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MSMESB: Experience with Adding Analytics to the Academic Program

MSMESB: Experience with Adding Analytics to the Academic Program. Kellie Keeling University of Denver. Outline. Business CORE class restructure Undergraduate Business Analytics Major/Minor MS Business Analytics. Creation of Department. Initial Departments

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MSMESB: Experience with Adding Analytics to the Academic Program

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  1. MSMESB: Experience with Adding Analytics to the Academic Program Kellie Keeling University of Denver

  2. Outline • Business CORE class restructure • Undergraduate Business Analytics Major/Minor • MS Business Analytics

  3. Creation of Department • Initial Departments • Statistics & Operations Technology • Major/Minor: Statistics • Information Technology & Electronic Commerce • Major/Minor: Business Information Technology • New: Business Information & Analytics

  4. Business CORE - Old • STAT 1300 – Statistics I (through CI) • STAT 1400 – Statistics II (through M. Reg) • STAT 2800 – Survey of Operations Mgmt - Basic mathematical modeling of business decisions, project planning, quality, supply chains, forecasting, location analysis and spreadsheet modeling • INFO 2800 – Leveraging IT for competitive advantage, Technical trends, Software trends, IS-related ethical issues (privacy, security, green IS), Collaboration systems

  5. Business CORE - New • Analytics I: Data Management and Analysis • Databases & ethics, privacy, and security issues • Descriptive & visual summaries • Survey analysis • Excel Certification • Analytics II: Business Statistics and Analysis • Traditional business statistics (Prob. to Simp. Reg.) • Word & Powerpoint Certification • Analytics III: Business Modeling and Analysis • Multiple regression • Time series forecasting • Optimization • Simulation • Communicate results, data visualization, reporting, and presentation techniques.

  6. Analytics Major - Courses AUTOMATED BUSINESS PROCESSES Programming Style and Logic, Basic Programming Structures (VBA&VB) FOUNDATIONS OF INFORMATION MANAGEMENT Database fundamentals, Data modeling and normalization, Database creation and SQL ENTERPRISE INFORMATION MANAGEMENT Enterprise database design and modeling, Advanced queries, Database triggers, functions, and procedures, Windows application development DATA WAREHOUSING AND DATA MINING Data warehouse components and construction, Extraction, transforming, and loading (ETL) and data cleansing, Predictive analytics and Descriptive analytics

  7. Analytics Major - Courses OPTIMIZATION MODELING Spreadsheet Model Design, Optimization and Linear Programming, Real World Problem Solving, Technical Writing and Project Documentation BUSINESS FORECASTING AND VISUALIZATION Descriptive analytics: Data visualization, Dashboards/scorecards, Time Series Analysis, Regression and Survival Analysis ADVANCED ANALYTICS Text Mining, Geospatial Data Analytics, Financial and Risk Analytics, Marketing and Web Analytics PROJECT MANAGEMENT AND SIMULATION Plan projects with flexibility in scope, timeframe, and resources, Critical Chain Approach, Probability distributions versus point estimates, Monte Carlo Simulation Modeling

  8. Analytics Major - Courses CAPSTONE/SENIOR PROJECT Partner Company project Written and oral presentation PICK TWO ELECTIVES Health Informatics Applied Probability: Gambling Utility Analytics Statistical Computing Computer Simulation-Discrete Event

  9. Undergraduate Minors • Minors • Business Information Technology • Analytics  will really be pushing to other majors • Statistics

  10. MS Business Analytics THE ESSENCE OF ENTERPRISE Leadership development, team building, around a global-world view examining the organization and personnel to build success. ETHICS FOR THE 21ST CENTURY PROFESSIONAL Ongoing reflection and dialog about responsibilities and leaders and managers. BUSINESS INTELLIGENCE Intro to data, data warehousing, data marts, advanced analytic techniques, decision making and organizational dynamics and leadership BUSINESS DATABASES Database design, SQL and SQL Server

  11. MS Business Analytics BUSINESS STATISTICS Statistical inference, regression, ANOVA, categorical data, goodness of fit CAPSTONE PLANNING “Consulting” overview, see capstone proposals and pick project DATA WAREHOUSING Requirements, realities, and architecture; building and populating data bases, developing BI applications, Powerpivot, SW/BI system, deploy and manage PROJECT MANAGEMENT Budgeting, uncertainty, PERT/CPM, risk; simulation using Crystal Ball, Optimization (Excel Solver), and Simulation (in Excel)

  12. MS Business Analytics PREDICTIVE ANALYTICSMultiple regression/GLM, Logistic regression, CART, kNN classification, time series, text mining BUSINESS METRICSANOVA, MANOVA, ANCOVA, cluster analysis, association rules, PCA/FA, survey analysis, SEM, HLM, dashboards/scorecards, data visualization DECISION PROCESSESDecisions (framing, trees, matrix, payback), simulation & sensitivyt analysis, dashboards part 2 CAPSTONE ELECTIVES - 3 courses

  13. Thank you Kellie Keeling Kellie.Keeling@du.edu

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