Welcome!

@ThingsExpo Authors: Pat Romanski, Yeshim Deniz, Zakia Bouachraoui, Elizabeth White, Liz McMillan

Related Topics: @ThingsExpo, @CloudExpo, @DXWorldExpo

@ThingsExpo: Article

IoT: Four Things to Watch | @ThingsExpo #IoT #M2M #InternetOfThings

There's no doubt that there's a lot more "connected things" these days and that means a lot more data

What's next for IoT?

There's no doubt that there's a lot more "connected things" these days and that means a lot more data. Specifically, technology is moving out of the consumers' hands and into Healthcare, Oil & Gas, Transportation, Aviation and more. The spread of smart devices and sensors creates new forms of value and brings challenges for enterprises seeking to exploit this technology. However, while this boom in data has the potential to advance the industrial space in ways never before thought possible, few companies today have the right technologies in place or the right business models that can truly utilize the power of IoT.

So what should enterprises know about the permeation of sensors and connected devices and how can they prepare now or risk being left behind by their faster moving competitors? Here are four things to keep an eye on:

Smart Meters for a Smarter Planet
Consider smart meters' (the kind that Talend Data Masters' winners m2ocity and Springg are using) impact on data growth. Each single device typically generates about 400MB of data a year. Not much, right? Well, the numbers add up quickly! According to a recent Bloomberg report, it's predicted that 680 million smart meters will be installed around the world by 2017 leading to an estimated 280 petabytes of data generated by smart meters each year.

How can this lead to a smarter planet you ask? Consider Springg, an international software company specializing in agricultural data transport, software development and sensor technologies. Utilizing Talend software, Springg is able to evaluate data collected from sensors used in its mobile laboratories around the globe to measure soil elements. Based on these insights, Springg can give farmers soil and fertilizer advice to help dramatically increase their yield targets-thereby helping those farmers feed the world.

Data Up in the Sky
Watching for another area of machine-to-machine data growth? Try looking up in the air. A report from Wikibon found that the aviation industry is ripe for innovation in the form of Big Data analytics. An airplane flight (depending on length) can generate up to 40TB of data that will be used to analyze flying patterns, tune jet engine functions, identify new routes and reduce downtime. This is the type of data-driven decision making that has been revolutionizing eCommerce. Airlines with the ability to handle their big data in real-time and turn that data into instant will ultimately gain the competitive advantage.

For example, Air France/KLM. Each of the airline's A380 aircrafts contain roughly 24,000 sensors, which generate 1.6 GB of data per flight from Smart meter technology. The company utilizes this data to detect breakdowns before they occur. Using the smart meter analytics technology, Air France can now detect potential needed repairs 10 to 20 days before they occur. This prevents immobilization of the aircraft, which is not only expensive for the company, but also impacts their overall level of customer service and revenue.

Machine Learning and Data Science
Data is the life-blood of your business. You need to not only absorb as much as you can, but you need to analyze it and find any secrets. Data science and machine learning are gaining adoption as companies become even more data-driven. Machine learning is a form of artificial intelligence, where computers can learn and act to make decisions - sort of automating some of the data science tasks. With the shear volume of data coming from the billions of Internet of Things (IoT) devices, automation is a good thing. Spark MLlib is gaining popularity with its many machine learning algorithms for customer segmentation, forecasting, classification, regression analysis and more. Incorporating machine learning into heavy data loads will be an important step for companies to make better use out of the wave of information coming from connected devices - and find the needles in the IoT haystack.

Operationalizing Analytics
Even though we now live in ‘the Golden age' of big data, what will likely surprise you is that most companies are NOT utilizing the true value of the data to its full potential. In fact, a recent study by McKinsey showed that less than 1% of all IoT data is actually being used for decision making today. WHHHAAATT??

Why you ask? Mostly since the IoT data is being used for alarms or real-time control, not really optimization, or predictive and prescriptive analytics. Also, there are many challenges in making machine learning a reality.  Data has to first be organized and cleansed.  It can take a long time (months) to put a model into production-particularly when analytics models change frequently (requiring more updates), and there is a lot of hand-coding going on....Not exactly in the best interest of the data-driven firm. But there is a solution. Companies applying open, native technologies like Talend for real-time big data integration, which requires zero hand- coding, utilizes Spark, Spark Streaming and Spark machine learning, can start to get more insight from their data.

Originally Published on Talend.com

More Stories By Jacob Spencer

Jacob Spencer is Corporate Marketing Manager at Talend.

IoT & Smart Cities Stories
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...
Bill Schmarzo, author of "Big Data: Understanding How Data Powers Big Business" and "Big Data MBA: Driving Business Strategies with Data Science," is responsible for setting the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogge...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
Business professionals no longer wonder if they'll migrate to the cloud; it's now a matter of when. The cloud environment has proved to be a major force in transitioning to an agile business model that enables quick decisions and fast implementation that solidify customer relationships. And when the cloud is combined with the power of cognitive computing, it drives innovation and transformation that achieves astounding competitive advantage.
With 10 simultaneous tracks, keynotes, general sessions and targeted breakout classes, @CloudEXPO and DXWorldEXPO are two of the most important technology events of the year. Since its launch over eight years ago, @CloudEXPO and DXWorldEXPO have presented a rock star faculty as well as showcased hundreds of sponsors and exhibitors! In this blog post, we provide 7 tips on how, as part of our world-class faculty, you can deliver one of the most popular sessions at our events. But before reading...
If a machine can invent, does this mean the end of the patent system as we know it? The patent system, both in the US and Europe, allows companies to protect their inventions and helps foster innovation. However, Artificial Intelligence (AI) could be set to disrupt the patent system as we know it. This talk will examine how AI may change the patent landscape in the years to come. Furthermore, ways in which companies can best protect their AI related inventions will be examined from both a US and...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
DXWorldEXPO LLC, the producer of the world's most influential technology conferences and trade shows has announced the 22nd International CloudEXPO | DXWorldEXPO "Early Bird Registration" is now open. Register for Full Conference "Gold Pass" ▸ Here (Expo Hall ▸ Here)
@DevOpsSummit at Cloud Expo, taking place November 12-13 in New York City, NY, is co-located with 22nd international CloudEXPO | first international DXWorldEXPO and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time t...