The idea of applying the Internet of Things (IoT) to business intelligence (BI) is now becoming a mainstream part of corporate strategy. IoT has taken off over the past few years, and the BI industry is booming with all sorts of enterprise resource planning (ERP) software and business technologies that can optimize the use of data for insights.
In general, companies often use the IoT for predictive analytics – that is, they aggregate data and try to use that data to predict what's going to happen next. Developing trend insights is a major part of how IoT is useful for BI. (Read How Predictive Analytics Can Improve Medical Care.)
One example is the field of anomaly detection. Along with identifying trends, IoT data can help decision-makers to develop understanding of anomalies and the evaluation of peak traffic or peak business conditions. (Read What Are the Top Driving Forces for the Internet of Things (IoT)?)
All of this funnelled into analytics that helps to provide a path forward for the business, in what experts often refer to as "prescriptive analytics," crafting business plans through the use of carefully collected data.
As for the actual structure of using IoT for business intelligence, many companies are innovating with the Internet of Things to position devices at the edge of a network and closer to the real world. (Read An Introduction to Business Intelligence.)
In the old days, data center systems often housed the most important and sensitive data sets in the core of the business architecture in a central data warehouse. The Internet of Things really changes this paradigm and allows companies to aggregate data at the edges of a network given the right security protocols and network protections.
For example, companies might employ sensors outside of a retail store or fast food location, or they may use IoT devices to interconnect with customer smartphones.
The key lies in adapting a system of data aggregation that will ultimately benefit the business goals. The IoT devices, more often than not, are the vehicle through which the data comes in, and the result is freer data, data that can easily travel to where it’s needed throughout the architecture.