1. Experiences with Introducing or Expanding Analytics Offerings Data, Analytics, and Statistics Instruction DSI 2016 Austin, TX
Kellie Keeling
Department of Business Information & Analytics
University of Denver (DU)
November 20, 2016

2. Outline
Experiences with first Graduating Class for Business Analytics Major/Minor
Curriculum
Placement
MS Business Analytics
Continuing Discussions

3. Our Department Business Information & Analytics
Combination of Former Departments
Statistics & Operations Technology
Information Technology & Electronic Commerce
Quarter System (4-hour 10-week classes)
Faculty (Statistics, Management Science, IS, Industrial Engineering, Applied Math, Educational Technology)
Hiring 1 More
Teaching/Practice
Tenure Track
2 Full Prof of Practice
1 Full Prof
1 Associate Teaching Prof
3 Associate Profs
3 Assistant Teaching Prof
5 Assistant Profs
CLICK - Hiring

4. Business CORE Analytics I: Data Management and Analysis
Ethics, privacy, and security issues
Descriptive & visual summaries & Excel optimization
Gathering data, "database" terminology, pivot summaries
Excel Certification
Analytics II: Business Statistics and Analysis
Traditional business statistics (Probability, Distributions, Hypothesis Testing, ANOVA, Goodness of Fit/Independence)
Communicating results including basic data visualization (Posters)
Word & Powerpoint Certification
Analytics III: Business Modeling and Analysis
Regression
Time series forecasting
Simulation
Intro to Data Mining (Trying Cluster, Logistic with XL Miner/JMP)
Communicating results – 4 projects
Analytics I
Principal Content Elements (i.e., modules):
Data – Sources and Value
Introduction to Analytics and Business Intelligence
Analytics Systems and Software
Emerging Trends in Data Analysis and Analytics
Prerequisites: None
Learning Outcomes:
Develop the ability to obtain, generate, and manage a database with the purpose of supporting a business decision.
Apply visual and descriptive data analysis techniques to the decision-making process.
Understand how businesses use traditional and emerging technologies to manage data, including considering the issues of ethics, security, and privacy.
Develop the presentation techniques that allow data analysis to be transformed into business intelligence for decision makers.
Begin to develop the critical thinking and problem solving skills necessary to produce a business decision or recommendation form a data set.
Analytics II
Probability
Sampling
Hypothesis Testing
Multiple Regression
Prerequisites: BIA 1010, MATC 1200 or MATH 1951, MS Excel certification
Understand the tenets of probability and statistics as they apply to business decisions.
Apply sampling and statistical inference to business applications such as data analysis, quality control, risk analysis, and confidence in decision making.
Employ statistically-supportable modeling techniques that use data to predict and explain interactions and outcomes that affect business decisions, with emphasis on multiple regression.
Communicate the results of modeling and analysis to a decision maker in a way that enhances the decision-making process.
Conitnue to develop the critical thinking and problem solving skills necessary to produce a business decision from a data set.
Analytics III
Time series forecasting
Optimization
Simulation
Project management
Prerequisites: BIA 1020, MS Word and PowerPoint certification, DCB2 checkpoint
Construct appropriate quantitative models for a variety of business problems using a spreadsheet environment.
Apply quantitative techniques and spreadsheet tools to derive a set of conclusions from these models.
Evaluate conclusions and perform what-if analysis to gain insights about the business problem.
Analyze and interpret conclusions and insights, and communicate this intelligence to decision makers using appropriate data visualization, reporting, and presentation techniques.
Continue to develop the critical thinking and problem solving skills necessary to produce a business decision or recommendation from a data set.

5. MINOR
+ 2 Electives
Click for Minor

6. Analytics Major – 11 4-hr 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 (Access)
ENTERPRISE INFORMATION MANAGEMENT
Enterprise database design and modeling, Advanced queries, Database triggers, functions, and procedures, Windows application development (SQL SERVER)
DATA WAREHOUSING AND BUSINESS INTELLIGENCE
Data warehouse components and construction, Extraction, transforming, and loading (ETL) and data cleansing, Decision Trees and Association Rules
Skip through these 2– just for completeness

7. Analytics Major - Courses
OPTIMIZATION MODELING
Spreadsheet Model Design, Optimization and Linear Programming, Real World Problem Solving
DATA MINING AND VISUALIZATION
Descriptive analytics: Data visualization, Dashboards/scorecards, Time Series Analysis, Regression and Survival Analysis
COMPLEX DATA ANALYTICS
Text Mining and Social Network Analysis
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 (Excel)
Directions here:
Red Color Value: R=150, G=35, B=47

8. Analytics Major - Courses
CAPSTONE/SENIOR PROJECT
Partner Company project
Spring 16: RTD: Public Bus System
Spring 17: RideFare (new Uber/Lyft competitor)
Began with Individual work – then group work
Other Focus:
Communication/Visualization/Presentation
Reproducible Research/Documenting/Journaling
Talk about this

9. Analytics Major - Courses
PICK TWO ELECTIVES
Statistical Computing (SAS/R Scripting)
Database Driven Websites
Nonparametric Statistics
Internship
Python for Data Analytics (??? Graduate Class)

11. MS Business Analytics
PROGRAMMING (Python) Basic logic and design, data management and statistical analysis DECISION PROCESSES Decisions (framing, trees, matrix, payback), simulation & sensitivity analysis, dashboards part 2 INTRODUCTION TO BUSINESS ANALYTICS Intro to data, data warehousing, data marts, advanced analytic techniques, decision making and organizational dynamics and leadership (EDR, Tableau)
Skip through these 4

12. MS Business Analytics
BUSINESS STATISTICS Statistical inference, regression, ANOVA, categorical data, goodness of fit (Excel) PREDICTIVE ANALYTICS Multiple regression/GLM, Logistic regression, CART, kNN classification, time series, text mining (SPSS Modeler, Python) DATA MINING AND VISUALIZATION ANOVA, MANOVA, ANCOVA, cluster analysis, association rules, PCA/FA, survey analysis, SEM, HLM, dashboards/scorecards, data visualization (JMP, Tableau, HLM)

13. MS Business Analytics
OPTIMIZATION Optimization (Excel Solver and Lingo)
PROJECT MANAGEMENT
Budgeting, uncertainty, PERT/CPM, risk; simulation using Crystal Ball, and Simulation (in Excel)
ELECTIVES - 2 courses (SAS/R Scripting, 1 Other)

14. MS Business Analytics
BUSINESS DATABASES Database design, SQL (SQL Server) DATA WAREHOUSING Requirements, realities, and architecture; building and populating data bases, developing BI applications, Powerpivot, SW/BI system, deploy and manage CAPSTONE PLANNING and CAPSTONE “Consulting” overview, see capstone proposals and pick project, quarter-long project

15. Enrollments MS Business Analytics
2013 7, , , ,
Undergraduates
Spring 14 Graduates
6 statistics majors / 1 information technology major
4 statistics minors
Spring 15 Graduates
16 statistics / 1 information technology major
9 statistics minors
Spring 16 Graduate Estimates
4 statistics/information technology majors
21 BA majors
20 BA/statistics minors
Spring 17 Graduate Estimates
32 BA Majors + 1 STAT major
Summer 13--7
Winter 14--7
Summer 14—9
Winter
Summer 15—14
Winter
Summer
2016 – 31
FALL 2016 Numbers
BA Majors: 25 Fresh, 30 Soph, 34 Junior, 32 Seniors (+1 STAT Major)
BA Minors: STAT 12, BANA 39
MSBA
Fall: 6?
Winter: 17?
Spring: 6?
Summer: 20?
Should be around 50.  Maybe closer to 45.

16. Enrollments Fresh: 25 Soph: 30 Junior: 34 Minors: STAT: 12 BANA: 39
Click – box future

17. Enrollments
Winter 2017 Undergraduates – increasing required first 2 courses and required 2 courses for minor from 2 to 3 sections
INFO 3100 VBA/VB – 3 sections (78)
INFO 3200 Database – 3 sections (65)

18. Enrollments

22. Job Placement (21 2016 Grads) 2 No Jobs 1 Not Looking 1 unknown
Willis Towers Watson: Actuarial Analyst (Health and Benefits)
KPMG: Associate in Tax Technology Transformation
Northern Trust Bank: Financial Analysis Rotations
Goldman Sachs: Public Sector/Infrastructure Investment Banking Analyst
Amazon: Business Analyst
2 Motivity Solutions: Business Analyst
DataLab: Business Analyst
2 Arrow Electronics: Data Analyst & Big Data Analyst
Turbine Labs: Principal
EKS&H: Staff Consultant
EKS&H: Data Integration Consultant
Conatngo Technologies: IT Analyst
Boeing: IT Career Rotations
Dish Network: Marketing Analyst
Comedy works/Grad School: Business Affair intern
2 No Jobs
1 Not Looking
1 unknown

23. Continuing Discussions
BA Undergraduate Major
Student Suggestions:
Add coding: JAVA/C/C# and statistical coding: R/Python/SAS, more elective choices
Project Management/Sim: issues with course – add simulation
Data: Moore data warehousing, non-relational databases
Required reading: Signal and the Noise
watch for overlap of material

24. Continuing Discussions
BA Undergraduate Major
Professor Suggestions:
Disturbing mind map of program
More translation to non-statistical stakeholders
Fix Project Management, Data Warehousing/BI (was DW/Data Mining) and Data Mining/Viz (was Forecasting/Viz)
Challenging, Critical Thinking & Problem Solving
List of positives:
Helpful enthusiastic professors overall
Good start with VBA, like database sequence, SQL, VB, data visualization
Next Page Mind Maps

25. Continuing Discussions
Mind Maps for Undergraduate Courses:
Some put 3 CORE outside of INFO courses
None integrated business classes
A couple grouped Business:
'Financial/Accounting', 'Pretty Good', 'Totally worthless classes' (MGMT,MKTG!!!)
Groupings:
Coding, Modeling, Visualization, Other (Project Management!)
Data Storage/Query, Data Interpretation, Data Visualization
Point here: We should create these groupings for the students

26. Continuing Discussions
MS in Business Analytics:
Removed 2 required Business Courses for all MS programs (Essence of Enterprise/Ethic)
Need to add 'business' back
Require R (or SAS/R)????
Combine Business Processes & Project Management into one class???
Add more electives if want to stay in department

27. Thank you
Kellie Keeling
University of Denver