Presented by Cenk Tunasar, Nicholas Nahas, Patrick McCreesh, Jeff Munns – Booz Allen Hamilton
Booz Allen’s implementation of analytics spanned over three years of support to ICE where they developed a set of models that are used to solve challenging problems such as: forecasting the number of criminal illegal aliens, optimizing a technology deployment schedule, and minimizing the transportation costs of removal. The impact of this work has resulted in a doubling of criminal alien removals leading to greater public safety for the American people.
Tools and Approaches for Big Analytics
Presented by Manoj Chari, SAS Institute
Chari discusses some of the high performance analytical tools, as well as data management approaches, being developed at SAS in order to meet a broad spectrum of requirements. He will use specific business use cases to illustrate the application of these approaches.
Modeling in Minutes, Not Months
Presented by Steven Hillion, Alpine Data Labs
Hillion identifies several of the most common obstacles to an agile analytics process, and also suggests potential solutions in areas from data acquisition and movement to modeling scalability and portability.
The Need for Speed: Responsive Prescriptive Analytics in Today’s Business Environment
Presented by T. Glenn Bailey, Manheim Consulting
Within the hierarchy of descriptive, predictive, and prescriptive analytics, the latter often serves as a benchmark for an organization’s analytics maturity. While O.R. make prescriptive analytics both possible and powerful, there are well documented challenges in integrating these techniques within the business decision-making process.
Connecting the Stars: Applying Social Media Understanding to a Structured Marketing Data Environment in a B2B World
Presented by Theresa Kushner, Cisco Systems
During this presentation, you’ll learn how a leading internet company employs listening not only in marketing, but in services and other product development functions, how marketing analytics is applied to help challenge the status quo in a demand driven marketing organization, and more.
High-Impact Analytics Teams: Defining Choices and Timeless Lessons
Presented by Thomas Olavson, Google
Olavson offers observations based on his experience leading teams of analysts at both HP and Google. While there are some defining choices that make analytics teams different (e.g., “data scientist” vs “OR analyst”), there are also timeless lessons that apply broadly to quantitative analysts wanting to convert analysis into business impact.
Click on the tracks below
The Analytics Process
Online Master of Science in Predictive Analytics
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