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Predictive Analytics Speaker

 
Patrick Schwerdtfeger is a leading authority on global business trends including predictive analytics and the “big data” revolution. The amount of data being accumulated is doubling every 18 months and data scientists and engineers are looking for attribution and developing algorithms to solve the world’s most pressing problems. In so doing, they are literally ‘optimizing’ our water consumption, energy usage and agricultural production. As population growth slows around the world, it is precisely technologies like these that might save the planet from the damage we have caused thus far. In addition, these same techniques in predictive analytics are allowing companies to anticipate consumer demand and react accordingly. Patrick is the author of the award-winning book Marketing Shortcuts for the Self-Employed (2011, Wiley) and a regular speaker for Bloomberg TV. He has spoken at business events and conferences around the world. His program on predictive analytics focuses on case histories and success stories where companies have leveraged their data to find new revenue, reduce costs or increase market valuation.
 

Big Data Motivational Speaker

 


 

 

Past speaking clients include:

 

Business Intelligence Speaker

 

Recent speaking destinations include:

 

 

Keynote Speech on Predictive Analytics

 
Predictive analytics is all about forecasting the future, even if just by a few milliseconds. Examples range from Target modeling the shopping behavior of pregnant women to Walmart predicting shopping behavior ahead of a hurricane. Predictive analytics allows Netflix to suggest movies and Pandora suggesting songs, all based on past preferences. Wall Street companies use predictive analytics to identify stock market trading opportunities and police departments use it to anticipate crimes before they occur. These are all examples of big data algorithms in action, and Patrick’s keynote delivers them in an engaging and thought-provoking way.

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The term ‘big data’ refers to the processing of data sets that are so large that they require ‘parallel processing’ to analyze. Technologies like Hadoop and MapReduce are allowing companies and governments to process terabytes, petabytes and hexabytes of data, and then exploit the valuable insights they discover. Inevitably, these insights (normally defined in terms of correlations and causation) are combined into sophisticated algorithms that generate actionable guidance as a result. Patrick’s case history approach (similar to the Harvard Business School methodology) allows your attendees to think creatively about the data they have themselves and how they might leverage it in the future.
 


 
The process of stimulating creative thinking around predictive analytics is driven by asking the right questions. What would you do if data processing, bandwidth and storage were free? Can your data be sold in raw or aggregated formats? Can your data spur activities that generate cash flow? Can your data affect operations so as to increase market valuation? Asking these questions, even in isolation, often stimulate new ideas. But when combined with a series of inspiring case histories, they generate excitement and buzz among attendees, even at executive levels.
 

 

The Future of Predictive Analytics

 
Data mining is at the core of business intelligence. Data analysts, data scientists and data engineers will be in increasing demand as predictive analytics proliferates and companies are well advised to begin recruiting talent in their IT departments. Data analytics will lead to a more intuitive world and those companies who implement the process early will capitalize on the trend financially. Data processing, bandwidth and storage are all evolving along an exponential curve, meaning that analytics will encompass larger and larger data sets as time passes. The time to seize the opportunity is now!
 


 
There are an increasing number of business intelligence tools available for companies to use. IBM has their acclaimed Netezza platform and other companies including Oracle have other alternatives. Meanwhile, ERP (enterprise resource planning) platforms are integrating systems across large organizations, accumulating massive quantities of data in the process. Finally, the field of data visualization is exploding, making insights easier to interpret. These three trends are converging quickly and businesses will soon have access to integrated platforms that allow for data accumulation and predictive analytics at the same time.
 
Because of the surging demand for predictive analytics expertise, Patrick has created a small website dedicated to that topic. You’re welcome to visit it by clicking here.
 

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