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Editorial Review of “Building Industrial Digital Twins”

Rocket-Powered Data Science

This book is a very timely contribution to the world of industrial digital transformation. The digital twin is more than a data collector. examples, with constant reminders that’s it all about the data plus analytics! It is truly a business digital transformation manual. 6) Specific Industry 4.0

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT).

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Citizen Data Scientists Are Key. So Is the Solution They Use.

Smarten

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

What is data analytics? Data analytics is a discipline focused on extracting insights from data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. In business, predictive analytics uses machine learning, business rules, and algorithms.

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MRO spare parts optimization

IBM Big Data Hub

These supplies include everything from large infrastructure items such as turbines, generators, transformers and heating, ventilation and air conditioning systems to smaller items like gears, grease and mops. regulations, undergoing digital transformation and the need for cost-cutting. Now, consider the just-in-case approach.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. All they would have to do is just build their model and run with it,” he says.

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AIOps reimagines hybrid multicloud platform operations

IBM Big Data Hub

Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following: Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT infrastructure components, applications and performance-monitoring tools. Predictive analytics to show what will happen next.