Oct 16, 2012
As more and more solutions are developed to populate data warehouses, it is apparent that merely delivering data isn't the complete answer organizations are looking for. There is a crucial need for operational data quality upon which to base their analytical and decision support systems. Operational data quality - real-time or near-real-time delivery, as opposed to batch-based data quality processes - is incorporated directly into the business processes of the organization's operational systems.
This allows organizations to make better business decisions faster than ever before from varied sources and types of growing data. Although it's easy to assume that high-level executives make most of the organization's decisions, the reality is that operational decision making happens at all levels of the organization on a daily basis.
This white paper examines three areas of focus when considering the implementation of an operational data quality process. The first is variables that can disrupt data-driven decision making, such as time, big data, pattern recognition, human biases, intuitions and errors. The second is why decision-driven data management is a strategy for enabling your organization to achieve better decisions with better data. And finally, why closing the decision-data feedback loop is the most critical success factor in data-driven decision making.