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Scalable IoT, In-Database Computing

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Internet of Things (IoT) data is exploding, driven in part by the adoption of connected home technologies such as smart thermostats. While the adoption of connected home technology is increasing at a dramatic rate, creating value from the growing volume of sensor data generated by smart devices requires a new approach to advanced analytics at increasing scale.

Join us for the latest Iot Central webinar to learn how Ecobee, a maker of wi-fi enabled smart thermostats, leverages Vertica advanced analytics to process massive raw data clusters at scale to build thermal models so customers can intelligently manage heating and cooling systems and contribute to a sustainable future.

During this presentation, we will explore how:

  • Vertica in-database machine learning uses massively parallel processing and a familiar SQL interface to accelerate time-to-value on predictive analytics projects
  • Ecobee’s Vertica implementation and broader analytics stack allows them to answer analytics and data science questions faster
  • Ecobee is using smart thermostats and data analytics to unlock new innovations around demand response management, time of use optimization and energy storage


Sina Shahandeh, Director of Data and Analytics -- Ecobee
Benjamin Smith, Senior Product Marketing Manager -- Vertica

Hosted by:
David Oro, Editorial Director -- IoT Central

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  • Fascinating, I know that data science systems are revolutionizing how a lot of industries do business and improving their efficiency and value through the application ofdata science softwareto turn their data into accurate predictive models. But how this applies to IoT and specifically IoT that we all use on a personal basis is also very interesting. 

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