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November 07, 2016
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Big Data and IoT

Hortonworks sees big data and IoT evolving together. After all, every business is a data business. And in a connected world everything is an IoT device.

For example, consider the connected car. The connected car is actually multiple use cases of IoT data. There is data from the car needed for scheduled maintenance,  recalls and safe operations. There is data from the driver and the car to calculate insurance premiums and infotainment habits. There is data about the environment collected by sensors, the driver, and the car itself to assist with route optimization and autonomous driving. The list goes on an on. Everything is a tangled web of information creating an unprecedented deluge of data never before possible.

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Beyond the data itself, there is a need for real-time insights. In many ways, that’s what the promise of IoT brings. Big data generated by IoT brings the promise of immediacy, of real-time responsiveness and even predictive, personalized options.

But how does one make it all work?  IoT means data is being collected from all types of sources, often on the edge – in highly constrained, sometimes high latency environments. How often has your phone hit a “dead spot” on the road, or for some unexplainable reasons dropped a call? Or lost those 3 or 4 bars of 3G or 4G data connectivity? If your car sensor, IoT endpoint, your remote controlled security camera, your fitness or heart rate monitor lost some data what would that mean? Does a missing piece of data mean the car has had an accident? Or that your heart has stopped? Probably not, but how does the system monitoring this data know that it was just a glitch and not serious problem?  If it knew you were in a cellular “deadspot” then it would know.  Context is critical in IoT applications, and context comes from yet more data to be collected, analyzed and delivered.

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Join us on Nov 17 to learn more from Hortonworks and Denodo on how a complete picture of IoT data enabled by Hortonworks connected data platforms and Denodo data virtualization enable the big data insights demanded by business today. Don’t miss this opportunity to cut through the hype in understanding the critical technologies that form the backbone of IoT solutions.

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Comments

  • Big Data in the Automotive Industry: 2017 – 2030
    Opportunities, Challenges, Strategies & Forecasts

    SNS Research estimates that Big Data investments in the automotive industry will account for over $2.8 Billion in 2017 alone. Led by a plethora of business opportunities for automotive OEMs, tier-1 suppliers, insurers, dealerships and other stakeholders, these investments are further expected to grow at a CAGR of approximately 12% over the next three years.

    For Further Details Contact at Jawad.abbas@snscommunication.com

  • At Saturam http://www.saturam.com/, we know that greatness in a connected-era requires audacious re-interpretation of status-quo, best-in-class talent and a culture that believes in conquering together. We approach every device, data and AI challenge holistically, with tier-1 expertise in the areas of Banking, Manufacturing, Food, Hospitality, Retail and Telco. On-premise, On-cloud, On-edge.

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