BUSINESS ANALYTICSSub Code:010020Course Credits:03Course SnapshotLarge volumes of data have been collected by organizations using enterprise applications likeERP, SCM and CRM Most of the data is being analyzed for operational purposes !ery fe" areusing the information for Strategic #ecision Making $usiness %ntelligence &or $%' ob(ective is toderive information from large volume of data and apply this for strategic decision making to gainacompetitiveedge )hecourse"ill e*posethestudentstotoolsandtechni+uesusedin$%applications %t "ill also help the students to appear for S,S Enterprise Certification Programconducted globally Obe!ti"es -pon completion of the course it is e*pected that students "ill be able to understand. Relevance of $usiness %ntelligence in %ndustry Role of $usiness %ntelligence in decision making )echnology to implement $usiness %ntelligence %mportance of #ata /arehouse to implement $usiness %ntelligence #ata Mining and #ata !isualization 0uture #irectionsLearnin# $oa%sa& $enera% Learnin# $oa%sEffective Communication'L 1(%nterpersonal Skills 1 )eam"ork'L 2(Social Responsibility'L 3( Problem Solving 1 #ecision Making'L )( 2uantitative ,nalytical Skills&L *(3lobal ,"areness'L +( b& Spe!i,i! Learnin# $oa%s-no.%ed#e: -nderstand the process for linking data to critical business outcomes '-1( #eployment of $usiness analytics to arrive at effective and efficient decisions& '-2( )o recognize strengths and identify any needs for improvement in various business functions'-3(S/i%%s: 4o" to calculate R5% on various investments 'S1( #ata !isualization 'S2(Attitude: E*plorative Mind set 'A1( 5b(ectivity'A2( 4olistic vie" 'A3(Course 0e%i"er1C%assroo2 En#a#e2ent 'CE(3 contact hours in the class&lectures, case discussions, presentations, e*ercises, internal assessment'30 4ours0ire!ted Learnin# '0L(6 done under faculty supervision&lab6"ork, research, field"ork, pro(ect "ork'30 4oursTota% No& o, 4ours 'CE50L( 6+0E"a%uation Co2ponentsInterna% Assess2ent+07 Cases. )erm 5ral and /ritten Presentation Case #iscussions Participation. %ncluding responses to cases7topics Pro(ect Mid6)erm E*am6 8 hours 9:;9,L:=6>Planning a #ata "arehouse #efining $usiness Re+uirements, Role of Metadata)e*t $ook1 reference material Case presentation, analysis 1 discussion3roup Case #iscussion Presentation 1 3roup Case,nalysis PresentationsH96H=S96S8,96,=L>,L:>6:Star Schema and Multi #imension #atabase,5L,P )e*t $ook1 reference materialPP) 1 discussion3roup #iscussion H96H=S96S8,96,=L>,L::699Lab Sessions on $uilding a #ata "arehouse )e*t $ook1 reference materialLab SessionsLab Practical and handon e*perience on S7/H96H=S96S8,96,=L>,L:98%ntroduction to #ata Mining )e*t $ook1 reference materialCase presentation, analysis 1 discussion3roup Case #iscussion Presentation 1 3roup Case ,nalysis PresentationsH96H=S96S8,96,=L>,L:9=#ata Mining Methodology)e*t $ook1 reference materialCase presentation, analysis 1 discussion3roup Case #iscussion Presentation H96H=S96S8,96,=L>,L:9>#ata )ransformation, identifying variable of importance, #ata Sampling, #ata E*ploration )e*t $ook1 reference material Case presentation, analysis 1 discussion3roup Case #iscussion Presentation H96H=S96S8,96,=L>,L:9:#ecision )rees Logistic Regression #isc ,nalysis)e*t $ook1 reference material Case presentation, analysis 1 discussion3roup #iscussion, Lab practicalH96H=S96S8,96,=L>,L:9A68,L:Tota% 4ours: 300e%i"erab%e,ro2 students9 Case 8< Presentation8 $usiness ,nalytics lab 8 Presentation= ,ssignment69 8 ,ssignment> ,ssignment68 8 ,ssignment: Pro(ect > Short reportTota% 4ours3 30