LEADER 00000nam a2200925   4500 
001    BEP9781631574801 
003    BEP 
005    20190417111955.0 
006    m    eo  d         
007    cr cn |||m|||a 
008    190417s2020    nyua   fob    001 0 eng d 
020    9781631574801|qe-book 
020    |z9781631574795|qprint 
035    (OCoLC)1128049885 
035    (CaBNVSL)slc00000095 
040    CaBNVSL|beng|erda|cCaBNVSL|dCaBNVSL 
049    RIDW 
050  4 HD30.28|b.S34 2020eb 
082 04 658.4012|223 
090    HD30.28|b.S34 2020eb 
100 1  Sahay, Amar,|0https://id.loc.gov/authorities/names/
       no2019068585|eauthor. 
245 10 Business analytics :|ba data-driven decision-making 
       approach for business.|nVolume II,|pPredictive analytics /
       |cAmar Sahay, PhD. 
246 30 Predictive analytics 
250    First edition. 
264  1 New York, New York (222 East 46th Street, New York, NY 
       10017) :|bBusiness Expert Press,|c2020. 
300    1 online resource (xviii, 384 pages) :|billustrations 
       (some color). 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
340    |gpolychrome|2rdacc 
347    text file|2rdaft 
490 1  Big data, business analytics, and smart technology 
       collection,|x2333-6757 
504    Includes bibliographical references (pages 373-375) and 
       index. 
505 0  Chapter 1. Business analytics at a glance -- Chapter 2. 
       Business analytics and business intelligence -- Chapter 3.
       Analytics, business analytics, data analytics, and how 
       they fit into the broad umbrella of business intelligence 
       -- Chapter 4. Descriptive analytics--overview, 
       applications, and a case -- Chapter 5. Descriptive versus 
       predictive analytics -- Chapter 6. Key predictive 
       analytics models (predicting future business outcomes 
       using analytic models) -- Chapter 7. Regression analysis 
       and modeling -- Chapter 8. Time series analysis and 
       forecasting -- Chapter 9. Data mining: tools and 
       applications in predictive analytics -- Chapter 10. Wrap-
       up, overview, notes on implementation, and current state 
       of business analytics. 
506    Access restricted to authorized users and institutions. 
520 3  This business analytics (BA) text discusses the models 
       based on fact-based data to measure past business 
       performance to guide an organization in visualizing and 
       predicting future business performance and outcomes. It 
       provides a comprehensive overview of analytics in general 
       with an emphasis on predictive analytics. Given the 
       booming interest in analytics and data science, this book 
       is timely and informative. It brings many terms, tools, 
       and methods of analytics together. The first three 
       chapters provide an introduction to BA, importance of 
       analytics, types of BA--descriptive, predictive, and 
       prescriptive--along with the tools and models. Business 
       intelligence (BI) and a case on descriptive analytics are 
       discussed. Additionally, the book discusses the most 
       widely used predictive models, including regression 
       analysis, forecasting, data mining, and an introduction to
       recent applications of predictive analytics--machine 
       learning, neural networks, and artificial intelligence. 
       The concluding chapter discusses the current state, job 
       outlook, and certifications in analytics. 
530    Also available in print. 
538    Mode of access: World Wide Web. 
538    System requirements: Adobe Acrobat reader. 
561    Purchased with the Phippen Library Fund. 
588    Description based on PDF viewed 11/14/2019. 
650  0 Management|xStatistical methods.|0https://id.loc.gov/
       authorities/subjects/sh2008107306 
650  0 Decision making|xStatistical methods.|0https://id.loc.gov/
       authorities/subjects/sh2009123012 
650  0 Business planning.|0https://id.loc.gov/authorities/
       subjects/sh85032906 
650  0 Strategic planning.|0https://id.loc.gov/authorities/
       subjects/sh85128511 
650  0 Business intelligence.|0https://id.loc.gov/authorities/
       subjects/sh85018300 
650  7 Management|xStatistical methods.|2fast|0https://
       id.worldcat.org/fast/1007232 
650  7 Decision making|xStatistical methods.|2fast|0https://
       id.worldcat.org/fast/889068 
650  7 Business planning.|2fast|0https://id.worldcat.org/fast/
       842819 
650  7 Strategic planning.|2fast|0https://id.worldcat.org/fast/
       1134371 
650  7 Business intelligence.|2fast|0https://id.worldcat.org/fast
       /842723 
653    Analytics. 
653    Business analytics. 
653    Business intelligence. 
653    Data analysis. 
653    Decision making. 
653    Descriptive analytics. 
653    Predictive analytics. 
653    Prescriptive analytics. 
653    Statistical analysis. 
653    Quantitative techniques. 
653    Data mining. 
653    Predictive modeling. 
653    Regression analysis. 
653    Modeling. 
653    Time series forecasting. 
653    Optimization. 
653    Simulation. 
653    Maching learning. 
653    Neural networks. 
653    Artificial intelligence. 
655  0 Electronic books. 
776 08 |iPrint version:|z9781631574795 
830  0 Big data, business analytics, and smart technology 
       collection.|x2333-6757 
856 40 |uhttps://rider.idm.oclc.org/login?url=https://
       portal.igpublish.com/iglibrary/search/BEPB0000918.html
       |zOnline ebook via BEP. Access restricted to current Rider
       University students, faculty, and staff. 
901    MARCIVE 20231220 
948    |d20220401|tBEP reload 277|lridw 
948    |d20210525|cBEP|tBEP2021initial 229|lridw