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3 Compelling Ways IoT is Changing the Solar Industry

Smart Data Collective

The Internet of Things is one of the fastest growing industries. This explains the growing number of solar companies turning to big data. Since there is enough historical data, the energy companies can apply analytical and predictive models to calculate power generation rates under certain weather conditions.

IoT 99
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Otis takes the smart elevator to new heights

CIO Business Intelligence

Otis One’s cloud-native platform is built on Microsoft Azure and taps into a Snowflake data lake. IoT sensors send elevator data to the cloud platform, where analytics are applied to support business operations, including reporting, data visualization, and predictive modeling. based company’s elevators smarter.

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A Window Into the Future of Data in Motion and What It Means for Businesses

CIO Business Intelligence

At the same time, 5G adoption accelerates the Internet of Things (IoT). The possibilities of data in motion are endless and will be explored in our upcoming webinar with Cloudera APAC Field CTO Daniel Hand , Are You Ready for the Future of Data in Motion? .

IoT 80
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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

In the enterprise, sentinel analytics is most timely and beneficial when applied to real-time, dynamic data streams and time-critical decisions. Broken models are definitely disruptive to analytics applications and business operations. the predicted outcome Y from existing models will not occur in this case).

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list. How can we make it happen?

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models.

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Asset lifecycle management best practices: Building a strategy for success

IBM Big Data Hub

That data is then fed into AI-enabled CMMS, where advanced data analysis tools and processes like machine learning (ML) spot issues and help resolve them. This information is then used to build predictive models of asset performance over time and help spot potential problems before they arise.