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Editorial Review of “Building Industrial Digital Twins”

Rocket-Powered Data Science

It is an insight engine, providing not only data for descriptive and diagnostic analytics applications, but also providing essential data for predictive and prescriptive analytics applications. examples, with constant reminders that’s it all about the data plus analytics! The digital twin is more than a data collector.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Prescriptive analytics is the application of testing and other techniques to recommend specific solutions that will deliver desired business outcomes. Simplilearn adds a fourth technique : Diagnostic analytics: Why is it happening? Examples of business analytics. San Jose Sharks build fan engagement.

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BRIDGEi2i Named as A Cool Vendor by Gartner In CRM Sales Technologies

bridgei2i

BRIDGEi2i is recognized as cool for its advanced analytics solution, BRIDGEfunnel, an AI-based diagnostic analytics tool, supported by predictive analytics functions, that can be used in lieu of enterprise-grade advanced analytics platforms. Email: venkat.subramanian@bridgei2i.com.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

An electrical engineer can use prescriptive analytics to digitally design and test out various electrical systems to see expected energy output and predict the eventual lifespan of the system’s components. Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred.

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Birst Named to Constellation ShortList™ for Cloud-Based Business Intelligence and Analytics Platforms for 4th Straight Time

Birst BI

Constellation Research predicts that by 2020, 60 percent of mission-critical data will be accessed, rather than owned by enterprises – with external sources including SaaS, social networks, third-party enrichment data and partner information. Data-management capabilities, including data integration and self-service data preparation.

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Defining clear metrics to drive model adoption and value creation

Domino Data Lab

It’s often stated that nothing changes inside an enterprise because you’ve built a model. As Gartner, Harvard, and other organizations keep reminding us , most models fail to reach production inside modern enterprise organizations. Leveraging usage/health metrics to drive model iteration and better end-user adoption.

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