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Link to Best Practices for Deploying and Scaling Industrial AI

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Artificial Intelligence (AI) is transforming industrial operations, helping organizations optimize workflows, reduce downtime, and enhance productivity. Different industry verticals leverage AI in unique ways.

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The Center for Adaptive Edge Intelligence

Adaptive edge intelligence brings real-time decision-making to the point of data creation, whether from sensors, machines, or cameras.

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The Value of Vehicle Electrification

Electric vehicles (EVs) present automakers with many design, engineering, and manufactu ring challenges.

Link to Accelerating Manufacturing Digital Transformation with Industrial Connectivity and IoT

Accelerating Manufacturing Digital Transformation with Industrial Connectivity and IoT

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Leading a transportation revolution in autonomous, electric, shared mobility and connectivity with the next generation of design and development tools.

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Center for Data Pipeline Automation

As businesses become data-driven and rely more heavily on analytics to operate, getting high-quality, trusted data to the right data user at the right time is essential.

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Center for Automated Integration

The goal of automated integration is to enable applications and systems that were built separately to easily share data and work together, resulting in new capabilities and efficiencies that cut costs, uncover insights, and much more.

Link to Continuous Intelligence: Insights

Continuous Intelligence: Insights

Digital transformation requires continuous intelligence (CI). Today’s digital businesses are leveraging this new category of software which includes real-time analytics and insights from a single, cloud-native platform across multiple use cases to speed decision-making, and drive world-class customer experiences.
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Proactive Computing: Changing the Future

Proactive Computing: Changing the Future

proactive computing prescriptive analytics

“Imagine a world where it is possible to prevent problems or capitalize on opportunities before they even occur.”

Written By

Dr. Opher Etzion

Jan 18, 2016

In the movie “The Source Code,” the idea is to prevent a train wreck from happening. But what if computer code could do that?

Analytics has evolved from descriptive to predictive analytics, which shows the probability of certain events occurring. A third rung is prescriptive analytics, which shows why an event will happen and the outcome of certain decisions.

Analytics is growing increasingly sophisticated, however, with the ability to take in complex information, make decisions, and alter the future. That’s an analytic horizon we call “proactive computing.”

In this special report from RTInsights, you will learn:

Examples of proactive, event-driven computing, including condition-based maintenance, prevention of traffic congestion, and disaster management
How proactive computing uses predictive analytics to make operational decisions
The four phases of a proactive system
Schemes for various proactive computing scenarios

Want more? Check out our most-read content:

White Paper: How to ‘Future-Proof’ a Streaming Analytics Platform
Research from Gartner: Real-Time Analytics with the Internet of Things
E-Book: How to Move to a Fast Data Architecture
The Value of Bringing Analytics to the Edge
Three Types of IoT Analytics: Approaches and Use Cases
How AmEx Found Gold With Machine Learning
What’s Behind the Attraction to Apache Spark
John Bates, Plat.One: Enterprise IoT Doesn’t Have to Be Hard

Liked this article? Share it with your colleagues!

Dr. Opher Etzion

Dr. Opher Etzion is professor of information systems and head of the Technological Empowerment Institute in Yezreel Valley College in Israel. He is also a former chief scientist of event processing at the IBM Haifa Research Lab (full bio) . Follow him on Twitter @opheretzion.

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