Winning with Data Science : : A Handbook for Business Leaders / / Akshay Swaminathan, Howard Steven Friedman.
Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehe...
Saved in:
| Superior document: | Title is part of eBook package: De Gruyter Columbia University Press Complete eBook-Package 2024 |
|---|---|
| VerfasserIn: | |
| Place / Publishing House: | New York, NY : : Columbia University Press, , [2024] 2024 |
| Year of Publication: | 2024 |
| Language: | English |
| Online Access: | |
| Physical Description: | 1 online resource :; 13 figures |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
9780231556699 |
|---|---|
| ctrlnum |
(DE-B1597)679662 |
| collection |
bib_alma |
| record_format |
marc |
| spelling |
Friedman, Howard Steven, author. aut http://id.loc.gov/vocabulary/relators/aut Winning with Data Science : A Handbook for Business Leaders / Akshay Swaminathan, Howard Steven Friedman. New York, NY : Columbia University Press, [2024] 2024 1 online resource : 13 figures text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Frontmatter -- CONTENTS -- Acknowledgments -- Introduction -- 1 Tools of the Trade -- 2 The Data Science Project -- 3 Data Science Foundations -- 4 Making Decisions with Data -- 5 Clustering, Segmenting, and Cutting Through the Noise -- 6 Building Your First Model -- 7 Tools for Machine Learning -- 8 Pulling It Together -- 9 Ethics -- Conclusion -- Notes -- Index restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehensive guide to data science, emphasizing its real-world business applications and focusing on how to collaborate productively with data science teams.Taking an engaging narrative approach, Winning with Data Science covers the fundamental concepts without getting bogged down in complex equations or programming languages. It provides clear explanations of key terms, tools, and techniques, illustrated through practical examples. The book follows the stories of Kamala and Steve, two professionals who need to collaborate with data science teams to achieve their business goals. Howard Steven Friedman and Akshay Swaminathan walk readers through each step of managing a data science project, from understanding the different roles on a data science team to identifying the right software. They equip readers with critical questions to ask data analysts, statisticians, data scientists, and other technical experts to avoid wasting time and money. Winning with Data Science is a must-read for anyone who works with data science teams or is interested in the practical side of the subject. Mode of access: Internet via World Wide Web. In English. Description based on online resource; title from PDF title page (publisher's Web site, viewed 07. Feb 2024) Data mining. Databases. Electronic data processing. COMPUTERS / Database Management / Data Mining. bisacsh Swaminathan, Akshay, author. aut http://id.loc.gov/vocabulary/relators/aut Title is part of eBook package: De Gruyter Columbia University Press Complete eBook-Package 2024 9783110749687 https://doi.org/10.7312/frie20686 https://www.degruyter.com/isbn/9780231556699 Cover https://www.degruyter.com/document/cover/isbn/9780231556699/original |
| language |
English |
| format |
eBook |
| author |
Friedman, Howard Steven, Friedman, Howard Steven, Swaminathan, Akshay, |
| spellingShingle |
Friedman, Howard Steven, Friedman, Howard Steven, Swaminathan, Akshay, Winning with Data Science : A Handbook for Business Leaders / Frontmatter -- CONTENTS -- Acknowledgments -- Introduction -- 1 Tools of the Trade -- 2 The Data Science Project -- 3 Data Science Foundations -- 4 Making Decisions with Data -- 5 Clustering, Segmenting, and Cutting Through the Noise -- 6 Building Your First Model -- 7 Tools for Machine Learning -- 8 Pulling It Together -- 9 Ethics -- Conclusion -- Notes -- Index |
| author_facet |
Friedman, Howard Steven, Friedman, Howard Steven, Swaminathan, Akshay, Swaminathan, Akshay, Swaminathan, Akshay, |
| author_variant |
h s f hs hsf h s f hs hsf a s as |
| author_role |
VerfasserIn VerfasserIn VerfasserIn |
| author2 |
Swaminathan, Akshay, Swaminathan, Akshay, |
| author2_variant |
a s as |
| author2_role |
VerfasserIn VerfasserIn |
| author_sort |
Friedman, Howard Steven, |
| title |
Winning with Data Science : A Handbook for Business Leaders / |
| title_sub |
A Handbook for Business Leaders / |
| title_full |
Winning with Data Science : A Handbook for Business Leaders / Akshay Swaminathan, Howard Steven Friedman. |
| title_fullStr |
Winning with Data Science : A Handbook for Business Leaders / Akshay Swaminathan, Howard Steven Friedman. |
| title_full_unstemmed |
Winning with Data Science : A Handbook for Business Leaders / Akshay Swaminathan, Howard Steven Friedman. |
| title_auth |
Winning with Data Science : A Handbook for Business Leaders / |
| title_alt |
Frontmatter -- CONTENTS -- Acknowledgments -- Introduction -- 1 Tools of the Trade -- 2 The Data Science Project -- 3 Data Science Foundations -- 4 Making Decisions with Data -- 5 Clustering, Segmenting, and Cutting Through the Noise -- 6 Building Your First Model -- 7 Tools for Machine Learning -- 8 Pulling It Together -- 9 Ethics -- Conclusion -- Notes -- Index |
| title_new |
Winning with Data Science : |
| title_sort |
winning with data science : a handbook for business leaders / |
| publisher |
Columbia University Press, |
| publishDate |
2024 |
| physical |
1 online resource : 13 figures |
| contents |
Frontmatter -- CONTENTS -- Acknowledgments -- Introduction -- 1 Tools of the Trade -- 2 The Data Science Project -- 3 Data Science Foundations -- 4 Making Decisions with Data -- 5 Clustering, Segmenting, and Cutting Through the Noise -- 6 Building Your First Model -- 7 Tools for Machine Learning -- 8 Pulling It Together -- 9 Ethics -- Conclusion -- Notes -- Index |
| isbn |
9780231556699 9783110749687 |
| callnumber-first |
H - Social Science |
| callnumber-subject |
HD - Industries, Land Use, Labor |
| callnumber-label |
HD30 |
| callnumber-sort |
HD 230.215 F74 42024 |
| url |
https://doi.org/10.7312/frie20686 https://www.degruyter.com/isbn/9780231556699 https://www.degruyter.com/document/cover/isbn/9780231556699/original |
| illustrated |
Not Illustrated |
| dewey-hundreds |
600 - Technology |
| dewey-tens |
650 - Management & public relations |
| dewey-ones |
658 - General management |
| dewey-full |
658.4/033 |
| dewey-sort |
3658.4 233 |
| dewey-raw |
658.4/033 |
| dewey-search |
658.4/033 |
| doi_str_mv |
10.7312/frie20686 |
| work_keys_str_mv |
AT friedmanhowardsteven winningwithdatascienceahandbookforbusinessleaders AT swaminathanakshay winningwithdatascienceahandbookforbusinessleaders |
| status_str |
n |
| ids_txt_mv |
(DE-B1597)679662 |
| carrierType_str_mv |
cr |
| hierarchy_parent_title |
Title is part of eBook package: De Gruyter Columbia University Press Complete eBook-Package 2024 |
| is_hierarchy_title |
Winning with Data Science : A Handbook for Business Leaders / |
| container_title |
Title is part of eBook package: De Gruyter Columbia University Press Complete eBook-Package 2024 |
| author2_original_writing_str_mv |
noLinkedField noLinkedField |
| _version_ |
1792281689383239680 |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04131nam a22006375i 4500</leader><controlfield tag="001">9780231556699</controlfield><controlfield tag="003">DE-B1597</controlfield><controlfield tag="005">20240207110643.0</controlfield><controlfield tag="006">m|||||o||d||||||||</controlfield><controlfield tag="007">cr || ||||||||</controlfield><controlfield tag="008">240207t20242024nyu fo d z eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780231556699</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.7312/frie20686</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-B1597)679662</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-B1597</subfield><subfield code="b">eng</subfield><subfield code="c">DE-B1597</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">nyu</subfield><subfield code="c">US-NY</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">HD30.215</subfield><subfield code="b">.F74 2024</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM021030</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">658.4/033</subfield><subfield code="2">23/eng/20230714</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Friedman, Howard Steven, </subfield><subfield code="e">author.</subfield><subfield code="4">aut</subfield><subfield code="4">http://id.loc.gov/vocabulary/relators/aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Winning with Data Science :</subfield><subfield code="b">A Handbook for Business Leaders /</subfield><subfield code="c">Akshay Swaminathan, Howard Steven Friedman.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY : </subfield><subfield code="b">Columbia University Press, </subfield><subfield code="c">[2024]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource :</subfield><subfield code="b">13 figures</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="347" ind1=" " ind2=" "><subfield code="a">text file</subfield><subfield code="b">PDF</subfield><subfield code="2">rda</subfield></datafield><datafield tag="505" ind1="0" ind2="0"><subfield code="t">Frontmatter -- </subfield><subfield code="t">CONTENTS -- </subfield><subfield code="t">Acknowledgments -- </subfield><subfield code="t">Introduction -- </subfield><subfield code="t">1 Tools of the Trade -- </subfield><subfield code="t">2 The Data Science Project -- </subfield><subfield code="t">3 Data Science Foundations -- </subfield><subfield code="t">4 Making Decisions with Data -- </subfield><subfield code="t">5 Clustering, Segmenting, and Cutting Through the Noise -- </subfield><subfield code="t">6 Building Your First Model -- </subfield><subfield code="t">7 Tools for Machine Learning -- </subfield><subfield code="t">8 Pulling It Together -- </subfield><subfield code="t">9 Ethics -- </subfield><subfield code="t">Conclusion -- </subfield><subfield code="t">Notes -- </subfield><subfield code="t">Index</subfield></datafield><datafield tag="506" ind1="0" ind2=" "><subfield code="a">restricted access</subfield><subfield code="u">http://purl.org/coar/access_right/c_16ec</subfield><subfield code="f">online access with authorization</subfield><subfield code="2">star</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehensive guide to data science, emphasizing its real-world business applications and focusing on how to collaborate productively with data science teams.Taking an engaging narrative approach, Winning with Data Science covers the fundamental concepts without getting bogged down in complex equations or programming languages. It provides clear explanations of key terms, tools, and techniques, illustrated through practical examples. The book follows the stories of Kamala and Steve, two professionals who need to collaborate with data science teams to achieve their business goals. Howard Steven Friedman and Akshay Swaminathan walk readers through each step of managing a data science project, from understanding the different roles on a data science team to identifying the right software. They equip readers with critical questions to ask data analysts, statisticians, data scientists, and other technical experts to avoid wasting time and money. Winning with Data Science is a must-read for anyone who works with data science teams or is interested in the practical side of the subject.</subfield></datafield><datafield tag="538" ind1=" " ind2=" "><subfield code="a">Mode of access: Internet via World Wide Web.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">In English.</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Description based on online resource; title from PDF title page (publisher's Web site, viewed 07. Feb 2024)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Data mining.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Databases.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Electronic data processing.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">COMPUTERS / Database Management / Data Mining.</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Swaminathan, Akshay, </subfield><subfield code="e">author.</subfield><subfield code="4">aut</subfield><subfield code="4">http://id.loc.gov/vocabulary/relators/aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Title is part of eBook package:</subfield><subfield code="d">De Gruyter</subfield><subfield code="t">Columbia University Press Complete eBook-Package 2024</subfield><subfield code="z">9783110749687</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.7312/frie20686</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.degruyter.com/isbn/9780231556699</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="3">Cover</subfield><subfield code="u">https://www.degruyter.com/document/cover/isbn/9780231556699/original</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_CL_CHCOMSGSEN</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_EBKALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_ECL_CHCOMSGSEN</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_EEBKALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_ESTMALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_PPALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_STMALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV-deGruyter-alles</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">PDA12STME</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">PDA13ENGE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">PDA18STMEE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">PDA5EBK</subfield></datafield></record></collection> |