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Home » Podcast Episodes » Rooted in Reliability: The Plant Performance Podcast » 84 – Big Data and IoT with Saar Yoskovitz

by James Kovacevic Leave a Comment

84 – Big Data and IoT with Saar Yoskovitz

Big Data and IoT with Saar Yoskovitz

Every once in a while, there comes an amazing new technology that changes the way of living for people. Internet of Things and Big data are such trending technologies that have revolutionized the lives of everyone. With IoT, you can stay in touch with a lot of things like there are smart TVs, smart cars, and all those wonderful appliances that make your everyday household work easier to a great level of comfort. There is another side of IoT and that is Industrial IoT or IIoT. There are so many changes going around in the industry because of a huge wave of what IoT and Machine learning can do.

With Big data, analysis has been so good that makes the detecting and solving problems so much effective and easy. The world has been introduced with the real computing power to enhance efficiency and save cost. Things have gotten so speedy that it won’t be long before companies normalize their methods involving IIOT and start reaping its benefits at a whole new level.
Everyone in the industry just hates those expensive breakdowns that stop significant progress in your business. That is why Machine Learning and Big data analytics allow to get data and analyze in a real-time environment.

The systems are well connected with the business processes now and are more reliable than ever before. That is why companies are trying to make the IIOT part of their business processes to capture the opportunities that can take their business to a new level of success. This transformation of different businesses through IIOT has certain financial and technical rewards that are hard to ignore in a competitive global economy. That is why big data and IIOT are being implemented in the industry as soon as possible to generate a huge percentage of ROI via Machine Learning that is common these days in the business areas.

The sensor technology is being used to find potential failures in the assets and monitor their performance so closely that has made the predictive maintenance easier and more effective. The manufacturing process has been improved to a level where the cost of failures has reduced to a bare minimum. The data can be gathered and communicated so fast that downtime is reduced to an amazing extent. This algorithm-based approach has made the job of experts simpler because they can perform preventive actions and run diagnostics that gives wonderful results.

This not only empowers big industries but also helps smaller or medium level industries to grow themselves by gaining those competitive advantages that better analysis and simpler methods of big data technology has to offer. The prices of System components and storage devices have been reduced by a lot and that is the reason why companies are availing big data technology. There are already very high estimates of revenues in the next decade and all this has been possible because of the value of data that researchers can find because of improved analysis
techniques.

 

Eruditio Links:

  • Eruditio, LLC
  • A Smarter Way of Preventative Maintenance – Free eBook
  • Maintenance Planning & Scheduling: Planning for Profitability Video Course

Saar Yoskovitz Links:

  • Saar Yoskovitza LinkedIn
  • Augury
  • Augury Blog

 

Rooted in Reliability: The Plant Performance Podcast
Rooted in Reliability: The Plant Performance Podcast
84 - Big Data and IoT with Saar Yoskovitz
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Filed Under: Rooted in Reliability: The Plant Performance Podcast, The Reliability FM network

About James Kovacevic

James is a trainer, speaker, and consultant that specializes in bringing profitability, productivity, availability, and sustainability to manufacturers around the globe.

Through his career, James has made it his personal mission to make industry a profitable place; where individuals and manufacturers possess the resources, knowledge, and courage to sustainably lower their operating costs.

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