This week’s roundup discusses the benefits of AI for nonprofits, executives’ mistrust of internal data, Stephen Few’s new book Big Data, Big Dupe: A little book about a big bunch of nonsense, preparing for a data science transformation, and what universities need to know about teaching data science.
by Tal Frankfurt, Founder and CEO of Cloud for Good, featured on Forbes
Organizations are becoming more aware of the power of AI and are actively searching for ways to bring AI into their respective communities, expand their offerings and improve upon operational capabilities. Among the many benefits for nonprofits, fundraising efforts can be better tracked and predicted using AI.
by Leah Alger, Journalist at 31 Media, featured on Software Testing News
TDWI’s latest report Reducing Inefficiency and Increasing the Value of Analytics and Business Intelligence found that only 11% of respondents said that they were satisfied with their firms’ investments in data and analytics projects to meet strategic goals for enabling data-driven decision-making or actionable customer intelligence.
by Bill Luker Jr, PhD, Economist and Founder of terraNovum Solutions, featured on Predictive Analytics World
In his new book Big Data, Big Dupe: A little book about a big bunch of nonsense (Analytics Press, 2018), Stephen Few discusses how uncritical acceptance of Computer Science-IT Data Science’s (or CS-IT Data Science) ground truth and its applications can lead to wholly incorrect conclusions for methodology and methods (two different things, actually) across the whole of science.
by Robert Berkey, Managing director at Accenture Applied Intelligence, and Dr. Amy Gershkoff, Data Consultant, featured on Datamation
In an era where Artificial Intelligence is reshaping the way we do business, and where technology is only as smart as the analytics that powers it, it’s now widely understood that data science gives organizations a clear competitive edge.
by Meghan Bogardus Cortez, Associate Editor at EdTech
Every industry is seeking ways to collect data in order to discover actionable insights, and demands are increasing in the workforce for people who know how to deal with this data. But, how do higher education institutions prepare the next generation of workers to take on that challenge?
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