Introduction
Kevin Ashton introduced the term "Internet of Things", 17 years ago, to explain how the devices in the physical world will be connected to the internet. But after 17 years, IoT is about extensive connectivity. This confirms that everything and anything is connected to the internet either directly or indirectly. So, IoT opens the doors of opportunities for creating, extrapolating, and utilizing the actionable insights about customers and the trends and patterns, which was impossible a few years back.
Analysts predict that by 2019, IoT will be the largest device market in the world - double the size of the combined strength of smartphones, tablets, wearables, and connected cars.
80 percent of the industrial internet data contains information about the location. Utilizing the location intelligence and spatial information itself is a big platform. For example, the above-mentioned insight can be used to predict/understand population distribution. Analyzing demographics supports the establishment of a better transportation system. The identification of urban infrastructure inefficiencies can be used for city management which opens the huge business opportunity.
IoT and big data management
Data integration, in batch or real-time, requires the ability to collect data from numerous sources either directly or through integration with existing data access technologies or by introducing new technologies. This helps the marketers to unveil the hidden value of the data and they are able to create a 360-degree view of their customers' tastes and trends, the relationships, the scope and opportunities, and the customer in a meaningful way.
There are many innovations happening every day in the field of analytics. For example, with the help of a robust big data platform, it is possible to find out the expense trend of a customer by a finance business firm, which will be the most valuable input for the business.
IoT and Real-Time Analytics
IoT Analytics will be a data science specialized domain. The necessity of real-time analytics is the main threat of IoT Analytics. Suppose, a driverless car system has to take a decision to stop the car once a passenger jumped into the track with no delay. It is impossible to transfer the data into the cloud, do the analysis over there, and send back the response.
When real-time analytics comes into the picture, IoT devices such as sensors, etc. should be capable of doing minimal analytics. All the sensors and devices are part of the IoT network and must have minimal intelligence.
The real-time analytics with intelligence will be the differentiator for companies in the future.