Grid-based Data Quality and Data Integration Research

Abstract

Data information is important strategic enterprise resources, rational and effective use of the correct data to guide business leaders to make the right decision-making, enhance the competitiveness of enterprises. The data quality and the data integration, very important speaking of the enterprise, is the enterprise innovation development power. In order to improve the efficiency of data integration, we must permit multiple applications to share computing resources. The grid technology may step isomerism platform computing resource to carry on the work distribution and to carry out, uses the existing hardware property effectively or new highly effective, the economical hardware, may carry on highly effective to the data, expands economically, so that adjustment and optimization face enterprise's data transmission.Keywords: Data quality, Data integration, Data clean, Data grid, Data transmission, Isomerism platform BackgroundIn the present era, the enterprise informationization's request is getting more and more urgent, a very important aspect is the business data management. For most enterprises, ensure that data quality is a formidable challenge. PricewaterhouseCoopers issued the whole world data management survey result indicated. 75% of the companies believe that data lacking can lead to serious problems; over 50% of the companies overrun the cost due to the inner; over 33% of the companies can not but retard or give up use the new system's plan; over 20% of the companies thought that is unable to satisfy the contract or the agreement service level.[1] Up to 2009, Because of neglects the data quality question, some 50% above data warehouse project is unable to obtain the customer approval, even is defeated completely.Although some projects might not overrun at all, good business planning requires taking this into consideration as part of the overall plan. It is a great challenge that must be faced to improve the data quality and reduce IT costs. The relation between improving data quality and data integration is interdependent. Improving data quality can make data integration more exact, whereas, we can improve data quality of a system with the help of data integration. Also, we can improve the data quality in the process of data integration. This both already may parallel, may also carry on separately (Ralph Kimball (2008)).The main goal of gridding is to support coordinated work with the share source, which attribute to the result that the study on gridding data management has become very hot (Informatica (2008)). The effective and economic tensility for data integration can be achieved by developing the gridding computer system. Commercial hardware, for example, has shown the great demand for the tensility to reduce costs evidently. However, these griddings are dynamic for the nodes keep increasing and decreasing. Besides, collateral projects need to be timely adjusted in order to achieve the high-point, and reduce the load and frequency of modification of data mapping in order to answer the changi...