To provide correct business decisions, we need to address data quality consideration like accuracy, timely, consistency, etc. There is a sheer growth of data which needs to be accounted for and properly identified from the source. Quality movement focuses on many diverse aspects. The origins of defects therefore failed to be identified. The challenge is to understand the data, by use of data models and in context. Analysts build models based on continual consultation with business stakeholders. Metrics are established to quantify the relative importance and evaluate progress. Continual improvement is an ongoing discipline which gives breakthrough results and competitive advantage. To know more:
http://www.thoughtsoncloud.com/2015/07/enabling-a-data-culture-through-continuous-improvement/