfying feature extraction of the business management big data and outputting an identification result; step S2, configuring the processing authority level corresponding to the output identification result, and configuring the corresponding identification label for the business management big data according to the processing authority level; and step S3, establishing a data classification storage structure corresponding to the data feature extraction training set. According to the method, big data are classified and processed based on the processing authority and the corresponding identification tags, the identification result output comprises data content, data types and data value grades, the processed data are accessed according to the authority grades of workers, the time for data screening and cleaning by technicians is saved, data loss or theft is effectively prevented, the requirement of data storage is met, and meanwhile, the classified safety management of the big data is realized.
Description
Technical Field
The invention relates to the technical field of big data management, in particular to a big data classification method for business management.
Background
The big data is a data set which is large in scale and greatly exceeds the capability range of the traditional database software tools in the aspects of acquisition, storage, management and analysis, and has the four characteristics of massive data scale, rapid data circulation, various data types and low value density. In other words, if big data is compared to an industry, the key to realizing profitability in the industry is to improve the "processing ability" of the data and realize the "value-added" of the data through the "processing".
With the advent of the cloud era, big data has attracted more and more attention. Analyst teams believe that large data is often used to describe the large amount of unstructured and semi-structured data created by a company that can take excessive time and money to download to a relational database for analysis. Big data analysis is often tied to cloud computing because real-time large dataset analysis requires a MapReduce-like framework to distribute work to tens, hundreds, or even thousands of computers.
The existing big data classification mode for business management is only used for conveniently storing data, but does not provide any help for management after data storage, technicians still need to screen and clean data from massive data, the data storage capacity is large and complicated, the safety is low, the follow-up safe and reliable management of big data is not facilitated, and the problem of data loss caused by database crash is easily caused.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a big data classification method for business management, which solves the problems that the existing big data classification method for business management is only convenient for storing data, does not provide any help for management after data storage, technicians still need to screen and clean data from massive data, the data storage capacity is large and complicated, the safety is low, the subsequent safe and reliable management of big data is not facilitated, and data loss is easily caused by database crash.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: a big data classification method for business management comprises the following steps:
step S1, configuring a data feature extraction training set corresponding to the business management big data, satisfying feature extraction of the business management big data and outputting an identification result;
step S2, configuring the processing authority level corresponding to the output identification result, and configuring the corresponding identification label for the business management big data according to the processing authority level;
step S3, establishing a data classification storage structure corresponding to the data feature extraction training set;
s4, acquiring a data source, extracting a training set according to the data characteristics of the S1 step and outputting a recognition result, and simultaneously outputting a recognition label corresponding to the business management big data according to the processing authority level of the S2 step;
and step S5, analyzing the identification result according to the data classification storage structure of the step S3, and classifying and storing the obtained business management big data according to the analysis result.
As a preferred technical solution of the present invention, the configuring step of the data feature extraction training set comprises: and establishing a data feature extraction training model, extracting the data features of the big data for business management according to the data feature extraction training model, and outputting a recognition result through judgment and recognition.
As a preferred technical scheme of the invention, the data feature extraction training set uses a Principal Component Analysis (PCA) method for feature extraction.
As a preferred technical solution of the present invention, the identification result includes data content, data type, and data value level, and the processing permission level is set according to the data value level.
As a preferred technical solution of the present invention, the processing permission level includes a low level permission, a medium level permission and a high level permission, and the corresponding first level tag, second level tag and third level tag are configured according to the permission level, and the permission level of the user can only identify the corresponding level and the identification tags below the corresponding level, so as to obtain the large data for business management in classified storage limited by the corresponding permission.
As a preferred technical solution of the present invention, when the user acquires the big data for business management stored in a classified manner, the user first needs to perform identity recognition, and the identity recognition mode includes one or more combinations of face recognition, fingerprint recognition, and iris recognition.
(III) advantageous effects
Compared with the prior art, the big data classification method for business management provided by the invention has the following beneficial effects:
according to the big data classification method for business management, big data classification processing is carried out based on processing authority and corresponding identification tags, the identification result output comprises data content, data types and data value grades, the processed data are accessed according to the authority grades of workers, the time for data screening and cleaning of technicians is saved, data loss or theft is effectively prevented, and the classified safety management of the big data is realized while the data storage is met.
Drawings
FIG. 1 is a schematic diagram illustrating steps of a big data classification method for business management according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Examples
Referring to fig. 1, the present invention provides the following technical solutions: a big data classification method for business management comprises the following steps:
step S1, configuring a data feature extraction training set corresponding to the business management big data, satisfying feature extraction of the business management big data and outputting an identification result;
step S2, configuring the processing authority level corresponding to the output identification result, and configuring the corresponding identification label for the business management big data according to the processing authority level;
step S3, establishing a data classification storage structure corresponding to the data feature extraction training set;
s4, acquiring a data source, extracting a training set according to the data characteristics of the S1 step and outputting a recognition result, and simultaneously outputting a recognition label corresponding to the business management big data according to the processing authority level of the S2 step;
and step S5, analyzing the identification result according to the data classification storage structure of the step S3, and classifying and storing the obtained business management big data according to the analysis result.
Specifically, the configuration step of the data feature extraction training set comprises the following steps: and establishing a data feature extraction training model, extracting the data features of the big data for business management according to the data feature extraction training model, and outputting a recognition result through judgment and recognition.
Specifically, the data feature extraction training set uses PCA principal component analysis for feature extraction.
Specifically, the identification result includes data content, data type and data value grade, and the processing authority grade is set according to the data value grade.
Specifically, the processing permission levels include a low-level permission, a middle-level permission and a high-level permission, corresponding first-level tags, second-level tags and third-level tags are configured according to the permission levels, and the permission levels of the users can only identify the corresponding levels and the identification tags below the corresponding levels, so that the large data for business management, which are restricted by the corresponding permissions and complete classified storage, can be obtained.
In this embodiment, the access and processing authority of the corresponding big data for business management, which can be obtained by the user, is determined according to the own authority of the user, and the higher the authority of the user is, the higher the processing authority level is, for example, when the authority level of the user is in a high level, the user states that the processing authority level is a high level authority, masters the highest processing authority, and has a secret key for identifying a first-level label, a second-level label and a third-level label, while the user with the middle-level authority only has low and middle-level authorities, and only can identify the first-level label and the second-level label, but does not have the function of processing the big data for.
Specifically, when the user acquires the large data for business management stored in a classified manner, the user first needs to perform identity recognition in a manner of one or more combinations of face recognition, fingerprint recognition, and iris recognition.
In the embodiment, the user identity can be identified by adopting an identity identification mode, and the user identity is authenticated by one or more combined identification modes of face identification, fingerprint identification and iris identification, so that misuse or invasion of personnel in a non-system to access data is avoided, and the data security is further ensured.
The working principle and the using process of the invention are as follows: firstly, configuring a data feature extraction training set corresponding to the business management big data to meet the feature extraction of the business management big data and output an identification result; configuring a processing authority level corresponding to the output identification result, and configuring a corresponding identification tag for the business management big data according to the processing authority level; establishing a data classification storage structure corresponding to the data feature extraction training set; when data source acquisition data is acquired, extracting a training set according to data characteristics and outputting an identification result, and outputting an identification label corresponding to the big data for business management according to a processing authority level; and finally, analyzing the identification result according to the data classified storage structure, and classifying and storing the acquired big data for business management according to the analysis result.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A big data classification method for business management is characterized in that: the method comprises the following steps:
step S1, configuring a data feature extraction training set corresponding to the business management big data, satisfying feature extraction of the business management big data and outputting an identification result;
step S2, configuring the processing authority level corresponding to the output identification result, and configuring the corresponding identification label for the business management big data according to the processing authority level;
step S3, establishing a data classification storage structure corresponding to the data feature extraction training set;
s4, acquiring a data source, extracting a training set according to the data characteristics of the S1 step and outputting a recognition result, and simultaneously outputting a recognition label corresponding to the business management big data according to the processing authority level of the S2 step;
and step S5, analyzing the identification result according to the data classification storage structure of the step S3, and classifying and storing the obtained business management big data according to the analysis result.
2. The big data classifying method for business management as claimed in claim 1, wherein: the data feature extraction training set configuration step comprises: and establishing a data feature extraction training model, extracting the data features of the big data for business management according to the data feature extraction training model, and outputting a recognition result through judgment and recognition.
3. The big data classifying method for business management as claimed in claim 1, wherein: the data feature extraction training set uses PCA principal component analysis for feature extraction.
4. The big data classifying method for business management as claimed in claim 1, wherein: the identification result comprises data content, data type and data value grade, and the processing authority grade is set according to the data value grade.
5. The big data classifying method for business management as claimed in claim 1, wherein: the processing authority level comprises a low-level authority, a middle-level authority and a high-level authority, corresponding first-level labels, second-level labels and third-level labels are configured according to the authority level, and the authority level of the user can only identify the corresponding level and the identification labels below the corresponding level, so that the large data for business management which is limited by the corresponding authority and finishes classified storage is obtained.
6. The big data classifying method for business management as claimed in claim 1, wherein: when the user acquires the large data for business management stored in a classified manner, identity recognition is first required, and the identity recognition mode comprises one or more combinations of face recognition, fingerprint recognition and iris recognition.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106682527A (en) * | 2016-12-25 | 2017-05-17 | 北京明朝万达科技股份有限公司 | Data security control method and system based on data classification and grading |
| CN107229743A (en) * | 2017-06-21 | 2017-10-03 | 刘晨曦 | A kind of business management big data classified use method and system |
| CN108182368A (en) * | 2017-12-27 | 2018-06-19 | 武汉摩索科技有限公司 | A kind of business management big data classified use method and system |
| US20190164062A1 (en) * | 2017-11-28 | 2019-05-30 | International Business Machines Corporation | Data classifier |
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- 2021-01-07 CN CN202110019370.XA patent/CN112632353A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106682527A (en) * | 2016-12-25 | 2017-05-17 | 北京明朝万达科技股份有限公司 | Data security control method and system based on data classification and grading |
| CN107229743A (en) * | 2017-06-21 | 2017-10-03 | 刘晨曦 | A kind of business management big data classified use method and system |
| US20190164062A1 (en) * | 2017-11-28 | 2019-05-30 | International Business Machines Corporation | Data classifier |
| CN108182368A (en) * | 2017-12-27 | 2018-06-19 | 武汉摩索科技有限公司 | A kind of business management big data classified use method and system |
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Application publication date: 20210409 |