000 04433nam a2200601 i 4500
001 9781631573323
003 BEP
005 20240726104618.0
008 180828s2018 nyu foab 001 0 eng d
020 _a9781631573323
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 0 4 _aHD
_b.B875 2018
100 1 _aSahay, Amar,
_e1
245 1 0 _aBusiness analytics :
_ba data-driven decision making approach for business
_cAmar Sahay.
250 _aFirst edition.
260 _aNew York, New York (222 East 46th Street, New York, NY 10017) :
_bBusiness Expert Press,
_c(c)2018.
300 _a1 online resource (xiv, 224 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _adata file
_2rda
490 1 _aBig data and business analytics collection,
505 0 0 _aPart I. Foundations of business analytics (BA) --
_t1. Business analytics (BA) at a glance --
_t2. Business intelligence (BI), business analytics (BA), and data analytics --
_tPart II. Descriptive analytics --
_t3. Data, data types, and descriptive statistics --
_t4. Descriptive analytics: data visualization --
_t5. Data visualization with big data --
_t6. Basic analytics tools: describing data numerically: concepts and computer analysis --
_t7. Wrap-up, cases, and notes on implementation --
_tReferences --
_tAdditional readings --
_tAbout the author --
_tIndex.
520 3 _aThis book is about Business Analytics (BA)--an emerging area in modern business decision making. The first part provides an overview of the field of Business Intelligence (BI) that looks into historical data to better understand business performance thereby improving performance, and creating new strategic opportunities for growth. Business analytics (BA) is about anticipated future trends of the key performance indicators used to automate and optimize business processes. The three major categories of business analytics--the descriptive, predictive, and prescriptive analytics along with advanced analytics tools are explained. The flow diagrams outlining the tools of each of the descriptive, predictive, and prescriptive analytics are presented. We also describe a number of terms related to business analytics. The second part of the book is about descriptive analytics and its applications. The topics discussed are--Data, Data Types and Descriptive Statistics, Data Visualization, Data Visualization with Big Data, Basic Analytics Tools: Describing Data Numerically--Concepts and Computer Applications. Finally, an overview and a case on descriptive statistics with applications and notes on implementation are presented. The concluding remarks provide information on becoming a certified analytics professional (CAP) and an overview of the second volume of this book which is a continuation of this first volume. It is about predictive analytics which is the application of predictive models to predict future trends. The second volume discusses Prerequisites for Predictive Modeling; Most Widely used Predictive Analytics Models, Linear and Non-linear regression, Forecasting Techniques, Data mining, Simulation, and Data Mining.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat reader.
588 _aTitle from PDF title page (viewed on August 28, 2018).
650 0 _aManagement
_xStatistical methods.
650 0 _aDecision making
_xStatistical methods.
650 0 _aBusiness planning.
650 0 _aStrategic planning.
653 _aanalytics
653 _abusiness analytics
653 _abusiness intelligence
653 _adata analysis
653 _adata mining
653 _adecision making
653 _adescriptive analytics
653 _amachine learning
653 _amodeling
653 _aneural networks
653 _aoptimization
653 _apredictive analytics
653 _apredictive modeling
653 _aprescriptive analytics
653 _aquantitative techniques
653 _aregression analysis
653 _asimulation
653 _astatistical analysis
653 _atime-series forecasting
856 4 1 _uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000780.html
_zClick here to access this RESOURCE ONLINE | Login using your my.ciu username & password
942 _m2018
_c1
_hHD.
_i2021-2022
_dCynthia Snell
999 _c72783
_d72783
902 _a1
_bCynthia Snell
_c1
_dCynthia Snell