An Approach to Improve Data Quality from Big Data Aspect by Sensitive Cost and Time

Big data is term of dataset with characteristic volume, value and veracity that lead to challenges unable proceed using traditional techniques to extract value, project management perspective is dynamic processing that utilizes the appropriate resources of organization in many phases by measuring in four-factor scope, time, cost and quality. In this research aim improve data quality from big data via project management scope depends on high trust which is getting high accuracy from confidence level in volume of data, confidence get with context and value of data which lead to determine accuracy deeply in it and finally choose from data depending on veracity of it, the experiment using three main factors time, cost and scope, strongest relation arranging between them start by project scope as strongest one then cost, product and finally time is weakest between them, in the final when select best quality use two sides generally from quality degree and be middle-quality interval and especially from relative distance with the strongest factor.