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Design and Implementation of a Data Quality Management Platform

Author: YouZhiQing
Tutor: LiangWenXin
School: Dalian University of Technology
Course: Software Engineering
Keywords: Data quality Collection point Rule management Data checking
CLC: TP311.52
Type: Master's thesis
Year: 2012
Downloads: 122
Quote: 2
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Abstract


The data is an important asset of the enterprise data center, It is essential to obtain and maintain high-quality data for efficient IT and business operations. At present, data quality management does not gain particularly great importance. With the gradual strengthening of the importance of the asset life cycle management business systems in the business development process, the business department staffs are demanding higher data quality business systems. Therefore, data quality management issues are on the agenda.This article does deep study in data quality management, conducts extensive research on domestic and international data quality management system, determines the functional requirements, hardware and software environment, and other non-functional requirements of a data quality management platform, describes related technologies and business processes. Under the company’s technical architecture, combining with the existing framework, the system model for data quality management platform is established. With software life cycle theory, a needs analysis, outline design, database design, detailed design and system testing of the data quality management platform is conducted and data quality management platform is implemented.The data quality management platform (DQMP) is constructed for the data quality of asset lifecycle management system. The system can be divided into seven parts, as the basic information, collection point management, rules management, data checking management, problem processing, data exploration and rules engine. Its workflow is extracting from the major business systems data warehouse in accordance with the data source information provided by the major business system, and checking data with business rules, then found the problem data and distributed these data to specialized data processing staff of related business departments for processing. Finally the workflow of data extraction, data checking, problem finding and problem processing is completed.The data quality management platform designed and implemented in this paper is based on the technical architecture of the company. Currently it is used by many customers, the actual usage indicates that the platform helps customers effectively manage data quality and quickly detect problems in the appropriate business systems, reducing the risks of data quality issues.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Software Engineering > Software Development
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