Data seems to be placed in the ‘too big to handle’ box.
90% of the world’s data didn’t exist two years ago*. Technological advances and the lowering cost of computing makes data available to businesses like never before. Successful businesses are using this data to review business models and drive transformation.
This paper will address each of the challenges and propose a model for data-driven decision making for enterprise risk management purposes.
*Mckinsey Analytics, How to win in the age of analytics, 2017
- Data and analytics; what is big data and data science
- The four stages of analytical maturity
- Risk data and use at all levels of the business
- The barriers to data use
- How to maximize the value in data interchange (which is how your risk management system processes the growing volume of data from internal and external sources).