Headquartered in Burlingame, CA, Blazent Inc. is a provider of big data services that help enterprise IT departments and managed service providers collect and analyze masses of decision-making information from their management and operational systems in near real time. In this executive Q&A, Blazent CTO and chief product officer Michael Ludwig shares his front-line perspective on implementing and operating an effective big data platform.
What are the keys to success in big data?
First, you have to understand what you’re trying to accomplish. People disappointed by a big data project usually weren’t clear going in on the end results they hoped to achieve. Second, you have to think carefully about your data sources. Some of the data our system uses, for example, is generated automatically by IT systems but some of it is entered manually by end users, and could be inaccurate. You need a way to weight sources like that differently based on their reliability. Third, information is changing continually, so you need to account for the fact that a source saying one thing today may be trumped by another source saying something different tomorrow.
How are disruptive technologies generally and big data specifically changing the CTO’s role in today’s enterprise?
There’s an immense amount of breakthroughs occurring in many different areas of IT today, so you have to spend a lot of time researching emerging technologies and how they could impact you. It helps to have a community of smart people outside your organization who you can trade ideas and questions with. I have a network of friends and experts across the industry who I speak with pretty frequently.
How have the demands of big data impacted your talent strategy and leadership style?
It’s no secret that big data experts are in short supply right now, so if you have any on staff you need to take good care of them. We have some world-class people here and we make sure our environment and culture keep them productive and free from distraction. We’ve also invested in Web conferencing and other systems that help them work whenever and wherever they want, because these kinds of people don’t necessarily keep 9-to-5 hours. As for leadership style, you have to allow people to be at their best while still meeting business objectives. There have been instances when we’ve had to ship an algorithm that some people thought wasn’t perfect yet, for instance, because time to market is so critical in this industry.
Your title is CTO but you’re also part of a four-person “Office of the CTO.” How did that structure come about, and how does it work?
It was kind of an organic process, actually. We were completely re-doing our backend infrastructure and four of us turned out to have complementary skills. One of us is really strong in data modeling, another has deep knowledge of the latest big data technologies, a third has a close eye on what’s happening in the startup world, and I’m good at analyzing how all of that affects our solution. From the very beginning, it’s been a lot like being in a band. We each understood that we were playing different instruments but that they all needed to fit together. I lead the group, but we seldom have significant disagreements.