In terms of numbers, the Internet of Things (IoT) is gaining momentum every day. Already, things connected to the Internet have surpassed the number of people connected to the Internet. Gartner estimates that the Internet of Things (IoT) will consist of 30 billion objects connected by 2020. When it comes to monetary numbers, it really signifies the huge potential that is estimated to bring over $2.3 trillion by 2025.
Experts envision over 90% of the things for everyday living inside our homes will be connected in the future, too. We are already living in a world attached to several smart things, such as mobile phones, smart watches, smart glasses, healthcare wearable devices, WiFi-enabled entertainment systems, ever-connected home security systems, sensor-based irrigation systems, smart meters, smart cutting boards, and even connected cars. In the future, connectivity will penetrate deeper into other objects that we interact with every day, such as can openers, pop cans, smart utensils, and smart pantries.
The overarching goal is to enhance the everyday experience through seamless connectivity that blends the physical and digital worlds with natural, smart interactions. The key challenge for manufacturers will be keeping that connectivity to a low cost.
A current debate in IoT is pushing the computing intelligence to the edge versus managing in the cloud. While “edge computing” offers benefits (such as cutting down the bandwidth by filtering the unwanted data from being sent via 3G), it poses a few challenges, too.
First, the cost of updating the computing software/firmware in the edge will be a factor, especially if the scale of the “things” is high. Secondly, there is a lot of flexibility in evolving the computing intelligence, if managed in the cloud. Lastly, all the potential use cases of the data read from the sensors and smart things are not known at the point of development.
Hence, most of the adopters have chosen to bring in as much data as possible from the smart things to the cloud and explore use cases as they evolve.
Enter Big Data
Millions of smart things across the world are pushing up the scale towards Big Data. To make the matter more interesting, the velocity of the incoming data poses challenges to process them in real time. A big use case for bringing connectivity in various verticals (healthcare, manufacturing, automobile) is to continuously improve the quality of the products and to know the usage and vital parameters read from products after they leave the factory.
In many cases, the direct ROI for bringing connectivity is often to apply the power of analytics on the pile of data acquired. Business Intelligence has been around for a long time and often it is confused with the business and data analytics.
Here’s a good view of the differences, according to Pat Roche, Vice President of Noetix Products: “Business Intelligence is needed to run the business while Business Analytics are needed to change the business.” The power of data analytics lies in the real-time analysis and being able to predict the outcome as opposed to monitoring KPIs and reporting the outcome aftermath. Forecasting and Predictive modeling are pivotal to business analytics.
One of the key steps towards embracing the Big Data for the enterprise is to lay down the data storage and analytics strategy. NoSQL, Real Time analytics and batch analytics are the cornerstones of Big Data. Big Data has become a crowded space in the last 2 to 3 years, but most of the players have converged in the approach of embracing Open Hadoop Distribution. Expectedly, most of the organizations try to avoid vendor lock-in and the choice has become easier with wide adoption of Hadoop.
The key foundation for an enterprise to embrace IoT is to have a business model, and data analytics plays a huge role. Hence, it is not a chicken-and-egg situation any more. If you want to be in the league of IoT, preparing the journey of transformation towards Big Data must begin today.