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/

As the amount of data being generated daily is increasing, sales teams are now using analytics to boost sales. Several factors should be kept in mind while doing this like choosing the right set of data. The sales team may be lead astray when wrong data sets are chosen leading to drawing wrong conclusions. Choosing the right metric and making correct assumption is also crucial. Data on compensation can also provide insights into how sales can affect individuals or a group. Using this data and applying predictive analytics, one can easily forecast future performance and accordingly plan sales process. Read more at:http://www.cmswire.com/digital-marketing/dont-let-data-blind-your-sales-team/