By 2020 the Internet of Things (IoT) is expected to empower 26 billion devices connecting home appliances, cars, buildings and cities. To stay ahead of the curve, organizations will eventually have to rely on IoT to improve efficiency and engage customers at more personal levels. The challenge, however, is to figure out how to manage the waves of data that these IoT devices bring. How should we address the IoT complexity in analytics and what are the key considerations?

By adding another layer of intelligence to where the data is generated, edge analytics helps reduce the quantity of data and network communications overhead. Edge analytics is therefore the perfect answer to the influx of data that results from the advent of IoT. But what are the skills data scientists and decision makers need to effectively manage the size, speed and spread of IoT data? How can we create an analytic culture that propels the transformational opportunities promised by IoT?

With data processing being mobilized and autonomic data collection taking the fore, the analytics landscape is changing. But do not let the complexity be a deterrent as SAS is in an ideal position to facilitate your journey towards a new analytics platform.