As companies engage in the implementation of analytics and data science applications, many challenges lie ahead. According to the Harvard Business Review, many data science applications fail due to poor goal definition, a lack of understanding of the key data, or a lack of focus on business value. We believe the best route to data analytics and particularly analytics for the Industrial Internet of Things, must have several key elements.

The terms Big Data, Data Analytics, Artificial Intelligence (AI), and Machine Learning (ML) are being used increasingly in articles and publications about energy - but what is the real intrinsic value customers are trying to achieve, and what are some of the specific types of analytics that can have a real impact on generating assets?

Makers of giant wind turbines are hoping that artificial intelligence can bring back some of the industry’s mojo. While developers have spent $1.1 trillion on new wind farms over the past dozen years -- helping transform the global energy landscape with renewable power -- more money is going into new solar systems these days. Also, governments are phasing out subsidies, including programs in the U.S. that have offered $22 billion in tax breaks to turbine projects in the past 15 years.