Tame the IoT Data Tsunami

Find out how a new, built-for-IoT dataviz solution is helping firms make better decisions, more easily in an age of ever-increasing data volumes and complexity.

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For enterprises seeking to leverage analytics to fuel growth, Hopara is the MIT-developed IoT analytics solution that empowers any business user to easily make better, data-driven decisions—powered by a set of unique capabilities that combine limitless, live data; support for real-time actionable insights; and everybody ready usability.

Firms are increasingly drowning in the sheer volume of data generated by growing mobile data, cloud computing traffic, IoT, AI.
And it’s clear that today’s analytic tools are not up to the task of easily providing actionable insights from all of that data.

In this webinar you’ll learn about a solution that:

  • Builds visualization + decision-support apps that refresh as fast as your data
  • Gives you a dynamic picture of NOW (not a historic snapshot) from diverse data elements within the same visualization
  • Enables fast, painless adoption that allows all decision makers to fully engage with all available dat

Your Host

Prof. Michael Stonebraker  

Michael Stonebraker is a pioneer of database research and technology. He joined the University of California, Berkeley, as an assistant professor in 1971 and taught in computer science and EECS departments for 29 years. While at Berkeley, he developed prototypes for the INGRES relational data management system, the object-relational DBMS, POSTGRES, and the federated system, Mariposa. He is the founder of three successful Silicon Valley startups whose obiective was to commercialize these prototypes. Mike is the author of scores of research papers on database technology, operating systems, and the architecture of system software services. He was awarded the ACM System Software Award in 1992 (for INGRES) and the Turing Award in 2015. He was elected to the National Academy of Engineering and is presently an adjunct professor of computer science at MIT’s Computer Science and Al Laboratory CSAIL.)

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