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Forecasting Beer Production Using Time Series Analysis

April 23, 2019

Forecasting Beer Production Using Time Series Analysis

When facing a business question, it's important to put thought into the problem, try to understand what data is needed for your analysis, try different techniques to arrive at an answer, and be prepared to fail. 

Most analyses don't lead to a crisp answer the first time. Iteration is key. 

Join us for this lecture, led by Dan Trepanier, Faculty Director at SCU, as he looks at a beer production dataset to help you: 

  • understand the nature of the data 
  • understand trends, seasonality, and cyclicality of beer consumption and production 
  • come up with a model to predict beer production over a 3 year horizon

About Presenter:

Dan Trepanier is an adjunct lecturer in the Information Systems and Analytics department and the current faculty director of SCU's M.S. of Business Analytics program.

Dan was most recently CEO of Xambala, an electronic market maker in US Equities where he led Xambala’s pivot from a hardware fabless semiconductor vendor to a proprietary trading firm. He built the team for the new business model, grew the revenue and ultimately sold the firm to Final, an Israel based trading firm. Prior to Xambala, Dan was founder of Quake Technologies, a semiconductor firm that led the development of 10 G Ethernet networking technology. He sold the firm after growing it to profitability.

Dan received a BScE (Electrical) from Queen’s University and his MBA from NYU. In his spare time Dan enjoys running, yoga, and sailing.

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