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| 001 | | 000000321718 |
| 003 | | OCoLC |
| 005 | | 20230613111503 |
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| 007 | | cr |n||||||||| |
| 008 | | 210320s2021 xx o 0|| 0 eng d |
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▼a 1242466353
▼a 1243536680
▼a 1251804336 |
| 020 | |
▼a 9781000376548
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▼a 2891538
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▼a (OCoLC)1242465662
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| 037 | |
▼a 9781003042303
▼b Taylor & Francis |
| 040 | |
▼a YDX
▼b eng
▼c YDX
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▼d EBLCP
▼d TYFRS
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▼d 248032 |
| 049 | |
▼a MAIN |
| 050 | 4 |
▼a LC1085 |
| 072 | 7 |
▼a COM
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▼2 bisacsh |
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▼2 bicssc |
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▼a 378.1035
▼2 23 |
| 100 | 1 |
▼a PRIESTLEY, JENNIFER. MCGRATH, ROBERT. |
| 245 | 10 |
▼a CLOSING THE ANALYTICS TALENT GAP
▼h [electronic resource] :
▼b an executive's guide to working with universities. |
| 260 | |
▼a [S.l.] :
▼b CRC PRESS,
▼c 2021. |
| 300 | |
▼a 1 online resource |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b c
▼2 rdamedia |
| 338 | |
▼a online resource
▼b cr
▼2 rdacarrier |
| 490 | 1 |
▼a Data Analytics Applications |
| 505 | 0 |
▼a Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgements -- About the Authors -- 1. Analytics and Data Science 101 -- From Plato to Davenport and Patil -- Universities Answer the Call -- A Wide Range of Solutions -- Endnotes -- 2. Navigating Universities -- Where to Start -- Universities 101 -- What Do Universities Actually Do? -- University Classifications and the Role of Research -- Teaching and Training -- Incentives -- Why Would a Faculty Member Take Your Call? -- The Taxonomy of Faculty -- Tenured Faculty |
| 505 | 8 |
▼a Pre-Tenure (Tenure-Track) Faculty -- Non-Tenure Track Faculty -- Research Faculty -- A View from the Ground -- Khalifeh Al-Jadda, Director of Data Science, The Home Depot -- Internships -- Research Collaboration -- Advisory Board Membership -- Our Summary Checklist for Working with Universities -- Endnotes -- 3. Collaborating with Undergraduate Programs -- What Do Undergraduates Really Know? -- The Rise of Undergraduate Data Science Programs -- Views from the Ground -- Structuring Successful Internships -- Structuring Successful Capstones -- High Impact in Action -- Two Case Studies |
| 505 | 8 |
▼a Our Summary Checklist for Working with Undergraduate Students -- Endnotes -- 4. Collaboration with Master's Programs -- Differences Between Master's and Undergraduate Education -- The Rise of Master's Programs in Analytics and Data Science -- A View from the Ground -- The University -- The Company -- The Student -- Our Summary Checklist for Working with Master's Students -- Endnotes -- 5. Collaboration with Doctoral Programs -- Differences Between Doctoral and Master's-Level Education -- The Rise of the PhD in Data Science -- Establishing a Research Lab -- A View from the Ground |
| 505 | 8 |
▼a Christopher Yasko, Equifax Vice President, Innovation Office -- A Second View from the Ground -- Our Summary Checklist for Research Partnerships with University Doctoral Programs -- Endnotes -- 6. Continuing Education, Training, and Professional Development -- Continuing Education 101 -- Analytics and Data Science -- Revisited -- Certificates, Certifications, Badges, "Mini" Degrees, and MOOCs -- Certificates -- Digital Badges/Micro-Credentials -- Massive Online Open Courses (MOOCs) -- "Mini" Degree -- Certification -- A View from the GroundThe |
| 505 | 8 |
▼a Tim Blumentritt, PhD, Dean, College of Continuing and Professional Education -- Our Summary Checklist for Working with Universities for Continuing Education -- Endnotes -- Index |
| 520 | |
▼a 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. . |
| 590 | |
▼a Master record variable field(s) change: 050, 072, 082, 650 - OCLC control number change |
| 650 | 0 |
▼a Academic-industrial collaboration. |
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▼a COMPUTERS / Database Management / General
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▼a Academic-industrial collaboration.
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▼a Data mining.
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▼0 (OCoLC)fst00887946 |
| 655 | 4 |
▼a Electronic books. |
| 776 | 08 |
▼c Original
▼z 0367486903
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▼w (OCoLC)1202747281 |
| 830 | 0 |
▼a Data analytics applications. |
| 856 | 40 |
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