Smart Data: Enterprise Performance Optimization Strategy

3.3 TOP–DOWN STRATEGY

The place to begin is with executives at every level of the enterprise recognizing and embracing their data—insisting that they have clear visibility into the data that they need to optimize performance, and into the data representing enterprise assets that they must protect. Executives need and want a holistic approach to data strategy and data management.

With the notion of smart data, the data should be engineered such that it addresses executive needs for problem solving, decision making, planning, sense making, and predicting. This means that when an executive or manager needs to refer to the data for answers, it is unnecessary to scramble to locate it or to judge its reliability or quality, as executive requirements are anticipated and the response preengineered as in data engineering.

Better still, the executive does not have to search for the answers because solutions and answers are presented to the executive, anticipating requirements. It is accompanied by methods and algorithms representing best analytics. Some describe this as an autonomic or self-managing system that is characteristic of smart data.

Data that is shared throughout the enterprise by multiple users and disciplines must be engineered such that it is available openly for seamless processing to those who are credentialed and privileged.

While there are a host of issues in the domain of smart grid and smart enterprise services associated with implementation, our focus is on anticipating ...