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020 _a9783030224073
_9978-3-030-22407-3
024 7 _a10.1007/978-3-030-22407-3
_2doi
050 4 _aLB1028.3
072 7 _aJNV
_2bicssc
072 7 _aEDU000000
_2bisacsh
072 7 _aJNV
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082 0 4 _a371.33
_223
100 1 _aRawlings-Goss, Renata.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aData Science Careers, Training, and Hiring
_h[electronic resource] :
_bA Comprehensive Guide to the Data Ecosystem: How to Build a Successful Data Science Career, Program, or Unit /
_cby Renata Rawlings-Goss.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXVII, 85 p. 3 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5776
505 0 _aIntroduction -- Building Data Careers -- Building Data Programs -- Building Data Talent and Workforce -- Conclusion. .
520 _aThis book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growthin this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, whothey want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build.
650 0 _aEducational technology.
650 0 _aTechnical education.
650 0 _aTechnology
_xSociological aspects.
650 1 4 _aDigital Education and Educational Technology.
650 2 4 _aEngineering and Technology Education.
650 2 4 _aScience, Technology and Society.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030224066
776 0 8 _iPrinted edition:
_z9783030224080
776 0 8 _iPrinted edition:
_z9783030224097
830 0 _aSpringerBriefs in Computer Science,
_x2191-5776
856 4 0 _uhttps://doi.org/10.1007/978-3-030-22407-3
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c172803
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