COURSE SYLLABUS REQUIRED COURSE TEXTBOOK AND SUPPLEMENTARY MATERIALS:

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1 TCMG-568X-6M1 (8045) FOUNDATION OF INFORMATION ANALYTICS University f Bridgeprt Fall, 2015 Semester Mnday, August 24 December 07, :15PM 8:45PM Mandeville Hall Rm 320 Instructr: M.F.Uddin; ; muddin@bridgeprt.edu Office Hurs: by appintment. Student Hnr Cde: As a UB student, I take persnal respnsibility fr emulating the highest values and ethical nrms: my wrk is my wn and reflective f my best effrts and abilities. COURSE SYLLABUS COURSE DESCRIPTION AND APPROACH: This curse is a required curse fr the cncentratin in infrmatin analytics and will intrduce the fundatins f infrmatics. The curse fcuses n business/engineering managers, infrmatin prfessinals, business/technlgy analysts, as well as general audience wh are interested in applying data mining, statistics and basic prgramming techniques t slve real-wrld prblems. The basic principles f infrmatics that gvern cmmunicatin systems, quantitative techniques, data structure, data management, supprt and evidence based business and technlgy decisin supprt will be explred. COURSE LEARNING OBJECTIVES: The curse learning bjectives are t: 1. T equip students with a basic backgrund in databases and analytics prgramming cncepts that relate t business intelligence and business analytics. 2. T develp technical skills necessary t manage prgrammers, develpers and thers in related areas. 3. T develp critical thinking and prblem slving skills arund business intelligence and analytics prgramming and data management methdlgies. 4. T prvide an verview f business intelligence slutin architecture and the tls required t cnduct and analyze infrmatin fr decisin supprt. 5. T prvide expsure t the tls and platfrms used in business intelligence. 6. T prvide expsure t Big Data Analytics, tls and technlgies. REQUIRED COURSE TEXTBOOK AND SUPPLEMENTARY MATERIALS: 1. (fr database) Abraham Silberschatz, Henry F. Krth, and S. Sudarshan, Database Systems Cncepts, 5th Editin, ISBN- 10: (fr data analytic) Michael Miltn, Head First Data Analysis, O Reilly. ISBN-10: Nte: Yu are encuraged t ask the Reference Librarian at Wahlstrm Library fr any ther research infrmatin yu may need regarding yur prject. Nte: These are ptinal textbks. The curse wrk is Lab riented and spanned ver varius tls and areas and therefre ne bk can t be enugh. Instructr will prvide relevant handuts, references and Lab manuals (electrnic r hard cpies). Nte: Students are advised nt t buy any bk until we have met fr first lecture and we can talk abut the best apprach t gather study material and bks. The UB bk distributin system is fr yu t rder the bks n line at r at the UB Bkstre n the main campus. COURSE REQUIREMENTS: 1. Class Attendance, Participatin, Punctuality, Cheating and Plagiarism: Attendance at each class sessin is expected. Class lectures cmplement, but d nt duplicate, textbk infrmatin. Tgether the students and instructr will be creating a learning rganizatin. Students are expected t be n time fr class. A significant prtin f yur learning will accrue thrugh the cnstructive and respectful exchange f each ther s ideas (including mine!) and search fr alternative slutins. Yu must be actively engaged in class discussins t imprve yur thinking and cmmunicatin skills. Be certain that yur travel arrangements d NOT cnflict with any f yur team r individual presentatins. 2. Preparatin, Deadlines and Late Plicy: Late assignments will be penalized 20% fr each class day past the deadline. N 1

2 excuses will be accepted. Dn t wait until the last minute t print ut yur assignment. 3. UB Plicy: It is the student's respnsibility t familiarize himself r herself with and adhere t the standards set frth in the plicies n cheating and plagiarism as defined in Chapters 2 and 5 f the Key t UB r the apprpriate graduate prgram handbk. Cheating and plagiarizing means using the wrk f thers as yur wn. Cpying hmewrk, using papers frm the Internet, any talking r lking arund during exams and allwing thers t lk at yur exam papers are examples f cheating. As a UB plicy, it is expected that each student that attends ne hur f classrm instructin will require a minimum f tw hurs f ut f class student wrk each week fr apprximately fifteen weeks fr ne semester. COURSE STRUCTURE Part 1: Database Cncepts and SQL Structured Query Language, database prgramming and implementatin, Database system architecture, Entity- Relatinship data mdel and mdeling tls, the relatinal database mdel and RDBMS, Database prgramming techniques. OLAP and OLTP, SQL Server Business Intelligence. SSIS, SSRS, SSAS. Business intelligence slutin architecture and design. Data prperties, mdels, structures and ptimizatin (include flat, hierarchical, relatinal, bject-riented, netwrk, snwflake and star schemas, peratinal data stres (ODS )). Surce t target data mapping, metadata and data lineage Hands n exercises: Micrsft Transact/SQL, Oracle PL/SQL, MySQL. Cntrast with GUI ETL interfaces. Part 2: Prgramming Overview Java,.Net, C++, C#, VB.NET Language, Pythn, verviews using predefined frms and prcessing bullet prfed fr nn technical users. Intrductin t Sftware develpment languages, Overview f OOP and mdern sftware develpment technlgies, Database driven applicatin develpment, ASP.NET and web sites and web services, etc. Part 3: Industry Tls and Big Data Big Data: Types (unstructured, high vlume, i.e. scial media, healthcare, educatin, click stream, vide, etc.) Architectures and tls (Map Reduce/HADOOP, Hive, Scp, Pig, etc,) Challenges and pprtunities. Part 4: Business Analytics and Statistical Tls Data Mdeling: Classificatin, linear discriminant functins, regressin mdeling Linear/Predictive Mdeling: Crrelatin supervised segmentatin, visualizatin, prbability Applicatins Survey: SPSS, RStudi and SAS - Hands n exercises: Rstudi, SAS. PHILOSOPHY OF HOMEWORK, CASE STUDIES, RESEARCH PAPERS AND PROJECT: Hmewrk: T practice tls and strengthen the cncepts learned in class. Case studies: T investigate particular segments f real wrld industry in data analytics and decisin making. T understand hw varius situatins arise and hw are they handled in an efficient manner in real wrld. (Details will be discussed in class abut appraching case studies and what are ur gals ut f it as part f ur learning). Research Paper: T review the literature and existing published knwledge and build a wrk f ur wn t imprve research studies and knwledge. Prject: T develp a wrk f ur wn based n cncepts and tls learned in the curse. SCHEDULE FALL WEEKS (Depending upn class prgress, I may add/remve mre Tpics/H.W/Case studies/labs sessins) Nte: 1. We may visit Lab mre ften than scheduled in belw weekly breakdwn. 2. We may als lk int mre case studies than listed belw. 3. Our weekly layut may change due t hlidays, cancellatins, class perfrmance, r emergency situatin and we will adjust ur schedule accrdingly and as/if needed, we will arrange fr makeup classes if needed. 2

3 4. Quizzes are nt mentined in weekly schedule but will be given n biweekly basis, n instructr discretin. Part 1: Database Cncepts and SQL Week 1: Intrductin t Curse Structure (Syllabus as guidelines) and Data analytics cncepts in nutshell. Defining ur end gals fr this curse in light f class lectures, labs, research paper, presentatins, case studies, hmewrk, exams and final prject. Getting t knw each ther (Instructr and Students). Dates annunced fr Midterm and Finals. Week 2: Week 3: Intrductin t Structure Query Language (SQL) and its variatins. Relatinal Database Management Systems (Micrsft SQL Server, Oracle, etc) Database cncepts, data mdeling, data architecture, data structures and data ptimizatin cncepts (including flat, hierarchical, relatinal, bject-riented, netwrk, snwflake, star schema and peratinal data stres) Database develpment and administratin, data backups and restres, disaster recvery and highly availability slutins. DDL, DML. Lab 1 Wrking with Database Engines. H.W 1 (Due in tw weeks) Week 4: Week 5: Intrductin t Business intelligence. Micrsft Business intelligence (SSIS, SSRS, SSAS) Intrductin t Data Warehuse, OLAP, OLTP, ETL. Intrductin t varius BI tls frm varius vendrs in the real wrld. Case Study 1 (BI based) Lab 2 Wrking with MS BI Tls. H.W 2 Part 2: Prgramming Overview Week 6: Intrductin t Prgramming and Sftware Develpment. Intrductin t OOP, Web applicatin, Web services, XML, SOA and Clud cmputing. Varius tls and Languages (C++, Java, C#, VB.NET, Pythn) ASP.NET cncepts (Websites and Web services) utilizing databases. Case Study 2 Week 7: Lab3 Wrking with OOP Languages. Recap f Part 2 Quick Review fr Midterm 1 What t expect? Week 8: Midterm 1 Heads-up fr Part 3(Next week). 3

4 Part 3: Big Data and Industry tls Week 9: Week 10: Week 11: Intrductin t Big Data and Big Data Analytics and Prcessing Intrductin t Data retrieval and prcessing with APIs (e.g scial netwrking and LinkedIn APIs) Very Large Infrmatin Systems and Infrmatin Retrieval Intrductin t Data Mining Case Study 3 Intrductin t unstructured data real wrld examples (Scial Netwrking, text, audi and vide, healthcare data, etc) Architectures and Tls (Hadp/MapReduce, Hive, Pig, Mahut, etc) Recap f Part 3 Lab4 Wrking with Hadp, MapReduce and their varius implementatin (HDInsights, Cludera, Virtual Machine, etc) H.W 3 Part 4: Business Analytics and Statistical Tls Week 12: Week 13: Week 14: Week 15: Business Analytics (Descriptive, Predictive and Prescriptive) Data Mdeling, Regressin Mdeling, Classificatin, Linear discriminate functin Linear/Predictive Mdeling: Crrelatin, supervised segmentatin, visualizatin, prbability applicatins. Case Study 4 Tls, Rstudi, SAS (Statistical Analysis System), SPSS (Statistical Package fr Scial Services) Lab 5 Wrking Rstudi, SAS, SPSS. H.W 4 Lab 6 Quick review f all sftware s/tls learned in previus labs and refresh ur understanding and/r checking every grup/student H.Ws in regard t Lab practices. Recap f Curse Research Paper due Final Prject Dem and Presentatin based n wrk dcumented and paper writing. Preparing fr Final (Next week) Final exam Pizza COURSE GRADING: Class Participatin, Attendance & Current Events (News) 10% Case Studies Analysis and Reprts/H.W 20% Quizzes 20% Midterm 20 % Written Term Paper/Prject & Oral Summary 10% Exam (Final) 20% Ttal 100% Letter Grade Percentage A % A % 4

5 08/01/2015 B % B % B % C % C % C % D % D % D % F Belw 60% 5