REPLACE Big Data Show logo
April 30 - May 1, 2025
North Javits Center | New York City

Introduction to Mike Ferguson
Program Advisor Profile for Data Universe 2024

In just over seven months Data Universe will be holding its inaugural event in New York City, April 10-11, 2024.  

When we decided to build this event for the US, which will take place at the North Javits Center—a sparkling technologically advanced venue on Manhattan’s west side—one of our core objectives was to find and deliver the most relevant, up-to-date, and compelling intelligence available pertaining to the data ecosystem, in a vendor-neutral format. To ensure we are aligned with market needs on this mission, Data Universe has assembled an exceptional network of global experts from different areas of the data space to provide advice and guidance on our conference topics and event experience. Leading up to Data Universe in 2024, we will be highlighting each of our advisors and their careers, industry insights, and thoughts about the unique potential for this event, as well as their role in it.


Mike Ferguson is CEO of U.K.-based Intelligent Business Strategies where he has built a reputation over four decades as one of Europe’s leading analysts and consultants in data management and analytics, data strategy, technology selection, data architecture, data governance, data warehouse design and implementation, self-service analytics, machine learning and AI automation. He is a long-time member of the advisory board for Data Universe’s sister show in the U.K., Big Data London (BDL). And, since 2017, he has served as its Conference Chair.

DU: You’ve had an amazing impact on Big Data London’s success, and we’re very much looking forward to having you on the Data Universe program advisory board.  What’s inspired you to contribute so much of your energy to these types of projects? 

MF: As an analyst and consultant I work with both end users and vendors every day, so I’m an independent party continuously keeping track of key trends in data, analytics and AI, new technologies, and new vendors in the space. I also thoroughly enjoy sharing what I’ve learned with my peers in the field. I think that will let me contribute to the success of Data Universe by keeping it on point in terms of addressing key issues in business and keeping it at the leading edge of the industry in data and AI.

DU: You’re based in the UK, but how familiar are you with the US market?

MF: I would say very familiar. Prior to setting up my own business, I worked in Los Angeles and San Diego for Teradata. Since I struck out on my own as an analyst and consultant, I travel to the U.S. as a consultant probably half a dozen times a year. I have been a regular speaker on U.S. vendor webinars and at U.S. conferences on data and analytics and I attend vendor industry analyst briefings in various parts of the U.S. on a regular basis.

DU: Do data businesses and end users in the U.S. differ from those in Europe or elsewhere?

MF: The first thing you have to recognize is, I think, that the U.S. is more of a single market compared to Europe. For instance, Germany, Austria and Switzerland can be treated as a market while the U.K., the Nordics, Belgium and the Netherlands share similarities. France is a market on its own. Things are happening at different speeds in those places. For that reason, go-to-market strategy has to be different across Europe for vendors selling into those markets. In the U.S. the attitude towards adopting a technology is very different, In the U.S. people are more prepared to take risks early—they like to fail and fail fast, and that's OK. That means the sales cycle is different in the two regions. In Europe they will be more careful before they spend but you'll find when they make a decision, they'll go big. U.S. businesses are much more prepared to get tooling and technology in, understand it and then move forward. As a result, the content of a show will reflect that. For example, even though the adoption of data mesh was hot in Europe last year, the U.S. is still further down the road with it.

DU: Interesting. What would you like to see Data Universe excel at in the first year? what’s the most important thing to consider when deciding about the content of a data show in the U.S.?

MF: While the hype for certain technologies in the U.S. might be a bit ahead of Europe, customers are never where the hype is. Customers are somewhere behind it, so the educational element of the show really matters. Communicating real use cases matters because people will attend to see what technology can really accomplish. What has succeeded and what has failed in the real world. . Educational sessions at the show will clearly demonstrate how organizations can drive real value by linking data, data management, analytics, etc. to real business outcomes using the technologies available today.

An example of that that will make sense at a show happening in New York is a big bank trying to reduce fraud by 10 percent in the next 12 months. That’s the desired outcome. The questions they need to answer include what data will they need to produce to help reduce fraud? What machine learning models will they need to develop to help reduce fraud? What business intelligence reports will give them the information they need to recognize a reduction in fraud? What decisions should be made based on the metrics contained in those reports? How does data machine learning, AI and BI relate to the strategic outcomes organizations want. Those are the practical questions that educational sessions at Data Universe will be able to answer.

DU: What are the headline trends driving the technology people are going to learn about at Data Universe?

MF: Generative AI and how it’s being integrated into various platforms is on everyone’s mind right now, so attention will certainly be paid to that as the need for automation grows. None of the AI works without solid data. Beyond that, data governance is a foundational idea that people have to be more aware of.

Data is spreading out. For every business, it's in multiple places: It's on multiple clouds, it’s on premises, it's at the edge, it's in software as a service applications. So most corporations have their data spread across multiple underlying data stores, making it harder to govern in an increasingly complex regulatory environment. I thought the EU was bad trying to regulate 27 member countries. But the U.S. is even more complex since you may have to comply with 50 different regulatory regimes at the state level.

Finally, upskilling is increasingly vital for businesses. Rather than rely on central IT experts to do everything, business line employees must become more data enabling organization-wide communication and execution of data and analytic strategy to achieve strategic business goals.