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Predictive vs. Prescriptive Analytics: What’s the Difference?

Dataiku

The bulk of an organization’s data science, machine learning, and AI conquests come down to improving decision-making capabilities. When during this process, though, should data executives get either predictive or prescriptive?

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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Skilled IT pay defined by volatility, security, and AI

CIO Business Intelligence

AI skills more valuable than certifications There were a couple of stand-outs among those. AI skills more valuable than certifications There were a couple of stand-outs among those.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Hype Cycle for Supply Chain Strategy, 2020

Read the latest insights on AI, IoT, network design, machine learning, prescriptive analytics and other hot technologies. Gartner’s latest recommendations on tried and true capabilities. Find out what's essential to supply chain excellence. Research insights on new technologies. Vendors you can work with.

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward. Business analytics techniques.

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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 CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. But if they wait another three years, they will never catch up.”

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Common Use Cases for Mathematical Optimization

Mathematical optimization is a subset of artificial intelligence and a type of prescriptive analytics. How can this type of prescriptive analytics be applied to lower costs, reduce carbon emissions and build more resilient supply chains? Want ballpark estimates of value and benefits achieved through optimization.