Big data and analytics

IMD Speaks

By using big data, managers can move from ideas, code and data – the human aspect of website design – to machines learning, building and adapting by themselves. Creating machines that can learn and then develop prototypes also means empowering them to adapt websites to best serve individual customers. Thus, with big data, growth is no longer linear, it is exponential.

Professor Carlos Cordon

Overview

Big data refers to datasets so large or complex that traditional data processing software are unable to handle them in a tolerable amount of time. Rather than referring to a definitive data size however, the term is often used to refer to predictive analytics, user behavior analytics, or other types of analytics that gain insight and find new correlations from large datasets.

As more data is generated and captured, analytics help make sense of this data. Real-time analytics, behavioral analytics, embedded analytics and prescriptive analytics are just some of the ongoing developments within this field. As computing power increases, data storage costs decrease and analytic software becomes more advanced, it becomes easier to take advantage of data in a timely manner to gain additional insights and uncover new opportunities.

Did you know?

Colleges are increasingly using predictive analytics to spot students who may drop out. Georgia State’s nursing school found the key factor was their students’ fundamental math score.

Big data and analytics

As management decisions become more fact-based, big data and analytics will play an increasingly important role. Are you asking the right questions? How do you prevent analysis paralysis? Do all your key people know how to use the tools? A key skill will be extracting and interpreting information.

Share

Get shareable link

Copy