Data volumes are exploding. Between data gathered by sensors on equipment, field employees and administrative staff, businesses end up with a staggering amount of data from your IoT implementation. This much data triggers the question: what do I do with all this data?

First, examine what you have gathered. Data visualization makes sense of your millions or billions of data points and you can click and tap on your data visual data sets for more detail. Create streams and views in your dashboard to organize your data in a way that makes more sense to you and your business.

Leverage Machine Learning and Predictive Analytics

Machine learning and predictive analytics can make the most out of your data. Machine learning combs through the mountain of data for you–a task that would take weeks could only take hours—and machine learning makes predictions based on historical based on historical and current trends, giving you reports on hand to make a more informed decision.

Keep and Analyze Old Data

Between storage on the cloud, utilizing predictive analytics and leveraging machine learning, you can keep your organization’s data indefinitely, regardless of how much. No longer do you have to dump data because of storage limitations.

Identify and Overcome Business Challenges

Uncover insights buried in your data to optimize the way you do business—assess inventory levels, predict product fulfillment needs, and identify potential backlog issues. Integrate big data from across the enterprise value chain and use advanced analytics in real time to optimize supply-side performance and save money.

As an example, we’ll illustrate a case on how to use IoT data on aircraft and engine components, specifically fuel pumps. The point at which fuel pumps are removed from aircraft engines is called a “soft life.” By analyzing detailed data from each specific pump and comparing it to data models and other pumps in the fleet, it is possible to provide an alert that indicates that a specific pump might not be performing well and should be replaced sooner than its soft life.

Conversely, if a pump is close to its soft life, but monitoring and analytics show that the performance is normal, a decision could be made to defer until a later, routine maintenance window. Moving to an approach based on components’ actual condition could potentially add up to tremendous savings across a fleet by minimizing the disruption and cost of maintenance.

Forward-thinking manufacturers are already improving performance and agility across their businesses— redesigning processes for greater agility and responsiveness, building more open, connected and trusted ecosystems, and delivering more personalized customer service experiences. Likewise, service management software is making it easier for organizations to delivery proactive and timely field service, and cloud-based and mobile technologies are enabling service information to be delivered to customers in real-time.

For more information, download our factsheet on how you can achieve a new level of IoT connectedness in 6 weeks.