LEADER 00000cam a2200709Mi 4500 
001    ocn900878630 
003    OCoLC 
005    20160805111103.8 
006    m    eo  d         
008    150126s2015    nyu    foab   001 0 eng d 
019    899942099|a904036452 
020    9781631571213|qe-book 
020    1631571214 
020    |z9781631571206|qpaperback 
035    (OCoLC)900878630|z(OCoLC)899942099|z(OCoLC)904036452 
040    NYBEP|beng|erda|cNYBEP|dOCLCO|dE7B|dOCLCF|dEBLCP|dIDEBK
       |dWEA|dYDXCP|dN$T|dCUS|dOCLCO 
049    RIDW 
050  4 HF54.5|b.M243 2015 
072  7 BUS|x082000|2bisacsh 
072  7 BUS|x041000|2bisacsh 
072  7 BUS|x042000|2bisacsh 
072  7 BUS|x085000|2bisacsh 
082 04 658.4038|223 
090    HF54.5|b.M243 2015 
100 1  Maheshwari, Anil,|d1949-|0https://id.loc.gov/authorities/
       names/n89181477|eauthor. 
245 10 Business intelligence and data mining /|cAnil K. 
       Maheshwari. 
250    First edition. 
264  1 New York, New York (222 East 46th Street, New York, NY 
       10017) :|bBusiness Expert Press,|c2015. 
300    1 online resource (1 PDF (xiv, 162 pages)). 
336    text|2rdacontent 
337    computer|2rdamedia 
338    online resource|2rdacarrier 
490 1  Big data and business analytics collection,|x2333-6757 
504    Includes bibliographical references (pages 157-158) and 
       index. 
505 0  1. Wholeness of business intelligence and data mining -- 
       2. Business intelligence concepts and applications -- 3. 
       Data warehousing -- 4. Data mining -- 5. Decision trees --
       6. Regression -- 7. Artificial neural networks -- 8. 
       Cluster analysis -- 9. Association rule mining -- 10. Text
       mining -- 11. Web mining -- 12. Big data -- 13. Data 
       modeling primer -- Additional resources -- Index. 
520 3  Business is the act of doing something productive to serve
       someone's needs, and thus earn a living, and make the 
       world a better place. Business activities are recorded on 
       paper or using electronic media, and then these records 
       become data. There is more data from customers' responses 
       and on the industry as a whole. All this data can be 
       analyzed and mined using special tools and techniques to 
       generate patterns and intelligence, which reflect how the 
       business is functioning. These ideas can then be fed back 
       into the business so that it can evolve to become more 
       effective and efficient in serving customer needs. And the
       cycle continues on. Business intelligence includes tools 
       and techniques for data gathering, analysis, and 
       visualization for helping with executive decision making 
       in any industry. Data mining includes statistical and 
       machine-learning techniques to build decision-making 
       models from raw data. Data mining techniques covered in 
       this book include decision trees, regression, artificial 
       neural networks, cluster analysis, and many more. Text 
       mining, web mining, and big data are also covered in an 
       easy way. A primer on data modeling is included for those 
       uninitiated in this topic. 
588    Title from PDF title page (viewed on January 26, 2015). 
590    eBooks on EBSCOhost|bEBSCO eBook Subscription Academic 
       Collection - North America 
650  0 Business information services.|0https://id.loc.gov/
       authorities/subjects/sh85018267 
650  0 Data mining.|0https://id.loc.gov/authorities/subjects/
       sh97002073 
650  0 Business intelligence.|0https://id.loc.gov/authorities/
       subjects/sh85018300 
650  7 Business information services.|2fast|0https://
       id.worldcat.org/fast/842715 
650  7 Data mining.|2fast|0https://id.worldcat.org/fast/887946 
650  7 Business intelligence.|2fast|0https://id.worldcat.org/fast
       /842723 
653    Data Analytics 
653    Data Mining 
653    Business Intelligence 
653    Decision Trees 
653    Regression 
653    Neural Networks 
653    Cluster analysis 
653    Association rules 
655  4 Electronic books. 
776 08 |iPrint version:|z9781631571206 
830  0 Big data and business analytics.|0https://id.loc.gov/
       authorities/names/no2019037574|x2333-6757 
856 40 |uhttps://rider.idm.oclc.org/login?url=http://
       search.ebscohost.com/login.aspx?direct=true&scope=site&
       db=nlebk&AN=935070|zOnline eBook. Access restricted to 
       current Rider University students, faculty, and staff. 
856 42 |3Instructions for reading/downloading this eBook|uhttp://
       guides.rider.edu/ebooks/ebsco 
901    MARCIVE 20231220 
948    |d20161013|cEBSCO|tebscoebooksacademic new |lridw 
994    92|bRID