One of the three emerging technology mega-trends in The Gartner Hype Cycle for Emerging Technologies, 2017, IoT or Internet of Things is powering the revolution of connectivity happening around us.

Gartner Hyper Cycle 2017

From smart home automation to everyday items, cars, smart speakers like Amazon Echo and any other object embedded with specialized sensors that can interact with its environment, regulate its internal state and be accessed by the internet, is a part of the Internet of Things ecosystem. But it is an ecosystem that runs on the power of data – Big Data.

The Relationship between IoT and Big Data

If IoT is the engine, Big Data is the fuel that powers this engine. With millions of devices getting connected every day, it is generating an inflow of Big Data where each bit of data exchanged by connected and applications devices adds to the Big Data universe. In other words, the world is seeing a massive influx of data generated by IoT devices and applications, data that is set to transform the world of business.

As more and more industries adopt IoT initiatives, there is a growing awareness of the corresponding rise in opportunities to analyze and leverage the insights generated by this data. Data in its native form is simply information, but processed, profiled and analyzed correctly it can yield critical actionable insights for informed decision making. As such, the real value of IoT lies in delivering intelligent insights to drive positive business outcomes.

The Impact of IoT on Big Data

As the world moves steadily towards the future of devices, connectivity and data – IoT – companies are quickly trying to upgrade their current processes, technologies and tools and set up data centers to prepare for the massive data loads that will hit as soon as the IoT revolution peaks.

Since the goal is to harness the data generated from sensors and apply it in the context of business, enterprises need to augment their existing technologies to effectively manage, store and extract real value from IoT generated Big Data.

Challenges

At this point in time, IoT, while a trending technology, has yet to mature. The main challenge right now, is uncovering, visualizing and extracting maximum value from diverse types of IoT generated big data and successfully applying it to improve business performance. Since IoT generates constant streams of data, a good analytics platform must keep up with the pace by converting and analyzing data in real-time.

Here it must be said that, given the rate of IoT adoption, in the coming decades, companies applying Artificial Intelligence (AI), deep machine learning and augmented analytics for real-time decision making will emerge as disruptors since AI is the brain of the future.

Data Storage and management is another concern. Once IoT technology peaks, enterprises will be hard pressed to store and manage the influx of big data unless adequately prepared. Business which have or are in the process of adapting their Big Data initiatives will be able to rapidly store, process and derive relevant insights to remain relevant in the market while enterprises with insufficient or limited big data tools will lose out.

Another challenge is Security – IoT being a very recent technology, there are numerous associated data risks. There is a severe lack of expertise to handle IoT-related security breaches. Attacks put not only data at risk but also the connected devices and applications which can sustain heavy damage. As such, organizations need to make massive changes to their security details, adopt multi-layered security to minimize threats.

In conclusion, as the world surges towards a smart, connected future with AI and IoT powered businesses, organizations must undertake massive changes to accommodate modern technologies and resolve new challenges.