Data visualization. / Volume 1, : Recent trends and applications using conventional and big data / / Amar Sahay.
Data visualization involves graphical and visual tools used in data analysis and decision making. The emphasis in this book is on recent trends and applications of visualization tools using conventional and big data. These tools are widely used in data visualization and quality improvement to analyz...
Saved in:
Superior document: | Quantitative approaches to decision making collection, |
---|---|
VerfasserIn: | |
Place / Publishing House: | New York, New York (222 East 46th Street, New York, NY 10017) : : Business Expert Press,, 2017. |
Year of Publication: | 2017 |
Edition: | First edition. |
Language: | English |
Series: | Quantitative approaches to decision making collection.
|
Online Access: | |
Physical Description: | 1 online resource (xii, 180 pages) |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
5004789484 |
---|---|
ctrlnum |
(MiAaPQ)5004789484 (Au-PeEL)EBL4789484 (CaPaEBR)ebr11332244 (CaONFJC)MIL988629 (OCoLC)970631358 |
collection |
bib_alma |
record_format |
marc |
spelling |
Sahay, Amar, author. Data visualization. Volume 1, Recent trends and applications using conventional and big data / Amar Sahay. Recent trends and applications using conventional and big data. First edition. New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, 2017. 1 online resource (xii, 180 pages) text rdacontent computer rdamedia online resource rdacarrier Quantitative approaches to decision making collection, 2163-9582 Includes bibliographical references (pages 175-176) and index. Graphical and visual tools for improving business process, product, and service quality -- 1. Overview and importance of visual representation -- 2. Data and data analysis concepts -- 3. Visual representation of data -- 4. Exploring relationships between two or more variables graphically -- 5. Data visualization with big data -- 6. Computer applications and implementation -- Appendix A. Charts and graphs using EXCEL -- Appendix B. Pivot table applications in descriptive statistics and data analysis -- Appendix C. Charts and graphs using MINITAB 17 -- Bibliography -- Index. Access restricted to authorized users and institutions. Data visualization involves graphical and visual tools used in data analysis and decision making. The emphasis in this book is on recent trends and applications of visualization tools using conventional and big data. These tools are widely used in data visualization and quality improvement to analyze, enhance, and improve the quality of products and services. Data visualization is an easy way to obtain a first look at the data visually. The book provides a collection of visual and graphical tools widely used to gain an insight into the data before applying more complex analysis. The focus is on the key application areas of these tools including business process improvement, business data analysis, health care, finance, manufacturing, engineering, process improvement, and Lean Six Sigma. The key areas of application include data and data analysis concepts, recent trends in data visualization and "Big Data," widely used charts and graphs and their applications, analysis of the relationships between two or more variables graphically using scatterplots, bubble graphs, matrix plots, etc., data visualization with big data, computer applications and implementation of widely used graphical and visual tools, and computer instructions to create the graphics presented along with the data files. Title from PDF title page (viewed on February 1, 2017). Electronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. Information visualization. visual representation quality tools software applications charts and graphs data data analysis data visualization information visualization business intelligence business analytics big data big data software Electronic books. Print version: 9781631573354 ProQuest (Firm) Quantitative approaches to decision making collection. 2163-9582 https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=4789484 Click to View |
language |
English |
format |
eBook |
author |
Sahay, Amar, |
spellingShingle |
Sahay, Amar, Data visualization. Quantitative approaches to decision making collection, Graphical and visual tools for improving business process, product, and service quality -- 1. Overview and importance of visual representation -- 2. Data and data analysis concepts -- 3. Visual representation of data -- 4. Exploring relationships between two or more variables graphically -- 5. Data visualization with big data -- 6. Computer applications and implementation -- Appendix A. Charts and graphs using EXCEL -- Appendix B. Pivot table applications in descriptive statistics and data analysis -- Appendix C. Charts and graphs using MINITAB 17 -- Bibliography -- Index. |
author_facet |
Sahay, Amar, |
author_variant |
a s as |
author_role |
VerfasserIn |
author_sort |
Sahay, Amar, |
title |
Data visualization. |
title_full |
Data visualization. Volume 1, Recent trends and applications using conventional and big data / Amar Sahay. |
title_fullStr |
Data visualization. Volume 1, Recent trends and applications using conventional and big data / Amar Sahay. |
title_full_unstemmed |
Data visualization. Volume 1, Recent trends and applications using conventional and big data / Amar Sahay. |
title_auth |
Data visualization. |
title_alt |
Recent trends and applications using conventional and big data. |
title_new |
Data visualization. |
title_sort |
data visualization. recent trends and applications using conventional and big data / |
series |
Quantitative approaches to decision making collection, |
series2 |
Quantitative approaches to decision making collection, |
publisher |
Business Expert Press, |
publishDate |
2017 |
physical |
1 online resource (xii, 180 pages) |
edition |
First edition. |
contents |
Graphical and visual tools for improving business process, product, and service quality -- 1. Overview and importance of visual representation -- 2. Data and data analysis concepts -- 3. Visual representation of data -- 4. Exploring relationships between two or more variables graphically -- 5. Data visualization with big data -- 6. Computer applications and implementation -- Appendix A. Charts and graphs using EXCEL -- Appendix B. Pivot table applications in descriptive statistics and data analysis -- Appendix C. Charts and graphs using MINITAB 17 -- Bibliography -- Index. |
isbn |
9781631573361 9781631573354 |
issn |
2163-9582 |
callnumber-first |
Q - Science |
callnumber-subject |
QA - Mathematics |
callnumber-label |
QA76 |
callnumber-sort |
QA 276.9 I52 S253 42017 |
genre |
Electronic books. |
genre_facet |
Electronic books. |
url |
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=4789484 |
illustrated |
Not Illustrated |
dewey-hundreds |
000 - Computer science, information & general works |
dewey-tens |
000 - Computer science, knowledge & systems |
dewey-ones |
001 - Knowledge |
dewey-full |
001.4226 |
dewey-sort |
11.4226 |
dewey-raw |
001.4226 |
dewey-search |
001.4226 |
oclc_num |
970631358 |
work_keys_str_mv |
AT sahayamar datavisualizationvolume1 AT sahayamar recenttrendsandapplicationsusingconventionalandbigdata |
status_str |
n |
ids_txt_mv |
(MiAaPQ)5004789484 (Au-PeEL)EBL4789484 (CaPaEBR)ebr11332244 (CaONFJC)MIL988629 (OCoLC)970631358 |
title_part_txt |
Recent trends and applications using conventional and big data / |
hierarchy_parent_title |
Quantitative approaches to decision making collection, |
is_hierarchy_title |
Data visualization. |
container_title |
Quantitative approaches to decision making collection, |
_version_ |
1792330941210820608 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04264nam a2200625 i 4500</leader><controlfield tag="001">5004789484</controlfield><controlfield tag="003">MiAaPQ</controlfield><controlfield tag="005">20200520144314.0</controlfield><controlfield tag="006">m o d | </controlfield><controlfield tag="007">cr cnu||||||||</controlfield><controlfield tag="008">170201s2017 nyu foab 001 0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781631573354</subfield><subfield code="q">paperback</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781631573361</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(MiAaPQ)5004789484</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(Au-PeEL)EBL4789484</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaPaEBR)ebr11332244</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaONFJC)MIL988629</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)970631358</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">MiAaPQ</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">MiAaPQ</subfield><subfield code="d">MiAaPQ</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA76.9.I52</subfield><subfield code="b">S253 2017</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">001.4226</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sahay, Amar,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Data visualization.</subfield><subfield code="n">Volume 1,</subfield><subfield code="p">Recent trends and applications using conventional and big data /</subfield><subfield code="c">Amar Sahay.</subfield></datafield><datafield tag="246" ind1="3" ind2="0"><subfield code="a">Recent trends and applications using conventional and big data.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">First edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, New York (222 East 46th Street, New York, NY 10017) :</subfield><subfield code="b">Business Expert Press,</subfield><subfield code="c">2017.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (xii, 180 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Quantitative approaches to decision making collection,</subfield><subfield code="x">2163-9582</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references (pages 175-176) and index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Graphical and visual tools for improving business process, product, and service quality -- 1. Overview and importance of visual representation -- 2. Data and data analysis concepts -- 3. Visual representation of data -- 4. Exploring relationships between two or more variables graphically -- 5. Data visualization with big data -- 6. Computer applications and implementation -- Appendix A. Charts and graphs using EXCEL -- Appendix B. Pivot table applications in descriptive statistics and data analysis -- Appendix C. Charts and graphs using MINITAB 17 -- Bibliography -- Index.</subfield></datafield><datafield tag="506" ind1="1" ind2=" "><subfield code="a">Access restricted to authorized users and institutions.</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Data visualization involves graphical and visual tools used in data analysis and decision making. The emphasis in this book is on recent trends and applications of visualization tools using conventional and big data. These tools are widely used in data visualization and quality improvement to analyze, enhance, and improve the quality of products and services. Data visualization is an easy way to obtain a first look at the data visually. The book provides a collection of visual and graphical tools widely used to gain an insight into the data before applying more complex analysis. The focus is on the key application areas of these tools including business process improvement, business data analysis, health care, finance, manufacturing, engineering, process improvement, and Lean Six Sigma. The key areas of application include data and data analysis concepts, recent trends in data visualization and "Big Data," widely used charts and graphs and their applications, analysis of the relationships between two or more variables graphically using scatterplots, bubble graphs, matrix plots, etc., data visualization with big data, computer applications and implementation of widely used graphical and visual tools, and computer instructions to create the graphics presented along with the data files.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Title from PDF title page (viewed on February 1, 2017).</subfield></datafield><datafield tag="590" ind1=" " ind2=" "><subfield code="a">Electronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Information visualization.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">visual representation</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">quality tools</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">software applications</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">charts and graphs</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data analysis</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">data visualization</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">information visualization</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">business intelligence</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">business analytics</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">big data</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">big data software</subfield></datafield><datafield tag="655" ind1=" " ind2="4"><subfield code="a">Electronic books.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="z">9781631573354</subfield></datafield><datafield tag="797" ind1="2" ind2=" "><subfield code="a">ProQuest (Firm)</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Quantitative approaches to decision making collection.</subfield><subfield code="x">2163-9582</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=4789484</subfield><subfield code="z">Click to View</subfield></datafield></record></collection> |