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    • IoT without analytics is a non-starter

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    Analytics drives IoT value
    The constant momentum driving ever-changing trends in technology has been gaining a new kind of thrust. The effect on society and how we live reflects this – and sometimes it can seem suffocating. The Internet of Things (IoT) is one of those major tech trends. But like so many developments, it is only when combined with other technologies that it becomes powerful. In fact, IoT devices don't actually offer much on their own.

    Making the connection

    An IoT device only becomes useful when the user collects, stores, and analyzes the data it provides. This link between the IoT and data analytics is critical. Big data gives a company the opportunity to assess, predict and, as a result, improve efficiency by learning more about how their assets and products are consumed. With IoT devices providing new sources of data, the picture of what is actually happening is more complete. Often this will reveal an insight which had previously been overlooked.

    IoT storage and computing

    The other component of connected IoT system is cloud storage and computing. By connecting the device to the internet, users are able to store its valuable data prior to analysis and manipulation. This only works with the right environment, though. With the increase in connected devices (according to Gartner, 5.5 million new things were connected to the Internet every day in 2016) having a platform which performs at scale can be complex.

    Architecting for scale—and doing it in a cost-effective way—is challenging. It requires a specialist set of skills and expertise. A platform that allows you to collect and analyze the data is the foundation for delivering the business insights you are looking to deliver.

    Cloud platforms are well-placed to provide the capacity for growth needed, and the explosion in features from providers such as Amazon and Microsoft mean they are now available at an unprecedentedly low cost of entry.

    IoT, data analytics, and the cloud

    In isolation, IoT, data analytics and cloud are limited, but when combined to build a business platform, they can transform how a business operates.

    Each has a part to play in the continued development of technology adoption. Measure, store and analyze are the three vectors which are powering today's most successful businesses.

    The 7 laws of IoT cloud data
    • Until an IoT device transmits its data back to a cloud server, then the installed base of network software cannot act to provide analytics (and contextual relevance) and send findings forward for further action.
    • Until an IoT device transmits its data back to a cloud server, that data is just 'raw' data.
    • Until an IoT device transmits its data back to a cloud server, that data has not been stored in any relevant column store or database so is at risk of loss if the device is compromised.
    • Until an IoT device transmits its data back to a cloud server, the data may be comparatively unstructured and reside in uncharted areas of the so-called data lake.
    • Until an IoT device transmits its data back to a cloud server, little or no predictive action can be taken. In effect, the device is 'flying blind'.
    • Until an IoT device transmits its data back to a cloud server, it cannot connect, via APIs, to the wider software universe in which it needs to reside.
    • Until an IoT device transmits its data back to a cloud server, that data cannot be secured and stored.

    Data transformed into actionable operational intelligence removes the guesswork from decision making. Get more Insights on analytics for IoT.
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