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Need a dynamic ‘Big Data’ speaker for your upcoming event?

Patrick Schwerdtfeger is a leading authority on global business trends including Big Data, Predictive Analytics and the future of Information Technology. He spoke about that topic twice in Dubai (May 2012 and January 2013) and has also covered the topic in Bogota, Colombia (as well as a variety of cities in America). Patrick’s Monetizing Big Data program breaks the topic down into three sections. First, he defines “big data” and what differentiates it from traditional analytics methodologies. Second, Patrick provides real-life case histories of data accumulation and opportunities for business intelligence (led primarily by data engineers and data scientists). The third section is focused on success stories and how some businesses have already leveraged big data to reduce costs, increase revenue and even transform their industries. Future profits will be driven by algorithms and businesses need to find ways to monetize their data.

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Patrick Schwerdtfeger earns over 90% of his income in speaking fees. He’s a regular speaker for Bloomberg TV and has spoken in dozens of countries around the world. Please contact us to check availability and discuss your event objectives.

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Patrick is a TEDx speaker who speaks regularly for Bloomberg TV. He’s the author of the award-winning book Marketing Shortcuts for the Self-Employed (2011, Wiley) and also maintains his Strategic Business Insights video blog. He has spoken at technology conferences and business events around the world. Patrick’s past books include Webify Your Business: Internet Marketing Secrets for the Self-Employed (2009) and Make Yourself Useful: Marketing in the 21st Century (2008). He has been featured by the New York Times, LA Times, San Francisco Chronicle, CNN Money, Inc. Magazine, Fortune, Bloomberg Businessweek, the Associated Press, MONEY Magazine and Forbes, among others.

Past speaking clients include …

Patrick spoke about “Global Mega Trends” at the 18th GCC eGovernment & eServices Conference in Dubai in May, 2012. He was later asked by Techmahindra to come back in January, 2013, to discuss “Big Data and the Future of IT” at their “Futurescape Dubai” event. The “Big Data” topic started to gain momentum and he delivered his “Monetizing Big Data” program for EPICOR in Scottsdale, Arizona, and for BMC Software again in Dubai, and then again in Bogota, Colombia, for their association of Contact Centers and Business Process Outsourcers (BPO). Patrick has been invited to cover big data, predictive analytics and business intelligence again in Guatemala City and Hamburg, Germany.

The program is perfectly suited as an opening session. It’s built on a series of case histories, but not entirely. The first third defines the key terms for attendees, explains the underlying technology trends and highlights the distinctions between “big data” and traditional analytics. The second third provides a series of success stories (including the NSA, Google, Target, Walmart and UPS among others) and the last section details the common themes to the case histories and identifies the primary opportunities for companies going forward.

Recent speaking destinations include …

Background for Big Data Keynote Speech

The accumulation of data is accelerating. It began with the stock market and weather satellites, and soon included utilities, credit card companies, eGovernment initiatives and medical providers. Today, most large companies are harvesting massive quantities of user data. The problem is that they have no idea how to process it or even what to look for. The objective of data analytics is to find the patterns and opportunities hidden in all that data and the skills necessary are those of data engineers and data scientists.

Historically, all of the data engineers were gravitating to the stock market companies, working on trading algorithms and arbitrage platforms. That’s where the money was, but the Great Recession changed all that. With the virtual collapse of the financial markets in 2007 and 2008, tens of thousands of data scientists were laid off. That created an enormous opportunity for technology start-ups as well as Fortune 500 companies. All of a sudden, the available engineering talent exploded and other non-financial businesses started taking data analytics seriously.

The next step was to develop algorithms to exploit the needs and wants hidden in the data. This ranged from delivering personalized music songs on Pandora to matching kidney transplant donors at hospitals. It included sophisticated weather models and pharmaceutical prescription processing programs. Indeed, the future is all about algorithms. It’s all about delivering customized data based on a myriad of statistical inputs. So who rules the future? Those who optimize their data and monetize their analytics!

Structured versus Unstructured Data

The vast majority of data is unstructured. It resides in lengthy machine logs and is almost never in a consistent format from one server to the next. As a result, most companies avoid it and analyze their structured data instead. Turns out, the unstructured data holds far more promise than the structured data. Patrick’s big data keynote encourages attendees to embrace their unstructured data. He provides examples of unstructured data and event details all the information contained in the meta data of a single email.

Traditional data analysis involved sampling and rational databases. This is no longer the case. With technologies like Hadoop and MapReduce, companies are able to process entire datasets that were far too large for traditional databases. The primary difference is that traditional sampling techniques effectively ignored outliers whereas the new big data approach allows businesses to process ALL of the data, including the outliers. Those statistical outliers turn out to provide the most valuable insights with respect to business intelligence. This shift from sampling to an “N=all” approach is a fundamental shift in data analytics.

Information Technology and Business Trends

doesn’t come from the IT space. He’s not an engineer. His background is in global business trends, of which technology is one. Many of the industry experts in the ‘big data’ space are highly technical and their presentations can often be intimidating (and sometimes even boring) for attendees. Patrick’s passion is effective delivery as a speaker. He has built his career as a professional communicator and takes pride in having dynamic and entertaining programs.

Patrick’s perspective is strategic yet his explanations are accessible. Patrick’s father was a quantum physics professor at the University of British Columbia (UBC). His oldest sister is a PhD in inorganic chemistry and she married a PhD in robotics. His second sister is a PhD in organic chemistry and she married a PhD in biological sciences. So it’s safe to say that Patrick grew up with a lot of highly methodical left-brain people, yet his education is in finance and marketing, and he accumulated extensive sales experience before becoming an author. The result is an effective communicator who instinctively knows how to speak with engineers and science personalities.

Most big data speakers are scientists with impressive credentials. The problem is that most of their programs are fairly boring to listen to. Patrick doesn’t have those scientific credentials but he delivers an inspiring program full of case histories and success stories, leaving attendees with a solid understanding of the underlying technology trends and plenty of examples of how they might analyze their own data to increase revenue, reduce costs or transform their industries. Patrick’s “Monetizing Big Data” program has received outstanding reviews from technology conferences around the world.


Visit the Programs page to see Patrick’s four primary speaking topics along with descriptions and sample videos.


Visit Patrick’s “Strategic Business Insights” video blog to sample his content style, approach and delivery.


Contact us to check availability on your event date and get a quote to have Patrick speak at your upcoming event.