• Internet of Things
  • Experfy Editor, Experfy Editor
  • JUN 22, 2017

Integrating IoT with Big Data, a Revolutionary Step

Need training for Internet of Things? Browse courses developed by industry thought leaders and Experfy in Harvard Innovation Lab.

Internet of Things is concerned with the connectivity of devices and sensors, and multiple other sources and services linked to them. It is continuously pushing our society and industries to new heights. These devices, sensors and other connected sources emit enormous and dynamic structured, unstructured, semi-structured and behavioral data in real time, which in itself is raw. This data needs to be churned out to derive actionable insights to improve things connected by IoT and drive overall productivity.
 

Big Data crucial for IoT working

Picture

Source: DZone


In this context, big data and its analytics are crucial to work and grow Internet of Things. IoT’s fuel is the big data and its brain is an artificial intelligence that drives the connected things. Real value can be derived from IoT with making smarter connected things, driving intelligent insights that can pave the way for new businesses and new enlightenment around us. With millions of devices and things connected to Internet of Things, enormous data is generated from them. It needs artificial intelligence to analyze this data at scale, which is possible with big data analytics to know the patterns and contextual relations that impact business. IoT in a way is driving the big data analytics for making decisions in real-time. For example, big data analytics can predict the behavior of a connected car driver, suspicious behavior of people, their activities at an ATM, agricultural patterns of crops in remote places can be found, using drones, and so on.


IoT and Big Data inter-linked
In many use cases, IoT and big data can inter-link. For example, a retail store can display its products and offers available to a customer near to him when he opens the store app when he enters the store. This can be possible with the VLC technology (visible light communication) that makes use of Bluetooth beacons and lighting system. Whenever a customer enters the store and opens the store App, the VLC traces his location in the store, projects ultra-high-speed light at the smartphone in the customer’s hand, and display the offers available to him. The retail store can store this customer information in the cloud and performs analytics on his buying behavior information. This can help the retail store to offer customized better offers or services to the same customer whenever he visits the store. This ecosystem of VLC, Bluetooth beacons, cloud, switches and Ethernets and customer data emitted and its analytics by big data are all inter-linked. They depend on each other for their performance and improving both customer satisfaction and retail store performance.  Although IoT and Big data are not the same, the two are closely interconnected.


Stitching both together
IoT is already touching every possible thing in our lives, including manufacturing, retail business, transportation, health, smart homes, education and every ecosystem. In one way or the other, IoT connects cars, trucks, train tracks, traffic signals and lights, medical devices, voice activated appliances, thermostats, smartphones, wearables, software apps, millions of devices and sensors and much more.
All these IoT things are transmitting countless data that need a new infrastructure of software and hardware to handle the mass data and analyze in real-time. The technologies are improving and evolving day by day to deal with the producing stream of data continuously. That is where IoT stitches with the big data. Gartner projects use of 20.8 billion “things” globally, by 2020.
Big Data helps enterprises use data available around them to enable improve their performance. They have data written in social media by their customers, log files, sensors, applications and processes and devices. Then, the IoT is a big source of data.  Businesses need to analyze this data in real time for deriving new patterns of use and integrate them in their business. 


Reactive to proactive
Using IoT, businesses can track their assets to monitor and take corrective actions when necessary with the help of big data analytics. For example, IoT can help monitor assets such as engines, trucks, pumps and the likes. Big data helps analyze data available about this machinery and devices regarding failures and their causes. With Big data analytics, problems can be fixed by predicting them before they happen. IoT in collaboration with Big data helps businesses go from being reactive to being proactive.
According to the Oracle, eight percent of businesses are able to capture and analyze IoT data fully and timely. You can view the Oracle infographic here. This infographic summarizes that “tens of billions of internet-connected things expected by 2020, generating zettabytes of new data. Adoption of the Internet of Things is happening now, across a wide range of industries, as organizations capture and analyze data from devices in an effort to rapidly identify important changes and take immediate action” and “IoT will account for 4.4 trillion GB of the data in the digital universe by 2020”.


Leveraging Big data during IoT Journey
The basics of the rapidly evolving IoT technologies are how to address effectively to leverage data and analytics to power your operational models. The Dean of Big Data at Dell-EMC Services, said that they “have tweaked the Big Data Business Model Maturity Index to help organizations not only understand where they sit on the maturity index with respect to the above question, but also to provide a roadmap for how organizations can advance up the maturity index to become more effective at leveraging the wealth of IOT data with advanced analytics to power their business and operational models”. 
 Figure 5:  Big Data / IOT Business Model Maturity IndexMaturity Index
Source: Dell EMC - Big Data / IOT Business Model Maturity Index Maturity Index


The Dean further says “To drive meaningful business impact, you will need, to begin with, the business and not the technology” and “Align the business and IT teams”.
Adaptation of IoT by the businesses continuously expands the market for big data analytical solutions.  Data analysis from IoT things and sensors though complex has clear potential for massive impacts on the businesses. The complexity exists because of the many moving parts in IoT that make it difficult to assemble data at one point for analysis. 
Whether household gadgets or mobile applications, leveraging IoT with Big Data is anticipated a big revolutionary step forward in 2017 leading to many more discoveries. Development of IoT applications can make ripples all over the world ushering in many smart cities.


2017 predictions for IoT and Big Data

 10 predictions for the Internet of Things and big data in 2017

Source: The Information Age Magazine - ‘Enterprises will finally be able to speak about big data in terms of ROI’


There was enormous progress in 2016 for big data and IoT technologies. There is a more promising future in 2017 for more enterprises to adopt IoT in their businesses. Information Age magazine makes 10 predictions for the big data and IoT in 2017. These predictions depict rise of the IoT architect, hybrid architecture adoption, Deep learning impacts,  augmentation of products based on reality, low power and wide area (LPWAN) networking, higher IoT market consolidation, IoT talent honing, endeavouring security and integration, rise of Hadoop to new scale, and use cases with new BI. 
LPWAN networking is slated to help IoT explode in a big way. According to estimates of Business Insider, IoT devices estimated at 700 million are going to be connected by 2021 over LPWAN networking.  LPWANs have potential to connect IoT devices across a wider geography using less power.

Boston city bkg

Made in Boston @

The Harvard Innovation Lab

350

Matching Providers

Matching providers 2
comments powered by Disqus.