LINDNER College of Business
UC Center for Business Analytics
Master of Science degrees and graduate
certificates provide pathways to career success
Master of Science in
Business Analytics
Master of Science in
Information Systems
The Lindner Master of Science in
Business Analytics program seeks
students with quantitative and/or
technical backgrounds (mathematics,
engineering, statistics, science,
economics etc.) who are interested in
pursuing careers in the fast-growing
fields of business analytics and data
science. No work experience is needed
to enter the program which can be
completed in less than a year. Flexible
part-time options are offered for
working professionals.
The Lindner Master of Science in
Information Systems accepts students
from any undergraduate major
who want to gain a business and
technology foundation that includes
IT management strategy and project
management. Students will understand
technology’s role in business and
position themselves to stand out in
the job market. The program can be
completed in one year, including the
required six month paid internship.
Flexible part-time options are offered
for working professionals.
According to a report by the McKinsey
Global Institute, US companies
will face a shortage of 1.5 million
people with the skills to analyze big
data and develop insights to make
business decisions. Students with
these skills are highly sought after and
well compensated. Companies that
hire Lindner MS Business Analytics
graduates include Amazon, PayPal,
Procter & Gamble, Disney, McKinsey
& Co, Morgan Stanley, Microsoft and
many others.
business.uc.edu/msbana
Recognition for the Lindner
MS in Business Analytics
u One of InformationWeek’s “Big
Data Analytics Master’s Degrees:
20 Top Programs” and one of only
eight business schools to earn that
honor.
u Included in “23 Great Schools
with Master’s Programs in
Data Science”
by mastersindatascience.org
LINDNER College of Business
Upcoming Center Events
u March 26–27: “Analytics in Excel” Training Course
This course will introduce intermediate-to-advanced tools in Excel for
analytics. We will cover data visualization topics that move beyond the
basic charting tools in Excel. Descriptive analytics methods for analyzing
data and generating meaningful insights will be covered using PivotTables,
PivotCharts and other Excel tools. We will use Excel for predictive analytics
by utilizing Excel’s regression tools and other forecasting capabilities.
What-if analysis and other prescriptive analytics tools in Excel will also be
introduced. This is the perfect class for the Excel user who is ready to take
the next step of improving their analytics capabilities in a familiar software
environment.
Register at regonline.com/uc-excel-analytics
u April 2–3: “Introduction to Data Mining”
Students are 100% employed upon
graduation as Network or Software
Engineers, Systems Analysts,
Database Managers, Information
Systems Managers, or IT Consultants.
Companies that hire Lindner MS
Information Systems graduates include
Google, Microsoft, Accenture, Yahoo!,
EY, Deloitte Consulting, Procter &
Gamble, SAP, Unilever and many
others.
u April 23–24: “Advanced Data Mining”
business.uc.edu/msis
Stephen Few has over 20 years of experience as an innovator, consultant,
and educator in the fields of business intelligence (a.k.a. data warehousing
and decision support) and information design. He focuses on the effective
analysis and presentation of quantitative business information. Stephen is
recognized as a world leader in the field of data visualization.
Graduate Certificates
The Lindner College of Business offers
a number of graduate certificates
(shorter program) as part of a degree or
as stand-alone learning options. The 12
credit hour Data Analytics certificate
is selected by many MS Information
Systems students and working
professionals. A 20 credit hour Data
Science certificate is also offered jointly
between the College of Engineering
and the College of Business.
business.uc.edu/certificate
u May 29: “Analytics Summit 2015”
This year the Summit will feature two internationally recognized leaders in
the field of analytics.
Dr. John Elder leads America’s largest and most experienced data mining
consultancy and his company has solved projects in a huge variety of areas
by mining data in tables, text, and links. Dr. Elder co-authored 3 books, has
created data mining tools, and was a discoverer of ensemble methods.
FOLLOW AND VISIT US ONLINE:
business.uc.edu/analytics-center
@UCBusAnalytics
UCAnalytics
RISK
ANALYTICS
DAY
February 11, 2015
UC Center for Business Analytics
UC Center for Business Analytics: U Square @ the Loop
225 Calhoun Street, Suite 300, Cincinnati, Ohio 45219 | 513-556-7146
business.uc.edu/analytics-center
DATA - D R I V E N A N A LY T I C S
E D U C AT I O N A N D R E S E A R C H
The UC Center for Business
Analytics, a corporate-academic
partnership, brings together
best-in-class stakeholders, and
a world-class multidisciplinary
group of MS Business Analytics
and Information Systems
faculty and students. The Center
promotes the use of data-driven
analytical methods that improve
business, government, and
organizational performance.
We engage faculty and students
to work with Center members
and business organizations to
develop methods and models
for using large data sets.
Risk Analytics Day
Agenda
7:30–8:30 a.m.
Registration and Networking Breakfast
8:30–8:40 a.m.
Welcome Message
Jeff Camm
Director, UC Center for Business Analytics
8:40–9:40 a.m.
Mark Nigrini
“Benford's Law as a Risk Analytics Tool”
CENTER STAFF
Professor Jeff Camm, Director
Geoff Smith, Associate Director
Larry Porter, Staff
Tricia Burger, Administrative Assistant
February 11, 2015
Speakers
Mark Nigrini, West Virginia University, PhD Accounting University of Cincinnati
Benford’s Law as a Risk Analytics Tool
In the 1930s, Frank Benford, a physicist at GE discovered that there were predictable patterns to the
digits in lists of numbers. He showed that the ten digits were not expected to occur evenly in tabulated
data. The digit 1 was expected to occur about six times as often as the digit 9. We’ll cover the reasons
for the uneven distribution of the digits. We’ll discuss some examples of fraudulent and erroneous
data. We’ll conclude with some cautions against drawing incorrect conclusions from our data.
Mark Nigrini is the author of Forensic Analytics (Wiley, 2011) and Benford’s Law (Wiley, 2012). His work is regularly
featured in the press with a recent mention in a WSJ article in December, 2014. Mark published a fraud-related article,
co-authored with an incarcerated fraudster, in the August, 2014 issue of the Journal of Accountancy.
9:40–10:40 a.m.
David Kelton, Professor, Department of Operations, Business Analytics, and Information Systems, University of Cincinnati; and Visiting Professor, Department of Operations Research, Naval Postgraduate School
10:40–11:00 a.m.
The real world is a complicated place, so models of reality often need to be accordingly complicated in
order to be valid. This talk will focus on valid simulation modeling and analysis, go over several sound
applications of simulation in a variety of settings using current commercial simulation software, and
conclude with what’s needed for continued success with simulation as a method of choice.
David Kelton
“Valid Models and Analytics of Risk in
Complex Real-World Settings: Simulation
as a Method of Choice”
Valid Models and Analysis of Risk in Complex Real-World Settings: Simulation as a Method of
Choice
The Center hosts events that feature nationally known speakers and holds
professional analytics training classes. Analytical research and consulting
services, as well as, onsite corporate analytics training, using actual company
data, in any area of data analytics and data management are also offered.
Coffee Break
11:00 a.m.–12:00 p.m.
Sam Savage
“The Flaw of Averages and How to Cure It”
David Kelton received PhD and MS degrees in Industrial Engineering from the University of Wisconsin-Madison, an MS
in mathematics from Ohio University, and a BA in Mathematics from Wisconsin. He has also been on faculty at Penn
State, Michigan, Minnesota, and Kent State. In addition to 100 refereed publications, he has co-authored three simulation books. He was Editor-in-Chief of the INFORMS Journal on Computing for over seven years and is a Fellow of both
INFORMS and IIE.
UC Center for Business Analytics Partners
12:00–1:00 p.m.
Sam L. Savage, Stanford University and probabilitymanagement.org; author of the Flaw of Averages.
uAmerican Modern Insurance Group
uGE Aviation
uAxcess Financial
uGreat American Insurance
uCincinnati Bell Technology Solutions
uKroger
uCincinnati Children’s Hospital and
Medical Center
uMacy’s
uCintas
uProcter & Gamble
uData Intensity
uSAS
udunnhumbyUSA
uThe Cincinnati Insurance Companies
uEY
uUS Bank
uFifth Third Bank
uVantiv, Inc.
Lunch
1:15–2:45 p.m.
Software Demo Session 1
Arena - 400A/MathSIP - 400B
2:45–3:00 p.m.
Afternoon Break
3:00–4:30 p.m.
Software Demo Session 2
Arena - 400B/MathSIP - 400A
The Flaw of Averages and How to Cure It
The Flaw of Averages is a set of systematic errors that occur when single “average” outcomes are substituted for uncertain future forecasts. It masks both risks and opportunities. Today we have reached a
technological tipping point in which new standards and methodologies may be applied directly within
the common spreadsheet to simultaneously view thousands of future scenarios, and cure this endemic
problem. No statistical background is assumed, but for those with extensive training in this area, this
presentation will attempt to repair the damage.
Sam L. Savage is Executive Director of ProbabilityManagement.org, a nonprofit that is rethinking uncertainty through
standards, best practices, and education. Dr. Savage is author of the “Flaw of Averages: Why We Underestimate Risk in
the Face of Uncertainty,” and is a Consulting Professor at Stanford University. Dr. Savage consults and lectures extensively to business and government agencies, and has served as an expert witness.
business.uc.edu