Data Analytics : : Systems Engineering - Cybersecurity - Project Management / / Christopher Greco.
Data analytics is creeping into the lexicon of our daily language. This book gives the reader a perspective as to the overall data analytics skill set, starting with a primer on statistics, and works toward the application of those methods. There are a variety of formulas and algorithms used in the...
Saved in:
Superior document: | Title is part of eBook package: De Gruyter MLI AI COLLECTION |
---|---|
VerfasserIn: | |
Place / Publishing House: | Dulles, VA : : Mercury Learning and Information, , [2021] ©2021 |
Year of Publication: | 2021 |
Language: | English |
Online Access: | |
Physical Description: | 1 online resource (148 p.) |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
9781683926474 |
---|---|
ctrlnum |
(DE-B1597)653776 (OCoLC)1232277418 |
collection |
bib_alma |
record_format |
marc |
spelling |
Greco, Christopher, author. aut http://id.loc.gov/vocabulary/relators/aut Data Analytics : Systems Engineering - Cybersecurity - Project Management / Christopher Greco. Dulles, VA : Mercury Learning and Information, [2021] ©2021 1 online resource (148 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Frontmatter -- Contents -- Preface -- Acknowledgments -- 1 Introduction to Statistics for Data Analysts -- 2 What is Data ? -- 3 Statistics Review – Measures of the Central Tendency -- 4 Probability Primer -- 5 Occam’s Razor and Data Analytics -- 6 Data Analysis Tools -- 7 Effect Size -- 8 Analysis Process Methods -- 9 Data Analytics Thinking -- 10 Where’s the Data ? -- 11 Data Presentation -- 12 Geospatial Data Analytics -- 13 Additional Data Analytics Methods -- 14 Summary -- 15 Case Studies -- APPENDIX. RECOMMENDED SOLUTIONS FOR CASE STUDIES -- References -- Index restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star Data analytics is creeping into the lexicon of our daily language. This book gives the reader a perspective as to the overall data analytics skill set, starting with a primer on statistics, and works toward the application of those methods. There are a variety of formulas and algorithms used in the data analytics process. These formulas can be plugged into whatever software application the reader uses to obtain the answer they need. There are several demonstrations of this process to provide straightforward instruction as to how to bring data analytics skills to your critical thinking. This book presents a variety of methods and techniques, as well as case studies, to enrich the knowledge of data analytics for project managers, systems engineers, and cybersecurity professionals. It separates the case studies so that each profession can practice some straightforward data analytics specific to their fields. The main purpose of this text is to refresh the statistical knowledge necessary to build models for data analytics. Along with that, this book encompasses the analytics thinking that is essential to all three professions. Features: Provides straightforward instruction on data analytics methods Includes methods, techniques, and case studies for project managers, systems engineers, and cybersecurity professionals Refreshes the statistical knowledge needed to bring data analytics into your skillset and decision-making Focuses on getting readers up to speed quickly and efficiently to be able to see the impact of data analytics and analytical thinking Issued also in print. 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 02. Jun 2024) Computer security. Data mining. Systems engineering. Data. IT Management & Security. Programming. COMPUTERS / Database Management / Data Mining. bisacsh analytics. business. computer science. cybersecurity. data analysis. data science. programming. statistics. Title is part of eBook package: De Gruyter MLI AI COLLECTION 9783111573533 Title is part of eBook package: De Gruyter Sciendo All Ebooks Trial Collection 2024 9783111502496 EPUB 9781683926467 print 9781683926481 https://doi.org/10.1515/9781683926474 https://www.degruyter.com/isbn/9781683926474 Cover https://www.degruyter.com/document/cover/isbn/9781683926474/original |
language |
English |
format |
eBook |
author |
Greco, Christopher, Greco, Christopher, |
spellingShingle |
Greco, Christopher, Greco, Christopher, Data Analytics : Systems Engineering - Cybersecurity - Project Management / Frontmatter -- Contents -- Preface -- Acknowledgments -- 1 Introduction to Statistics for Data Analysts -- 2 What is Data ? -- 3 Statistics Review – Measures of the Central Tendency -- 4 Probability Primer -- 5 Occam’s Razor and Data Analytics -- 6 Data Analysis Tools -- 7 Effect Size -- 8 Analysis Process Methods -- 9 Data Analytics Thinking -- 10 Where’s the Data ? -- 11 Data Presentation -- 12 Geospatial Data Analytics -- 13 Additional Data Analytics Methods -- 14 Summary -- 15 Case Studies -- APPENDIX. RECOMMENDED SOLUTIONS FOR CASE STUDIES -- References -- Index |
author_facet |
Greco, Christopher, Greco, Christopher, |
author_variant |
c g cg c g cg |
author_role |
VerfasserIn VerfasserIn |
author_sort |
Greco, Christopher, |
title |
Data Analytics : Systems Engineering - Cybersecurity - Project Management / |
title_sub |
Systems Engineering - Cybersecurity - Project Management / |
title_full |
Data Analytics : Systems Engineering - Cybersecurity - Project Management / Christopher Greco. |
title_fullStr |
Data Analytics : Systems Engineering - Cybersecurity - Project Management / Christopher Greco. |
title_full_unstemmed |
Data Analytics : Systems Engineering - Cybersecurity - Project Management / Christopher Greco. |
title_auth |
Data Analytics : Systems Engineering - Cybersecurity - Project Management / |
title_alt |
Frontmatter -- Contents -- Preface -- Acknowledgments -- 1 Introduction to Statistics for Data Analysts -- 2 What is Data ? -- 3 Statistics Review – Measures of the Central Tendency -- 4 Probability Primer -- 5 Occam’s Razor and Data Analytics -- 6 Data Analysis Tools -- 7 Effect Size -- 8 Analysis Process Methods -- 9 Data Analytics Thinking -- 10 Where’s the Data ? -- 11 Data Presentation -- 12 Geospatial Data Analytics -- 13 Additional Data Analytics Methods -- 14 Summary -- 15 Case Studies -- APPENDIX. RECOMMENDED SOLUTIONS FOR CASE STUDIES -- References -- Index |
title_new |
Data Analytics : |
title_sort |
data analytics : systems engineering - cybersecurity - project management / |
publisher |
Mercury Learning and Information, |
publishDate |
2021 |
physical |
1 online resource (148 p.) Issued also in print. |
contents |
Frontmatter -- Contents -- Preface -- Acknowledgments -- 1 Introduction to Statistics for Data Analysts -- 2 What is Data ? -- 3 Statistics Review – Measures of the Central Tendency -- 4 Probability Primer -- 5 Occam’s Razor and Data Analytics -- 6 Data Analysis Tools -- 7 Effect Size -- 8 Analysis Process Methods -- 9 Data Analytics Thinking -- 10 Where’s the Data ? -- 11 Data Presentation -- 12 Geospatial Data Analytics -- 13 Additional Data Analytics Methods -- 14 Summary -- 15 Case Studies -- APPENDIX. RECOMMENDED SOLUTIONS FOR CASE STUDIES -- References -- Index |
isbn |
9781683926474 9783111573533 9783111502496 9781683926467 9781683926481 |
callnumber-first |
Q - Science |
callnumber-subject |
QA - Mathematics |
callnumber-label |
QA76 |
callnumber-sort |
QA 276.9 D343 G74 42021 |
url |
https://doi.org/10.1515/9781683926474 https://www.degruyter.com/isbn/9781683926474 https://www.degruyter.com/document/cover/isbn/9781683926474/original |
illustrated |
Not Illustrated |
dewey-hundreds |
000 - Computer science, information & general works |
dewey-tens |
000 - Computer science, knowledge & systems |
dewey-ones |
006 - Special computer methods |
dewey-full |
006.312 |
dewey-sort |
16.312 |
dewey-raw |
006.312 |
dewey-search |
006.312 |
doi_str_mv |
10.1515/9781683926474 |
oclc_num |
1232277418 |
work_keys_str_mv |
AT grecochristopher dataanalyticssystemsengineeringcybersecurityprojectmanagement |
status_str |
n |
ids_txt_mv |
(DE-B1597)653776 (OCoLC)1232277418 |
carrierType_str_mv |
cr |
hierarchy_parent_title |
Title is part of eBook package: De Gruyter MLI AI COLLECTION Title is part of eBook package: De Gruyter Sciendo All Ebooks Trial Collection 2024 |
is_hierarchy_title |
Data Analytics : Systems Engineering - Cybersecurity - Project Management / |
container_title |
Title is part of eBook package: De Gruyter MLI AI COLLECTION |
_version_ |
1806144019228524544 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05071nam a2200817Ia 4500</leader><controlfield tag="001">9781683926474</controlfield><controlfield tag="003">DE-B1597</controlfield><controlfield tag="005">20240602123719.0</controlfield><controlfield tag="006">m|||||o||d||||||||</controlfield><controlfield tag="007">cr || ||||||||</controlfield><controlfield tag="008">240602t20212021xxu fo d z eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781683926474</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/9781683926474</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-B1597)653776</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1232277418</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">xxu</subfield><subfield code="c">US</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA76.9.D343</subfield><subfield code="b">G74 2021</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">006.312</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Greco, Christopher, </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">Data Analytics :</subfield><subfield code="b">Systems Engineering - Cybersecurity - Project Management /</subfield><subfield code="c">Christopher Greco.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Dulles, VA : </subfield><subfield code="b">Mercury Learning and Information, </subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (148 p.)</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">Preface -- </subfield><subfield code="t">Acknowledgments -- </subfield><subfield code="t">1 Introduction to Statistics for Data Analysts -- </subfield><subfield code="t">2 What is Data ? -- </subfield><subfield code="t">3 Statistics Review – Measures of the Central Tendency -- </subfield><subfield code="t">4 Probability Primer -- </subfield><subfield code="t">5 Occam’s Razor and Data Analytics -- </subfield><subfield code="t">6 Data Analysis Tools -- </subfield><subfield code="t">7 Effect Size -- </subfield><subfield code="t">8 Analysis Process Methods -- </subfield><subfield code="t">9 Data Analytics Thinking -- </subfield><subfield code="t">10 Where’s the Data ? -- </subfield><subfield code="t">11 Data Presentation -- </subfield><subfield code="t">12 Geospatial Data Analytics -- </subfield><subfield code="t">13 Additional Data Analytics Methods -- </subfield><subfield code="t">14 Summary -- </subfield><subfield code="t">15 Case Studies -- </subfield><subfield code="t">APPENDIX. RECOMMENDED SOLUTIONS FOR CASE STUDIES -- </subfield><subfield code="t">References -- </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">Data analytics is creeping into the lexicon of our daily language. This book gives the reader a perspective as to the overall data analytics skill set, starting with a primer on statistics, and works toward the application of those methods. There are a variety of formulas and algorithms used in the data analytics process. These formulas can be plugged into whatever software application the reader uses to obtain the answer they need. There are several demonstrations of this process to provide straightforward instruction as to how to bring data analytics skills to your critical thinking. This book presents a variety of methods and techniques, as well as case studies, to enrich the knowledge of data analytics for project managers, systems engineers, and cybersecurity professionals. It separates the case studies so that each profession can practice some straightforward data analytics specific to their fields. The main purpose of this text is to refresh the statistical knowledge necessary to build models for data analytics. Along with that, this book encompasses the analytics thinking that is essential to all three professions. Features: Provides straightforward instruction on data analytics methods Includes methods, techniques, and case studies for project managers, systems engineers, and cybersecurity professionals Refreshes the statistical knowledge needed to bring data analytics into your skillset and decision-making Focuses on getting readers up to speed quickly and efficiently to be able to see the impact of data analytics and analytical thinking</subfield></datafield><datafield tag="530" ind1=" " ind2=" "><subfield code="a">Issued also in print.</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 02. Jun 2024)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Computer security.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Data mining.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Systems engineering.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">IT Management & Security.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Programming.</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="653" ind1=" " ind2=" "><subfield code="a">analytics.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">business.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">computer science.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cybersecurity.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data analysis.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data science.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">programming.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">statistics.</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">MLI AI COLLECTION</subfield><subfield code="z">9783111573533</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">Sciendo All Ebooks Trial Collection 2024</subfield><subfield code="z">9783111502496</subfield></datafield><datafield tag="776" ind1="0" ind2=" "><subfield code="c">EPUB</subfield><subfield code="z">9781683926467</subfield></datafield><datafield tag="776" ind1="0" ind2=" "><subfield code="c">print</subfield><subfield code="z">9781683926481</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1515/9781683926474</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.degruyter.com/isbn/9781683926474</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="3">Cover</subfield><subfield code="u">https://www.degruyter.com/document/cover/isbn/9781683926474/original</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">978-3-11-150249-6 Sciendo All Ebooks Trial Collection 2024</subfield><subfield code="b">2024</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">978-3-11-157353-3 MLI AI COLLECTION</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_BACKALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_CL_CHCOMSGSEN</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_DGALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">EBA_EBACKALL</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_STMALL</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV-deGruyter-alles</subfield></datafield></record></collection> |