CN103577605A - Data warehouse based on data fusion and data mining and application method of data warehouse - Google Patents
Data warehouse based on data fusion and data mining and application method of data warehouse Download PDFInfo
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Abstract
The invention discloses a data warehouse based on data fusion and data mining and an application method of the data warehouse. The data warehouse mainly solves the problems that in the prior art, a data warehouse cannot meet requirements of users for reliability, consistency and sharing performance of storage and extraction of large amounts of data information. The data warehouse comprises a data extraction layer, a data storage layer and a data access layer, wherein the data extraction layer is used for extracting data in online transaction processing system, an external data source and off-line data storage media and leading the extracted data into the data storage layer; the data storage layer comprises an ODS used for storing the data which are subject-oriented, integrated and current or close to the current and constantly change, an EDW storing enterprise-level data and a data mart; the data access layer is used for accessing data in the data storage layer in a statement, image or data analysis mode and carrying out analysis prediction. According to the data warehouse based on data fusion and data mining and the application method, the aim of storing and accessing data safely, reliably and conveniently is achieved, and the data warehouse has high practical value and popularization value.
Description
Technical field
The present invention relates to a kind of data warehouse, specifically, relate to a kind of data warehouse and application process thereof based on data fusion and data mining.
Background technology
Along with develop rapidly and computer technology the popularizing in electric system of power industry, dispatching automation, energy management system (EMS) and geographic information management system (GIS) etc. have obtained application more and more widely in electrical network.How the continuous expansion of electrical network scale make magnanimity, time become and Mobile data carries out overall treatment, and the data that collect are carried out to data fusion and data mining becomes the focus of paying close attention in electric system.Due to constantly improving and the application of computer networking technology and distributed frame of Automation of Electric Systems management system function, pending data message amount is increased greatly, people have higher requirement to the reliability of data message, consistance and sharing, how better to utilize and manage these day by day huge isomorphism and heterogeneous databases, and excavate the potential contact between data, help the better analysis and decision of enterprise, become Utilities Electric Co.'s problem day by day in the urgent need to address.Therefore, how data effectively being collected, store and to be extracted is research emphasis and the difficult point of data warehouse technology.
Summary of the invention
The object of the present invention is to provide a kind of data warehouse and application process thereof based on data fusion and data mining, mainly solve the data warehouse existing in prior art and can not meet the problem of user to the requirement of reliability, consistance and the sharing of the storage of mass data information and extraction.
To achieve these goals, the technical solution used in the present invention is as follows:
Data warehouse based on data fusion and data mining, comprising:
Data pick-up layer: the data in the data storage medium of extraction online transaction processing system, external data source and off line, and by the data importing data storage layer extracting;
Data storage layer: comprise subject-oriented, integrated, current or approach the ODS that data current, that constantly change are stored, the EDW that Enterprise Data is stored, and Data Mart;
Data access layer: the mode with form, figure or data analysis conducts interviews to the data in data storage layer, and carry out analyses and prediction.
Specifically, described data pick-up layer by interconnected, copy, the mode of increment, conversion, scheduling and monitoring extracts data.
Further, in described data storage layer, ODS carries out short-term storage by the data after extracting; EDW carries out longer-term storage by the data after extracting; Data Mart will be stored after Organization of Data according to user's request.
In the present invention, disclose a kind of application process of the above-mentioned data warehouse based on data fusion and data mining, comprised the following steps:
(1) data pick-up layer is browsed and pre-service the data in the data storage medium of online transaction processing system, external data source and off line, and pretreated data are extracted and merge processing;
(2) data storage layer is combined the data analysis in data pick-up layer and excavate by association analysis, sequence pattern analysis, classification analysis and cluster analysis, and the Data classification of excavation is stored in ODS, EDW or Data Mart;
(3) user inputs data access request at data access layer, and data access layer determines that according to the type of the request of access of user's input from ODS, EDW or Data Mart, extracting corresponding data shows.
Further, in described step (1), adopt multisource data fusion technology to screen merging to the data that extract; In described step (1), pre-service comprises data scrubbing, data integration, data transformation and data reduction.
Compared with prior art, the present invention has following beneficial effect:
(1) the present invention utilizes the characteristic of data fusion and data mining to carry out data acquisition, pre-service and access, has realized mass data is stablized, stored and extract reliably, easily, very applicable, and realistic demand is applicable to large-scale promotion application.
Accompanying drawing explanation
Fig. 1 is structural representation of the present invention.
Fig. 2 is the schematic flow sheet of data mining in the present invention.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described, and embodiments of the present invention include but not limited to the following example.
Embodiment
As shown in Figure 1, the present invention mainly comprises data pick-up layer, data storage layer and data access layer.
Data pick-up layer: data are imported to data warehouse from the data storage medium of online transaction processing system, external data source, off line by extraction process, the processing of several aspects such as data pick-up relates generally to technically interconnection, copies, increment, conversion, scheduling and monitoring, process comprises source system data analysis and mapping, data pick-up, conversion and loading, Data Audit;
Data storage layer: this layer is the core of whole system, comprises 3 layers of ODS, EDW and Data Marts.Wherein, ODS deposits through slight cleaning, substantially keeps the conforming data of data details with production system, and the data memory cycle is shorter; EDW deposits through arranging, business data customer-centric, and the deposit data cycle is longer, from ODS to EDW, the process of conversion, first will accomplish that client belongs to, and completes the ownership of customer relationship afterwards; Data Mart is to carry out case study for the business of some theme, according to theme, data is done to further tissue, on EDW basis, according to analysis demand, creates corresponding subordinate data acquisition, generally takes data model storage data;
Data access layer: mainly contain following several mode aspect data exhibiting: inquiry: realize predefine inquiry, dynamic queries, OLAP inquiry and decision support intelligent inquire; Form: produce relation data form, complicate list form, OLAP form, report and various group financial statements; Visual: by understandable point and line chart, histogram, pie chart, network diagramming, Interactive Visualization, dynamic similation, Computer Animated Graph performance complex data and mutual relationship thereof; Statistics: the value of averaging, maximal value, minimum value, expectation, variance, gather, the various statistical study such as sequence; Excavate: utilize the methods such as data mining from data, to obtain the knowledge about data relationship and pattern.
As shown in Figure 2, before carrying out data mining, need carry out data preparation, this stage is divided into data integration, data selection, data pre-service and four parts of data-switching, by association analysis, sequence pattern analysis, classification analysis, cluster analysis etc., analyze the data in data warehouse and database afterwards, just can finally data be stored and extract when user accesses, for the information that makes to obtain, be convenient to user and understand and observe, can use visualization tool.
For the data relationship and the pattern knowledge that make to obtain by data mining in the present invention can be made consistance explanation and describe evaluation and control object comprehensively, in the present invention by separate sources, different mode, different medium and on time, space redundancy and complementary information carry out multisource data fusion, obtain a kind of more reasonable effectively information combination criterion, then formulate Optimal Control Strategy.Utilizing the integration technology of multi-source data can from the data of these magnanimity, filter out the needed data of all departments presents.
The present invention, by building the data warehouse based on data fusion and data mining, first utilizes data integration that the data in multifile or multiple database running environment are merged to processing, resolve Ambiguity, the omission in deal with data and cleaning dirty data etc.; Utilize some database manipulations to process data, from extracting data, go out to need the data acquisition excavating; Utilize Data Preprocessing Technology to check integrality and the consistance of data, noise data is wherein processed, determine the type of the dredge operation that will carry out; Utilize data mining need to carry out related data conversion; Selected maintenance data method for digging; According to final user's decision-making object, the knowledge of extracting is analyzed and evaluated; By separate sources, different mode, different medium and on time, space redundancy and complementary information organically combined, found out a kind of more reasonable effectively information combination criterion, the consistance of evaluation and control object is explained and described comprehensively, then formulate Optimal Control Strategy; Utilize multisource data fusion technology by the data screening of these magnanimity and present the needed data of all departments.
According to above-described embodiment, just can realize well the present invention.
Claims (6)
1. the data warehouse based on data fusion and data mining, is characterized in that, comprising:
Data pick-up layer: the data in the data storage medium of extraction online transaction processing system, external data source and off line, and by the data importing data storage layer extracting;
Data storage layer: comprise subject-oriented, integrated, current or approach the ODS that data current, that constantly change are stored, the EDW that Enterprise Data is stored, and Data Mart;
Data access layer: the mode with form, figure or data analysis conducts interviews to the data in data storage layer, and carry out analyses and prediction.
2. the data warehouse based on data fusion and data mining according to claim 1, is characterized in that, described data pick-up layer by interconnected, copy, the mode of increment, conversion, scheduling and monitoring extracts data.
3. the data warehouse based on data fusion and data mining according to claim 2, is characterized in that, in described data storage layer, ODS carries out short-term storage by the data after extracting; EDW carries out longer-term storage by the data after extracting; Data Mart will be stored after Organization of Data according to user's request.
4. the application process of the data warehouse based on data fusion and data mining described in claim 1 ~ 3 any one, is characterized in that, comprises the following steps:
(1) data pick-up layer is browsed and pre-service the data in the data storage medium of online transaction processing system, external data source and off line, and pretreated data are extracted and merge processing;
(2) data storage layer is combined the data analysis in data pick-up layer and excavate by association analysis, sequence pattern analysis, classification analysis and cluster analysis, and the Data classification of excavation is stored in ODS, EDW or Data Mart;
(3) user inputs data access request at data access layer, and data access layer determines that according to the type of the request of access of user's input from ODS, EDW or Data Mart, extracting corresponding data shows.
5. the application process of the data warehouse based on data fusion and data mining according to claim 4, is characterized in that, in described step (1), adopts multisource data fusion technology to screen merging to the data that extract.
6. the application process of the data warehouse based on data fusion and data mining according to claim 5, is characterized in that, in described step (1), pre-service comprises data scrubbing, data integration, data transformation and data reduction.
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| CN104361060A (en) * | 2014-10-31 | 2015-02-18 | 广东工业大学 | Data mining method and system applied to manufacturing Internet of things |
| CN104484734A (en) * | 2014-11-17 | 2015-04-01 | 国家电网公司 | Low-carbon city energy optimized configuration data center architecture |
| CN104679248A (en) * | 2015-03-03 | 2015-06-03 | 江苏科技大学 | Multi-scenario interactive data visualization system and working method |
| CN104731953A (en) * | 2015-03-31 | 2015-06-24 | 河海大学 | R-based building method of data preprocessing system |
| CN105139277A (en) * | 2015-08-18 | 2015-12-09 | 国家电网公司 | Electric power distribution network information clustering system and method |
| CN105260835A (en) * | 2015-10-13 | 2016-01-20 | 北京凯行同创科技有限公司 | Method for modeling, analyzing, and self-optimizing multi-source business big data |
| CN105488231A (en) * | 2016-01-22 | 2016-04-13 | 杭州电子科技大学 | Self-adaption table dimension division based big data processing method |
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| CN106815307A (en) * | 2016-12-16 | 2017-06-09 | 中国科学院自动化研究所 | Public Culture knowledge mapping platform and its use method |
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| CN107704508A (en) * | 2017-08-31 | 2018-02-16 | 北京空间飞行器总体设计部 | The data fusion and data digging method of polymorphic type magnanimity extraterrestrial target data |
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