CN102708149A - Data quality management method and system - Google Patents
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Abstract
The invention discloses a data quality management method and a data quality management system. The data quality management method comprises the following steps: managing a quality knowledge library; analyzing the data quality characteristics, and presetting a quality problem domain, a quality dimension domain, a quality rule domain and a quality standard domain; collecting quality information: selecting the quality dimension and the quality rules required by a user from the quality knowledge library, and extracting a data set meeting the user requirements from the original data sets; evaluating the data quality: evaluating the data quality according to the collected quality information, and generating and submitting a data quality report to the user or a quality manager according to the quality problem domain and the quality standard domain in the quality knowledge library; and improving the data quality: correcting the data quality problem detected in the evaluation of the data quality for improvement. The data quality management method and the data quality management system are applied to monitoring, evaluating and continuously improving the data quality in the whole hydrology industry based on the whole data processing procedure of the hydrology industry.
Description
Technical field
The present invention relates to the data quality management method and system, particularly hydrology industry data quality management method and system.
Background technology
S National Hydrologic Database is important national conditions basic database and strategic information resource database; Being the foundation of all water thing activity decision-makings in the development of the national economy and the social development, also is the main information product that hydrology industry is served fields such as society, economy, environment, ecology and national defence.For many years, because the data storage standard of lack of uniform makes that various places hydrology data storage form is different, the hydrological data bank present situation far can not satisfy the social development needs.Therefore, must accelerate the construction of s National Hydrologic Database, for the scientific research and the engineering construction of socio-economic development, the problem of paddling provides the informix service based on modern information technologies better.
The quality of s National Hydrologic Database directly influences the correctness of relevant decision-making, is the soul through s National Hydrologic Database construction operation overall process.Press for design for this reason and develop the data quality management that a special data quality management system supports hydrology industry comprehensively, thereby this provides wide application prospect for how hydrology industry supports the data quality management Continual Improvement quality of data with information-based means.
Summary of the invention
Goal of the invention: to the problem and shortage of above-mentioned prior art existence; The purpose of this invention is to provide a kind of data quality management method and system; Be based on hydrology industry data processing overall process, be devoted to monitoring, the assessment of the whole hydrology industry quality of data and continue improvement.
Technical scheme: for realizing the foregoing invention purpose, first kind of technical scheme that the present invention adopts is a kind of data quality management method, comprises the steps:
(1) quality KBM: the data quality characteristic is analyzed, quality problems storehouse, quality dimensions storehouse, quality rule storehouse and quality standard storehouse are set in advance;
(2) quality information collection: in the quality knowledge base, select the quality dimensions and the quality rule of user's request, and from the concentrated data set of meeting consumers' demand that extracts of raw data;
(3) data quality accessment: the quality information according to gathering, carry out data quality accessment, and according to quality problems in the quality knowledge base and quality standard, generate quality of data report and submit to user or quality control officer;
(4) quality of data is improved: detected data quality problem in the data quality evaluation is revised and improved.
Also can comprise the steps:
(5) quality objective is confirmed: judge that whether the quality of data after improving reaches user's request, if reaching user's request then generates target data set, otherwise returns step (3).
In the said step (4), can adopt automatic and manual dual mode to revise and improve, but also recording quality improve log information.
Second kind of technical scheme that the present invention adopts is a kind of data quality management system, comprising:
The quality base module is used for the analysis of data quality characteristic is provided with quality problems storehouse, quality dimensions storehouse, quality rule storehouse and quality standard storehouse in advance;
The quality information acquisition module is used for quality dimensions and quality rule in quality base module selection user's request, and from the concentrated data set of meeting consumers' demand that extracts of raw data;
The data quality accessment module is used for the quality information according to the collection of quality information acquisition module, carries out data quality accessment, and according to quality problems in the quality base module and quality standard, generates quality of data report and submit to user or quality control officer;
The quality of data is improved module, is used for the detected data quality problem of data quality assessment modules is revised and improved.
In the quality base module, the quality problems storehouse: can deposit with hydrology data quality management process in run into or all kinds of problems that possibly run into, problem can classification, differentiated control and maintenance;
Quality (assessment) dimension storehouse: can deposit accuracy, consistance, integrality, promptness, the property obtained isometry index that hydrology data quality management is paid close attention to;
The quality rule storehouse: but the store data quality evaluation technical regulation related with detection, and quality rule is set up according to quality problems and quality index;
Quality standard storehouse: can deposit the judgment criteria whether up-to-standard to data.
Also can comprise quality objective affirmation module, be used to judge whether the quality of data after the improvement reaches user's request, if reaching user's request then generates target data set, otherwise the return data quality assessment modules.
The said quality of data is improved module and can be adopted automatic and manual dual mode to revise and improve, but also recording quality improves log information.
Beneficial effect: the present invention can play useful facilitation effect towards hydrology industry data processing overall process to the comprehensive control and the lifting of the hydrology quality of data.Through data quality management provided by the invention system, thereby can guarantee that the data quality management Continual Improvement hydrology quality of data provides technical support for hydrology industry adopts information-based means.
Description of drawings
Fig. 1 is the structural framing figure according to the data quality management system of a specific embodiment of the present invention;
Fig. 2 is the data quality accessment process flow diagram according to a specific embodiment of the present invention;
Fig. 3 improves process flow diagram according to the quality of data of a specific embodiment of the present invention.
Embodiment
Below in conjunction with accompanying drawing and specific embodiment; Further illustrate the present invention; Should understand these embodiment only be used to the present invention is described and be not used in the restriction scope of the present invention; After having read the present invention, those skilled in the art all fall within the application's accompanying claims institute restricted portion to the modification of the various equivalent form of values of the present invention.
The data stream of managing from the quality of data turns over journey, and system mainly ensures the quality of data in the s National Hydrologic Database through three aspects at present.
1, data source (collection, reorganization and typing) quality rule diagnosis;
2, the quality monitoring of data processing ETL (Extraction-Transformation-Loading, report, junction and dump) process;
3, each index rationality of data processing achievement, consistance are checked.
The data quality management system through to the inspection of data source (data acquisition, reorganization and typing), process (report, junction and dump), three aspects of processing achievement with check, realized monitoring to the whole process of data production process.After data were produced and accomplished, system can be according to assessment result automatically generated data quality report, and the structural framing of total system is as shown in Figure 1.
The quality knowledge base has comprised interior requiring of data on key elements such as quality problems, quality index, quality rule and quality standard, system constructing a comprehensive quality of data knowledge base, and carry out quality evaluation and quality improvement as the center.System has the assessment of automated quality information acquisition, automated quality, problem identification and quality report, automatically and the functions such as quality improvement that manually combine automatically, has greatly improved the efficient and the level of data quality management.This system adopts the infosystem instrument to carry out data quality management for hydrology industry and is with a wide range of applications.
The quality knowledge base through data quality characteristic analysis result is provided with in advance, comprises knowledge of Quality management such as data quality problem typelib, quality evaluation dimension storehouse, quality rule storehouse and quality standard storehouse by the quality control officer.
Information acquisition module is collected the user to original demands information such as data object and scope, quality of data index and quality of data requirements; And, in the quality knowledge base, select suitable evaluation index, Rules of Assessment and appraisal procedure, the data set of meeting consumers' demand that from raw data base, extracts according to user's request information; And above-mentioned information is passed to quality assessment modules as input carry out data quality accessment.
The data quality accessment module is the corn module of data quality management; This module is according to data set, assessment dimension, Rules of Assessment and the algorithm of information acquisition module and the transmission of quality knowledge base, and the quality evaluation standard of regularly carrying out in data quality accessment and the bond quality knowledge base generates the quality evaluation report; The data quality accessment report comprises the detailed bill and the quality improvement proposed projects of pending quality problems; The quality evaluation report is submitted to quality control officer or user with automated manner.
The quality of data is improved module and is comprised automatic and manual dual mode, and automated quality improves according to the quality improvement processing rule in the quality knowledge base and accomplishes the data quality problem processing automatically; Manually quality improvement bond quality assessment report adopts manual intervention patterns such as the expert appraises through discussion, user feedback, manually accomplishes the quality of data and improves processing; Recording quality problem improvement project and step.
Data quality management is a dynamic process, and therefore, the content of storing in the quality knowledge base will be carried out dynamic optimization with quality evaluation and QIP and upgraded.
The data quality management system mainly carries out quality management and monitoring from the different aspects such as form, content and effectiveness of data to data source (database, excel, text etc.), data converted products (Water Year Book, data warehouse, data cube etc.) and data handling procedure (data preparation and typing, data report and junction, data dump and Data Update, data backup and recovery etc.).
The quality knowledge base, is comprised through data quality characteristic analysis result is provided with in advance by the quality control officer:
Quality problems storehouse: the Problem Areas of sending out the type generation that produces data quality problem according to oneself;
The quality dimensions storehouse: data satisfy the fundamental characteristics tolerance of customer requirements and application target on form, content and effectiveness; Like integrality, consistance etc.;
The quality standard storehouse: data are in the judgment criteria of aspect quality grades such as form, content and effectiveness;
Quality rule storehouse: manage all quality of data relevant rules with quality evaluation, quality improvement and statistical study.These rules have contained form, content and the effectiveness requirement of data, and different quality metrics need adopt different grammers to come the describing mass rule.
Corresponding data hierarchy, quality metric, tolerance applicable object and scope, quality rule content and the instance of quality of data rule explained referring to shown in the table 1:
Table 1
The data quality accessment module is the core component in the data quality management system.To be the estimator be applied to the quality of data evaluation model target data or data set and finally obtain the series of steps of evaluation object quality state in quality of data evaluation procedure.The general flow that the hydrology quality of data is estimated is as shown in Figure 2.
The data quality accessment process is an iterative process, and the sequencing of each process is the active general sequence of expression phase only, and according to the quality decision of actual implementation status, some processes possibly repeat.
1), quality information collection: data quality accessment should be that guiding is carried out the quality evaluation analysis with user; Data resource is different from entity products; Have characteristics such as purposes personalization, variation, instability; Therefore, the user must be at first understood and assessment indicator system targetedly could be set up to also definite its evaluation object of the demand characteristic of particular data resource and scope thereof.
2), select the quality evaluation dimension: quality of data dimension is to carry out the concrete tolerance reflection of object in the quality activity; Like correctness, accuracy etc.; It is the main contents of control and evaluating data quality; Therefore, from the quality knowledge base, choose can survey, available quality dimensions are as evaluation index.Select the quality evaluation dimension should note level, the weight problem of each evaluation index, and with the collision problem of other same level index.
3), set up assessment models:,, select suitable quality evaluation algorithm to set up the quality evaluation model in conjunction with the characteristics of each evaluation object and evaluative dimension in definite its object range and after selecting the quality evaluation dimension.Quality evaluation algorithm commonly used has two kinds of quilitative method and quantivative approachs, and the former adopts method such as weight marking to carry out, and the latter carries out according to the specifications of quality one-level defective criterion in information each stage of production.
4), quality evaluation: data quality accessment is the active procedure that the quality object, quality object range and the quality evaluation model that utilize above-mentioned steps to confirm realized quality assessment.The method that should guarantee in the data quality accessment process to be adopted correct and objective; Avoid increasing the disturbing factor of quality assessment as far as possible; Farthest handle and realize, pursue comprehensively the objectively truth of the reflection quality of data by the robotization of computing machine and network technology.
5), assessment report: combine quality evaluation target in the knowledge base, analyze the quality requirements whether quality assessment result reaches the user, generate respective quality rank qualification result according to the quality discrimination standard; The data quality accessment report also comprises the detailed bill and the quality improvement proposed projects of pending quality problems; The quality evaluation report is submitted to quality control officer or user with automated manner.
Quality of data improvement technology relates generally to instance and two aspects of pattern.The mode layer quality of data improves and mainly to stress to understand data pattern and according to existing data instance design data pattern again; The common employing of instance layer quality of data raising data cleansing is through the improvement and the raising of repeating objects detection, missing data processing, abnormal data detection, logic error detection, the inconsistent data process etc. techniques realization quality of data.
The quality of data is improved module and is mainly paid close attention to the improvement of the instance layer quality of data, promptly accomplishes the quality of data through data scrubbing and improves, and the quality of data is improved and comprised automatic and manual dual mode.The improved general flow of the hydrology quality of data is as shown in Figure 3.
Automated quality improves according to the quality problems inventory that produces in the quality evaluation process, improves processing rule and the processing of quality improvement algorithm completion data quality problem from the knowledge base quality of match automatically.Automated quality is improved one's methods can accomplish duplicate record cleaning and check automatically, missing data cleans with fill up, quality problems such as logic error correction, inconsistent data processing; And quality of data improvement information write down into daily record storehouse.
Manually quality improvement bond quality assessment report adopts manual intervention patterns such as the expert appraises through discussion, user feedback, manually accomplishes the quality of data and improves processing, and quality of data improvement information is write down into daily record storehouse.Manually the quality improvement method is accomplished automated quality and is improved the quality problems that step can't be handled, and according to manual QIP, step and expertise, generates new quality improvement rule and algorithm and upgrades the quality knowledge base.
Quality improvement daily record storehouse is used to write down the information relevant with quality improvement, comprises the contents such as data relativity, quality improvement rule and algorithm of quality improvement front and back.
Hydrology data quality management is one and relates to application-dependent and use the independent dynamic change procedure.Therefore, in whole data life period, original data quality problem has solved, and finds to have new quality problems toward the contact meeting.Quality objective is confirmed module, is used to judge whether the data set quality of data after the improvement reaches user's request.If do not reach customer requirements through the improved quality of data, system returns the quality evaluation stage and carries out the next round quality control.
Claims (8)
1. a data quality management method comprises the steps:
(1) quality KBM: the data quality characteristic is analyzed, quality problems storehouse, quality dimensions storehouse, quality rule storehouse and quality standard storehouse are set in advance;
(2) quality information collection: in the quality knowledge base, select the quality dimensions and the quality rule of user's request, and from the concentrated data set of meeting consumers' demand that extracts of raw data;
(3) data quality accessment: the quality information according to gathering, carry out data quality accessment, and according to quality problems in the quality knowledge base and quality standard, generate quality of data report and submit to user or quality control officer;
(4) quality of data is improved: detected data quality problem in the data quality evaluation is revised and improved.
2. according to the said data quality management method of claim 1, it is characterized in that: also comprise the steps:
(5) quality objective is confirmed: judge that whether the quality of data after improving reaches user's request, if reaching user's request then generates target data set, otherwise returns step (3).
3. according to the said data quality management method of claim 1, it is characterized in that: in the said step (4), adopt automatic and manual dual mode to revise and improve.
4. according to the said data quality management method of claim 1, it is characterized in that: in the said step (4), go back recording quality and improve log information.
5. data quality management system comprises:
The quality base module is used for the analysis of data quality characteristic is provided with quality problems storehouse, quality dimensions storehouse, quality rule storehouse and quality standard storehouse in advance;
The quality information acquisition module is used for quality dimensions and quality rule in quality base module selection user's request, and from the concentrated data set of meeting consumers' demand that extracts of raw data;
The data quality accessment module is used for the quality information according to the collection of quality information acquisition module, carries out data quality accessment, and according to quality problems in the quality base module and quality standard, generates quality of data report and submit to user or quality control officer;
The quality of data is improved module, is used for the detected data quality problem of data quality assessment modules is revised and improved.
6. according to the said data quality management of claim 5 system; It is characterized in that: also comprise quality objective affirmation module; Be used to judge whether the quality of data after the improvement reaches user's request, if reaching user's request then generates target data set, otherwise the return data quality assessment modules.
7. according to the said data quality management of claim 5 system, it is characterized in that: the said quality of data is improved module and is adopted automatic and manual dual mode to revise and improve.
8. according to the said data quality management of claim 5 system, it is characterized in that: the said quality of data is improved also recording quality improvement log information of module.
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