Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities

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Jennifer Priestley Robert McGrath

Closing the Analytics Talent Gap

An Executive's Guide to Working with Universities

Jennifer Priestley, Robert McGrath

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English

CRC Press
04 May 2021

Databases; Network management; Computer science

Series: Data Analytics Applications

"How can we recruit out of your program? We have a project – how do we reach out to your students? If we do research together who owns it? We have employees who need to ""upskill"" in analytics – can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a ""real"" analytical project in the classroom? How can I get ""real"" data to help my students develop the skills necessary to be a ""data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent?

After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive’s Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel.

Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data – structured and unstructured, static and in-motion, voice, text, and image – into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding ""data natives"" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment.

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By: Jennifer Priestley, Robert McGrath
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 185g
ISBN: 9780367486907
ISBN 10: 0367486903
Series: Data Analytics Applications
Pages: 108
Publication Date: 04 May 2021
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Chapter 1. Analytics and Data Science 101. Chapter 2. Navigating Universities -- Where to Start. Chapter 3. Collaborating with Undergraduate Programs. Chapter 4. Collaborating with Master's Programs. Chapter 5. Collaborating with Doctoral Programs. Chapter 6. Continuing Education, Training, and Professional Development.

"Jennifer Lewis Priestley, Ph.D. is a Professor of Statistics and Data Science. Since 2004, she has served as the Associate Dean of the Graduate College and as the Executive Director of the Analytics and Data Science Institute at Kennesaw State University. In 2012, the SAS Institute recognized Dr. Priestley as the 2012 Distinguished Statistics Professor of the Year. She served as the 2012 and 2015 Co-Chair of the National Analytics Conference. Datanami recognized Dr. Priestley as one of the top 12 ""Data Scientists to Watch in 2016."" She architected the first Ph.D. Program in Data Science, which launched in February 2015. Robert Joseph McGrath, Ph.D. is the Everett B Sackett Professor of Health Management and Policy within the College of Health and Human Services at the University of New Hampshire. Since 2018 he has served as the Chair of the Department of Health Management and Policy and the Director of the Graduate Programs in Health Data Science. Prior to that time, he founded and directed the UNH Graduate Programs in Analytics and Data Science."