Five years ago, it seemed more like science fiction than fact: A wirelessly connected, always-on world of devices endlessly transmitting information. Today, it’s the Internet of Things (IoT), and according to research firm Gartner, the market is headed for $300 billion in revenue by 2020. Yet companies have barely scratched the surface of IoT; wireless sensors and monitoring devices are still in their infancy. The result? The best is yet to come — device sophistication and data collection will quickly ramp up over the next few years. To make best use of IoT, however, companies need to address the inherent challenge of connected devices and big data integration.
The Volume Vector
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The Internet is already teaming with connected devices, everything from mobile phones to tablets and traditional desktops. Adding in IoT, however, blows this number out of the water — every temperature sensor, every light bulb, every printer and fridge could potentially act as a data collection network endpoint. The Internet is the network these devices will use to make their events and data available. The increase in the number of devices will come with a potential huge uptick in big data. As smaller and more numerous devices gather ever-more-specific information, the available “pool” of data quickly increases past a point that even the most sophisticated information-handling tools can handle. The volume vector of IoT means companies must find new ways to manage the influx and extract meaningful results.
One option? Streamline storage. As noted by Data Informed, many companies are now moving away from site-based storage to platform-as-a-service (PaaS) solutions that let them store data off site and continually expand to meet the increasing need of IoT. Flash storage is another possibility since it offers improved density and retrieval times while lowering the chance of hardware failure. However, even flash and PaaS won’t be enough to meet the sheer volume of big data produced by IoT devices. As a result, there’s a growing trend toward tape-based storage that sees non-critical data physically stored off site over the long term, rather than compromising a company’s digital footprint. Bottom line? Multiple storage types are necessary to handle the information deluge.
even flash and PaaS won’t be enough to meet the sheer volume of big data produced by IoT devices
The next step in managing IoT data? Recognizing that not everything is important. Can companies drill down and grab usable data from light-switch monitoring sensors? Sure — with the right analytics tool it’s possible to improve space utilization and reduce total electricity spend. But will this same data always have comparably high value? Not likely. Enterprise Apps Today puts it simply: Some data just needs to be read and thrown away. The trick is telling actionable, immediately relevant data from less useful counterparts, and then funnelling this data into a usable stream. As IoT technology becomes more sophisticated, expect a commensurate rise in data funnelling technologies that help companies automatically separate critical data from overflow information.
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Seeing Is Believing
Even with the right data on tap, it may be difficult for companies to develop actionable, IoT-based strategies. Why? Because while IT and analytics professionals are used to working with this kind of unending information stream, C-suite decision-makers have a very different worldview. The result? A kind of miscommunication when data hits the boardroom: If executives can’t make sense of what they see, there’s little chance they’ll choose to act. The solution? Improved data visualization tools. By simplifying gathered data into easily consumable “bites” of information, it’s possible to communicate the core message of complex concepts without overwhelming those without prior IoT knowledge. Think of data visualization like a translator, allowing decision-makers and stakeholders to effectively tap the critical message of IoT integration.
Think of data visualization like a translator, allowing decision-makers and stakeholders to effectively tap the critical message of IoT integration.
The best is yet to come for IoT and big data. With the right storage solutions, funnel techniques and visualization tools, companies can get ahead of the game.