Chief Data & Analytics Officer UK (CDAO UK) is the United Kingdom’s premier event for senior data and analytics executives. The three-day event, with more than 200 attendees and 50+ industry-leading speakers, was packed with case studies, thought leadership, and practical advice around data culture, data quality and governance, building a data workforce, data strategy, metadata management, AI/MLOps, self-service strategies, and more.
Chris Santiago, Unravel VP of Solutions Engineering, sat down with Catherine King from event host Corinium Global Intelligence to discuss what’s top-of-mind for data and analytics leaders.
Here are the highlights from their 1-on-1 interview.
Catherine: What are you hearing in the market at the moment? What are people coming up to you and having a chat with you about today?
Chris: I think that, big picture-wise, there are a lot of things being talked about that are very insightful. But some of the stuff that hasn’t really been talked about are the things that people don’t want to talk about. They have this grand vision, but how are they going to get there? How are they going to execute? How are they going to have the processes in place, the right people hired—that sort of thing—to take advantage of data and all the great technology that’s out there and actually execute on the vision?
Catherine: I think you’ve hit the nail on the head there. I think the technology piece, which was so prevalent a few years ago—do we have the right tech, the right tools, to go out and do these things?—that’s almost been ticked off and done. Now it’s actually, do you have the processes in place to achieve it. So from your perspective, what would you like to see businesses do differently?
Chris: The technology has made leaps and bounds over the last few years. If you think about big data people who came from the Hadoop world, one of the challenges of that stack was that it did require expertise. Companies back then struggled to get the ROI on performance, on getting some sort of business value at the end of the day. Fast-forward to today, especially with the advancements in the cloud, they have solved a lot of the challenges. Ease of use? I can just literally just log in, click a button, and have an environment. Storage is cheaper. A lot of the problems back then have been solved with today’s technology.
I do think that the one thing that hasn’t been 100% solved yet, though, is the people, the skills. Right now, the things technology is not necessarily addressing directly are: Do we have the right skill set? Do we have the right people? As more folks are using these newer technologies, the gap in skills to do things the right way and best practices are not being directly addressed. The way that most customers are handling it right now is that they’ll bring in the experts, consultants like Accenture, Avanade, Deloitte, etc.
In order to achieve the true ROI in these data stacks, it’s adjusting the people-problem.
Catherine: What do you see coming in the next 12 months?
Chris: I think that if we look at the industry as a whole, a lot of the technology is still considered new(ish). You have a lot of folks who are still using DevOps tools. So they’re trying to work with observability tools that are focused on the issues that aren’t necessarily what data teams want. So I think in the next six to twelve months we’re going to have a proliferation of observability trying to solve this problem specifically for data teams. Because they’re different problems [than software application issues]. You can’t use the same [APM] tooling for folks who are running Databricks or Snowflake. There are going to be different problems, different challenges.
Obviously, Unravel is in that space now, but I do think the industry will recognize more and more that this is actually not just a small problem, but a major problem. Companies are starting to realize that [observability designed for data teams] is not a nice-to-have anymore, it’s a must-have—and needs to be addressed right now.
Everybody has a vision. Everybody has an idea of what they want to do with data, whether it’s having that strategic business advantage or getting insights that they didn’t know about—everybody trying to do really cool stuff—but everybody always seems to forget about how to execute. There’s lots of interesting talks about how we’re going to measure things, what KPIs we’re going to be tracking, what methodologies we should have in place—all great stuff—but if you truly want to be successful, it’s all about execution and [doing] the stuff people don’t want to talk about. That’s what will set up companies to be successful or not with their data initiatives, getting into the weeds and solving these hard challenges.