10 Aug 2012, England, UK --- male and female staff at site meeting inspecting production complex --- Image by © David Burton/CorbisIn June I kicked off a blog series to explore topics that are top of mind for organizations tackling predictive analytics. The first blog focused on Deep Learning and how it can be embedded in predictive modelling scenarios using SAP Predictive Analytics. Today I introduce the second blog in the series aimed at highlighting the various ways predictive can help make the world around us a better place to live.

With the advances in sensor, communication, and internet technologies, we’re starting to be part of a completely connected world. With the Internet of Things (IoT) becoming reality, large volumes of information rich digital signals and various types of high velocity data streams are now available in real time.

According Gartner the world will see 25 billion Internet “connected things” by 2020, which will produce close to $2 trillion of economic benefit globally.

“The Internet of Things is a revolution waiting to happen. The challenge of the IoT is less in making products “smart” and more in understanding the opportunities enabled by smart products and new ecosystems” – Christy Pettey, Gartner

Predictive analytics can be employed to find actionable insights from this data, and to enable a near zero downtime of systems around us. Today predictive analytics can be effectively employed to analyse the digital signals (sensor feeds) in real time, to understand abnormal behaviour of systems, and to help schedule proactive preventive maintenance, saving significant cost and downtime.

All of this can be enabled by software solutions, like SAP Predictive Analytics, for building robust models that can be easily operationalized to maximize the impact of predictive models for such use cases.

To learn more and how this applies to various predictive maintenance use cases, I invite you to read the whitepaper titled “Using Predictive Maintenance to Approach Zero Downtime”. The use cases span Transportation, Manufacturing and Production, Utilities, Medical Equipment, Data Centers, and Cloud Infrastructure. The paper also briefly touches on various software components and how they apply to the use cases.