CN115935235A - Big data decision analysis method and flow based on data middlebox - Google Patents
Big data decision analysis method and flow based on data middlebox Download PDFInfo
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Abstract
The invention provides a big data decision analysis method and a big data decision analysis process based on a data middlebox, and relates to the technical field of big data market analysis. The big data decision analysis method and the big data decision analysis process based on the data middlebox comprise the following steps: s1, data are hierarchically used on a data center, data in different fields are optimized and integrated and knowledge is precipitated in a modeling mode, and data encapsulation operation is completed by means of data service, so that diversified data application requirements are effectively met. The invention can promote various services to develop towards the direction of datamation, is beneficial to improving the data asset value and accelerating the interconnection and intercommunication of data information, so that the development trend of a big data era is followed, the data priority principle is continuously adhered to, the data management is highly emphasized and various application modes are mutually fused under the guidance of the service value, thereby effectively completing the construction work of a data center and a big data center and fully exerting the due effectiveness of the data center.
Description
Technical Field
The invention relates to the technical field of big data market analysis, in particular to a big data decision analysis method and a big data decision analysis process based on a data middlebox.
Background
Big data, or mass data, refers to the data that is too large to be captured, managed, processed and organized into information that can help enterprise business decision more actively within a reasonable time through the current mainstream software tools.
Since the strategy idea of the middle station proposed by the Alibara, following the development trend of the big data era, the calling between the middle station and the big data center in the data construction is higher and higher, and the data asset value is fully revealed by performing data processing on all services and performing decision analysis on related big data.
At present, the research quantity of data middleboxes and big data centers in China is relatively small, big data is lack of data quality improvement, effective processing analysis and decision analysis, and therefore results presented after search by users are unsatisfactory.
Therefore, those skilled in the art provide a big data decision analysis method and flow based on the data center to solve the above problems in the background art.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a big data decision analysis method and a big data decision analysis process based on a data center, which can promote the development of various services towards the direction of datamation, are beneficial to improving the data asset value, accelerate the interconnection and intercommunication of data information, enable the big data decision analysis method to follow the development trend of the big data era, continuously adhere to the data priority principle, highly attach importance to data governance and mutually fuse various application modes under the guidance of the service value, thereby effectively completing the construction work of the data center and the big data center, fully exerting the due utility of the data center, and solving the problems that the research quantity of the data center and the big data center is relatively small, the big data is lack of improving the data quality, effectively performing processing analysis and lacking decision analysis, and the result presented after searching for a user is unsatisfactory.
(II) technical scheme
In order to realize the purpose, the invention is realized by the following technical scheme:
a big data decision analysis method and a big data decision analysis process based on a data center station comprise the following steps:
s1, data layering
The data center is used for optimizing and integrating data in different fields and precipitating knowledge by utilizing a modeling mode, and data encapsulation operation is completed by relying on data service, so that diversified data application requirements are effectively met;
s2, defining data specification
The data center station needs to perform the specification definition on the data after performing the hierarchical planning on the data. Namely, a bus matrix is established by utilizing a dimensional modeling mode, and a data domain, a business process and the like are clearly defined. The index composition system can be generally subdivided into a plurality of components including atoms and derived indices, modification types and modifiers, and the like;
s3, data dimension modeling
And according to the specific standard definition, building a data dimension model by combining with the data analysis decision demand, and providing an optimized demand analysis service for the user by utilizing a model calculation mode. Firstly, when combing the service, the data field should abstract the process and dimension of the whole service step by step; secondly, creating a fact table according to the relevance between the business process based on the data domain and each dimension, wherein the table needs to contain all facts about the business process;
s4, data asset management
Various services are presented in a data form by utilizing a data center and a big data center, so that the services become precious service data assets, and users can enjoy various data application services including information management, data storage and the like under the condition of fully utilizing the services;
s5, data acquisition and processing
The method comprises the following steps that a data center platform and a big data center are utilized to tightly combine the data center platform with a service scene, knowledge and data are intentionally precipitated in the whole business operation process, various service data are collected in a classified mode around specific core services, and the collected data are collected, sorted and stored;
s6, data analysis
By using specialized data analysis software and a matched tool, modeling and accurate calculation are quickly carried out on various collected business data, and the core data value is extracted from the business data, so that related workers can make a scientific and reasonable decision-making decision by combining the obtained data analysis calculation results;
s7. Decision analysis
And performing decision analysis on the data through a mobile terminal or a control terminal, wherein the big data decision analysis comprises big data visualization, business scene visualization, decision analysis and other modes.
Preferably, the data center platform refers to a platform which can effectively realize data division and horizontal decoupling and has a function of effectively precipitating public data by utilizing technologies including big data technology and various professional tool software.
Preferably, when the data center and the big data center are constructed, the data priority principle needs to be always firmly trusted, and on the basis of correctly recognizing the asset value of the data, a data architecture suitable for the data center and the big data center is selected according to the actual situation, such as FEAF and the like, market and customer requirements are deeply known, various related data information is collected, and the big data center is used for carrying out layering and modeling calculation on the data structure, so that accurate positioning is realized, various marketing activities are reasonably developed, and more high-quality customers are attracted.
Preferably, in the step S5, during the data acquisition and processing, a data encryption technology, a data security protection technology, and the like should be actively introduced into the data acquisition and processing, for example, firewall software is additionally installed in the big data center, data with a higher importance level therein is encrypted, and the like, and meanwhile, the whole process of data acquisition, analysis processing, storage, and the like is monitored in real time by using an advanced intelligent monitoring system, so as to effectively ensure data security and privacy of user data.
Preferably, in the step S6, when data analysis is performed, different data application modes need to be actively fused with each other, for example, a Hadoop data structure is adopted, and a business intelligence system is applied to optimize and integrate a data platform for processing online transactions and other data platforms for analyzing business transaction types, making business decisions, and the like, and originally dispersed data platforms with single functions are fused into a complete big data middle platform, so that all the services such as data acquisition, data trend analysis, business decision making, and the like can be completed in the same big data middle platform.
Preferably, in the decision analysis process in step S7, five analysis modules are set by setting a plurality of analysis dimensions including wireless and PC, site, page, and the like, and the five analysis modules respectively include an overall profile, a page click, a user analysis, a path analysis, and a guidance link, and each analysis module is further refined, for example, the user analysis can be subdivided into a basic analysis and a multidimensional analysis, and the path analysis can be subdivided into a multi-step path and a source heading. Browsing, guiding, interacting and retaining are used as main analysis indexes, objective analysis and evaluation are carried out on user acceptance and participation, the capacity of content retaining users and the like, and data center asset management is carried out in a targeted mode.
Preferably, the big data decision analysis middle platform system based on the data middle platform comprises a table data model, and the table data model is sequentially divided into a data operation layer, a common dimension model layer and an application data layer. The data operation layer positioned at the bottommost layer in the table data model is directly accessed with data generated by each terminal and each service system, such as news access numbers, click numbers and the like, by using a synchronous task mode, and then is accessed into a corresponding data computing platform according to the specific type of the data, and is connected with the middle layer of the application layer and the source data layer, wherein the middle layer mainly comprises various service data such as advertisements, users, columns and the like, and a solid foundation is laid for the subsequent data service application by uniformly storing various detailed fact data, dimension table data and the like in the middle layer.
Preferably, the application data layer of the system is responsible for calculating various service data, and performing data assembly and processing according to specific service requirements, so as to provide real data application services such as news columns and advertisements for broad audiences.
(III) advantageous effects
The invention provides a big data decision analysis method and a big data decision analysis process based on a data middlebox. The method has the following beneficial effects:
1. the invention provides a big data decision analysis method and a big data decision analysis process based on a data center, which promote the development of various services towards the direction of datamation by constructing and using the big data center and the big data center, are beneficial to improving the data asset value and accelerating the interconnection and intercommunication of data information, so that the method follows the development trend of the big data era and continues to adhere to the data priority principle, highly emphasizes data management and mutually fuses various application modes under the guidance of the service value, thereby effectively completing the construction work of the data center and the big data center and fully exerting the due utility of the data center.
2. The invention provides a big data decision analysis method and a big data decision analysis process based on a data center, which can effectively help people to correctly know the data center and a big data center, indicate the construction significance of the data center and the big data center by combining related application practice cases, fully exert the advantages and the effects of the data center and the big data center for effectively constructing the data center and the big data center, and promote the long-term stable development of various industries based on corresponding practice guidance and help.
3. The invention provides a big data decision analysis method and a big data decision analysis process based on a data middlebox, which can promote the efficient convergence, collaborative development and reasonable utilization of data resources of industries and enterprises by identifying and analyzing big data, and reduce the difficulty of developing data sharing and exchange among enterprises; the industry and enterprise common problems can be refined into problems which can be solved by identification analysis through big data analysis and decision making of the industry and enterprise, decision making information is pushed to the enterprise through data analysis and visual portrayal in a big data decision making analysis mode, an effective solution is provided for the industry and enterprise, and the digital transformation of the enterprise is effectively promoted.
Drawings
FIG. 1 is a flow chart of a data decision analysis method of the present invention;
FIG. 2 is a schematic structural diagram of a big data decision analysis center system 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.
The embodiment is as follows:
as shown in fig. 1-2, an embodiment of the present invention provides a big data decision analysis method and a flow based on a data middlebox, including the following steps:
s1, data layering
The data center is used for optimizing and integrating data in different fields and settling knowledge by utilizing a modeling mode and completing data encapsulation operation by relying on data service, so that diversified data application requirements are effectively met;
s2, defining data specification
The data center station needs to perform the specification definition on the data after performing the hierarchical planning on the data. Namely, a bus matrix is established by utilizing a dimensional modeling mode, and a data domain, a business process and the like are clearly defined. The index composition system can be generally subdivided into a plurality of components including atoms and derived indices, modification types and modifiers, and the like;
s3, data dimension modeling
And according to the specific standard definition, building a data dimension model by combining with the data analysis decision demand, and providing an optimized demand analysis service for the user by utilizing a model calculation mode. Firstly, when the service is combed, the data field should gradually abstract the process and dimension of the whole service; secondly, creating a fact table according to the relevance between the business process based on the data domain and each dimension, wherein the table needs to contain all facts about the business process;
s4, data asset management
Various services are presented in a data form by utilizing a data center and a big data center, so that the services become precious service data assets, and users can enjoy various data application services including information management, data storage and the like under the condition of fully utilizing the services;
s5, data acquisition and processing
Tightly combining the data middlebox and the service scenes by using the data middlebox and the big data center, consciously precipitating knowledge and data in the whole business operation process, classifying and collecting each service data around a specific core service, and summarizing, sorting and storing the service data;
in the process of data acquisition and processing, a data encryption technology, a data security protection technology and the like are actively introduced, for example, firewall software is additionally installed in a big data center, data with higher importance level in the big data center is encrypted and processed, and meanwhile, an advanced intelligent monitoring system is used for monitoring the whole processes of data acquisition, analysis processing, storage and the like in real time, so that the data security and the privacy of user data are effectively guaranteed.
S6, data analysis
By using specialized data analysis software and a matched tool, modeling and accurate calculation are rapidly carried out on various collected service data, and the core data value is extracted, so that related workers can make a scientific and reasonable decision by combining the obtained data analysis calculation results;
when data analysis is carried out, different data application modes need to be actively fused with each other, for example, a Hadoop data structure is adopted, a business intelligent system is applied, a data platform for processing online transactions and other various data platforms for analyzing business transaction types, making business decisions and the like are optimized and integrated, originally scattered data platforms with single functions are fused into a complete big data middle platform, and all businesses such as data acquisition, data trend analysis, business decision making and the like can be completed in the same big data middle platform.
S7, decision analysis
Performing decision analysis on data through a mobile terminal or a control terminal, wherein the big data decision analysis comprises big data visualization, business scene visualization, decision analysis and other modes;
in the process of decision analysis, five analysis modules are set by setting a plurality of analysis dimensions including wireless and PC, sites, pages and the like, wherein the five analysis modules are respectively a whole profile, a page click, user analysis, path analysis and a guide link, and each analysis module is further refined. Browsing, guiding, interacting and retaining are used as main analysis indexes, objective analysis and evaluation are carried out on user acceptance and participation, the capacity of content retaining users and the like, and data center asset management is carried out in a targeted mode.
The data center platform is a platform which can effectively realize data division and horizontal decoupling by utilizing the technologies including big data and various professional tool software and has the function of effectively precipitating public data.
When a data center and a big data center are built, a data priority principle needs to be always firmly trusted, and on the basis of correctly recognizing the asset value of data, a data architecture suitable for the data center and the big data center is selected according to actual conditions, such as FEAF and the like, market and customer requirements are deeply known, various related data information is collected, and the big data center is used for carrying out layering and modeling calculation on the data architecture, so that accurate positioning is realized, various marketing activities are reasonably developed, and more high-quality customers are attracted.
A big data decision analysis middle platform system based on a data middle platform comprises a table data model which is sequentially divided into a data operation layer, a common dimension model layer and an application data layer. The data operation layer positioned at the bottommost layer in the table data model is directly accessed with data generated by each terminal and each service system, such as news access numbers, click numbers and the like, by using a synchronous task mode, and then is accessed into a corresponding data computing platform according to the specific type of the data, and is connected with the middle layer of the application layer and the source data layer, wherein the middle layer mainly comprises various service data such as advertisements, users, columns and the like, and a solid foundation is laid for the subsequent data service application by uniformly storing various detailed fact data, dimension table data and the like in the middle layer;
the application data layer of the system is responsible for calculating various service data, and carrying out data assembly and processing according to specific service requirements, thereby providing real data application services such as news columns, advertisements and the like for broad audiences.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A big data decision analysis method and a big data decision analysis process based on a data center station are characterized by comprising the following steps:
s1, data layering
The data center is used for optimizing and integrating data in different fields and settling knowledge by utilizing a modeling mode and completing data encapsulation operation by relying on data service, so that diversified data application requirements are effectively met;
s2, defining data specification
After the data are hierarchically planned, the data center station needs to carry out standard definition on the data;
namely, a bus matrix is established by utilizing a dimensional modeling mode, and a data domain, a business process and the like are clearly defined;
the index composition system can be generally subdivided into a plurality of components including atoms and derived indices, modification types and modifiers, and the like;
s3, modeling of data dimension
According to the specific standard definition, a data dimension model is built in combination with data analysis decision requirements, and an optimized requirement analysis service is provided for a user by utilizing a model calculation mode;
firstly, when combing the service, the data field should abstract the process and dimension of the whole service step by step; secondly, creating a fact table according to the relevance between the business process based on the data domain and each dimensionality, wherein the table needs to contain all facts about the business process;
s4, data asset management
Various services are presented in a data form by utilizing a data center and a big data center, so that the services become precious service data assets, and users can enjoy various data application services including information management, data storage and the like under the condition of fully utilizing the services;
s5, data acquisition and processing
The method comprises the following steps that a data center platform and a big data center are utilized to tightly combine the data center platform with a service scene, knowledge and data are intentionally precipitated in the whole business operation process, various service data are collected in a classified mode around specific core services, and the collected data are collected, sorted and stored;
s6, data analysis
By using specialized data analysis software and a matched tool, modeling and accurate calculation are rapidly carried out on various collected service data, and the core data value is extracted, so that related workers can make a scientific and reasonable decision by combining the obtained data analysis calculation results;
s7. Decision analysis
And performing decision analysis on the data through a mobile terminal or a control terminal, wherein the big data decision analysis comprises big data visualization, business scene visualization, decision analysis and the like.
2. The big data decision analysis method and process based on the data center as claimed in claim 1, wherein the data center refers to a platform which can effectively realize data separation and horizontal decoupling and has a function of effectively precipitating public data by using techniques including big data technology and various specialized tool software.
3. The big data decision analysis method and process based on the data center as claimed in claim 1, wherein the data center and the big data center need to always maintain the data priority principle when they are built, and need to select a suitable data architecture according to the actual situation, such as FEAF, to further understand the market and customer requirements, to collect various related data information, and to use the big data center to perform layering and modeling calculation, thereby realizing accurate positioning, developing various marketing activities reasonably, and attracting more high-quality customers.
4. The big data decision analysis method and process based on the data center station as claimed in claim 1, wherein in the data collection and processing process in step S5, a data encryption technology, a data security protection technology, etc. should be actively introduced into the big data center station, for example, firewall software is added in the big data center station to encrypt data with higher importance level, etc. and an advanced intelligent monitoring system is used to monitor the whole data collection, analysis, storage, etc. process in real time, so as to effectively guarantee data security and privacy of user data.
5. The big data decision analysis method and process based on data middleboxes as claimed in claim 1, wherein in step S6, during data analysis, different data application modes need to be actively fused with each other, for example, a Hadoop data structure is adopted, and a business intelligence system is applied to optimize and integrate a data platform for processing online transactions and other data platforms for analyzing business transaction types, making business decisions, and the like, and originally dispersed data platforms with single functions are fused into a complete big data middlebox, so that all the businesses such as data collection, data trend analysis, business decision making, and the like can be completed in the same big data middlebox.
6. The big data decision analysis method and process based on the data center of claim 1, wherein in the decision analysis in step S7, by setting a plurality of analysis dimensions including wireless and PC, site, page, etc., five analysis modules are set, which are respectively an overall profile, a page click, a user analysis, a path analysis and a guidance link, and each analysis module is further refined, if the user analysis can be subdivided into a basic analysis and a multidimensional analysis, the path analysis can be subdivided into a plurality of steps of path and source heading;
browsing, guiding, interacting and retaining are used as main analysis indexes, objective analysis and evaluation are carried out on user acceptance and participation, the capacity of content retaining users and the like, and data center asset management is carried out in a targeted mode.
7. The big data decision analysis middleware system based on data middleware as claimed in any of claims 1-6, wherein the middleware system comprises a table data model, and the table data model is divided into a data operation layer, a common dimension model layer and an application data layer in sequence;
the data operation layer positioned at the bottommost layer in the table data model is directly accessed with data generated by each terminal and each service system, such as news access numbers, click numbers and the like, by using a synchronous task mode, and then is accessed into a corresponding data computing platform according to the specific type of the data, and is connected with the middle layer of the application layer and the source data layer, wherein the middle layer mainly comprises various service data such as advertisements, users, columns and the like, and a solid foundation is laid for the subsequent data service application by uniformly storing various detailed fact data, dimension table data and the like in the middle layer.
8. The big data decision analysis middlebox system based on a data middlebox as claimed in claim 7, wherein an application data layer of the system is responsible for calculating various service data, and performing data assembly and processing according to specific service requirements, so as to provide real data application services such as news columns and advertisements for broad audiences.
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| CN116522095B (en) * | 2023-06-30 | 2023-09-08 | 中交第四航务工程勘察设计院有限公司 | Main data management method based on data center |
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