by Exosite, on March 3, 2016
The era of big data is upon us. With the advent of the Internet of Things (IoT), companies have access to more information than ever before. Employees sit in Internet-connected chairs in rooms with remotely monitored HVAC systems. Industrial buildings, built by cranes with pumps whose IoT performance monitoring can be seen on an iPad, feature Internet-connected pest-control traps that send text messages to sanitation workers when rodents have been caught. Employees go home to Internet-connected garage doors, lights, and thermostats that can all be controlled from a smartphone.
Although a staggering amount of information is gathered every day from IoT connected products just like these, the companies that have access to it are not necessarily using that data effectively. As Tim Hartford of the Financial Times notes, “Big data has arrived, but big insights have not.” Useful data analysis requires much more than the simple collection and summary of data. Companies must have a long-term IoT analytics strategy in place to provide significant, actionable insights that will fuel their business transformation from a product company to a connected product company. That strategy must begin with a solid IoT product deployment foundation and include the purposeful creation of a data pipeline, from the developing processes for data gathering to leveraging algorithmic predictions to inform business decisions.
This white paper co-authored by Exosite’s CTO, Mark Benson, and Business Analyst, Jay Carlson, provides an overview of analytics within the context of connected products and identifies the stages of analytics maturity. It introduces machine learning and the prospect of automating device behavior. With recommendations about how enterprises building connected products can realize the full potential of IoT by turning data into action that produces business results.
Stay tuned for future data analytic blog segments and download the full data analytics for IoT white paper today.
