Mike Capone, chief executive officer at QlikTech International AB, and Harveer Singh, chief data officer at Truist Bank, join theCUBE’s John Furrier and Bob Laliberte at Qlik Connect to explore how AI and data analytics are reshaping business outcomes. Their discussion highlights how Qlik’s strategic evolution is rooted in customer needs, with a growing focus on trust, data quality and operational agility.
Capone shares Qlik’s innovation journey through acquisitions and platform enhancements, describing how end-to-end integration simplifies complex workloads. Singh outlines Truist’s use of Qlik to streamline financial services delivery, emphasizing adaptive strategies and platform-based efficiency.
The conversation covers AI governance, data mobilization, and the importance of real-time actionable insights. Capone and Singh capture how business leaders are aligning data and AI to solve real-world challenges.
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Harveer Singh, Truist & Mike Capone, Qlik
Mike Capone, chief executive officer at QlikTech International AB, and Harveer Singh, chief data officer at Truist Bank, join theCUBE’s John Furrier and Bob Laliberte at Qlik Connect to explore how AI and data analytics are reshaping business outcomes. Their discussion highlights how Qlik’s strategic evolution is rooted in customer needs, with a growing focus on trust, data quality and operational agility.
Capone shares Qlik’s innovation journey through acquisitions and platform enhancements, describing how end-to-end integration simplifies complex workloads. Singh outlines Truist’s use of Qlik to streamline financial services delivery, emphasizing adaptive strategies and platform-based efficiency.
The conversation covers AI governance, data mobilization, and the importance of real-time actionable insights. Capone and Singh capture how business leaders are aligning data and AI to solve real-world challenges.
Chief Data Officer, Consumer & Small Business BankingTruist
Mike Capone
CEOQlik
Mike Capone, chief executive officer at QlikTech International AB, and Harveer Singh, chief data officer, Consumer and Small Business Banking, at Truist Bank, join theCUBE’s John Furrier and Bob Laliberte at Qlik Connect to explore how AI and data analytics are reshaping business outcomes. Their discussion highlights how Qlik’s strategic evolution is rooted in customer needs, with a growing focus on trust, data quality and operational agility.
Capone shares Qlik’s innovation journey through acquisitions and platform enhancements, describing how end-t...Read more
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What is the response or feedback to Mike's Keynote presentation?add
What was the speaker's experience working in consulting and their views on data transformation and access in relation to AI and competition?add
What is the company's approach to connecting to data sources and targets quickly, and how does their platform operate in relation to different technologies and reference architectures?add
What is the speaker's perspective on the use of AI and data pipelines in business growth?add
>> Welcome back, everyone, to theCUBE's live coverage of Qlik Connect 2025 here in Orlando, Florida. I'm John Furrier. Bob Laliberte from theCUBE Research. Got a great lineup. Premier guests coming on theCUBE. Mike Capone, CEO of Qlik. Thanks for coming on. Good to see you again. Harveer Singh, Chief Data Officer, Truist, fast-growing financial institution, doing great. A lot of data. Thanks for coming on.
Harveer Singh
>> Thank you.>> Good to see you. Both CUBE alumnis, welcome back.
Mike Capone
>> Thanks.
Harveer Singh
>> Thank you. Good to be here.>> Well, I want to get into the customer situation as you guys are on this massive expansion and journey. Mike, we'll start with you. Keynote, it was phenomenal. Great review. I love some of the narrative, trust, precision, decision engine, dashboards, all this great stuff. And then the open data lake with the managed service for Iceberg. Great call there. And then you got the cloud, you got answers kind of coming together product-wise. Strategy from last year is executing. One, how do you feel and what's your takeaway? What was the response? What was some of the feedback?
Mike Capone
>> Yeah, well, I mean you're sitting here, right? So you hear it behind you. I feel great. I feel great. This is a journey we've been on for a number of years. You know, a number of years ago we set out to build this end-to-end platform. We saw this AI thing coming, right? We saw this wave of AI, but we knew the key to it was going to be data. Data, data quality, data governance, trust. We talk about trust a lot and so 14 acquisitions later, lots of organic R & D, we built this out and all the innovation that you're talking about was always in our head is like, this is where we got to get to. And not only we got there, but I think we even got a little bit ahead. We talk about some of the open data lake work that we're doing, structuring unstructured data together. So to answer your question directly. I feel really great. I feel great.>> Well, we feel great for you watching the story, but I think it's still undertold because a lot of people might not know, Qlik has got a lot of jewels in the treasure chest. You've been doing the in-memory thing, you had this gen AI before gen AI kind of hit the scene. You guys know data, you know dashboards, so you got a lot of value and I think it was demonstrated. So I think we'll do our best to get out. Harveer, I want to get your take because you know what I'm talking about here. They got the tools.
Harveer Singh
>> So every time they acquire something, I am like, okay, now it's their problem. One less thing for me to worry about it. I'm a big believer of financial services like us. We are more assemblers than builders. We want to build solutions for our clients and customers. We want to focus on technology, but we're not Amazon, we're not Google. We want to bring in the best of these tools together. So once this starts happening, the number of, I think, the moving parts reduces, which is what these guys are doing. It helps us saying one less thing to worry about, one less failure to worry about, one less sleepless night for me and my production support team. It helps us a lot. Putting everything end to end, looking at things end to end, it helps us a lot. So that keynote signifies the importance of less moving parts. Let's bring it into one place. Let's act on it when it's there and let's make sure it works end to end. So kudos to the team, kudos to you who make that happen. And again, like you said, the response is phenomenal. I go to other conferences as well. I'm pretty blown away by how many people were there at the keynote. Every single seat was taken. Very impressive, amazed, great to be a partner and great to use the products and services as well.>> That's an authentic response. Mike. This speaks to the value of the word that's been kicked around a lot. I think it would encapsulate the show is, "unlock," is a word I'm hearing a lot. Unlocking value. It's all about assembling solutions, not being the R & D machine learning, $5 million salary DeepMind engineer. They're building, they have machine learning, good people. But I mean the point is these assembling, your customers want it to work.
Mike Capone
>> That right.>> The domain expertise and the business logic is in the enterprises.
Mike Capone
>> That's right.>> So you guys are creating that unlocking. What's your take on that? Because this unlocking value is money or productivity or some task.
Mike Capone
>> Yeah. Well, I mean first mean a lot of our innovation's actually customer-led. We talked about this a lot today. And in fact, I remember I was down with Tom Mazzaffaro from Truist who actually mentioned, "Hey, you guys should be thinking about this iceberg stuff." And we were, but it was great to get that validation and let's talk about unlocking, but we work on outcomes. So what outcome are we trying to drive? In a lot of cases, "Hey, we want to do AI, but it's getting really expensive. Can we afford to do AI at this rate? My bills are getting really big." So it really is understanding the customer's perspective on what outcome they're trying to drive and then the capabilities of technology are just a means to an end, and then wrapping services and other things around that in a true partnership fashion is really how you unlock value for our customers.
Bob Laliberte
>> And so along those lines, Haveer, you also had a long partnership with Qlik. Can you talk about how they've helped you execute faster, how they've helped you move to greater business benefits? You already talked about the personal benefits that you have that you actually get to go home at the end of the night. I'm wondering if you could share also maybe some of the other ones for your business as well.
Harveer Singh
>> So interestingly, I have sat on both sides of the equation. I've sat on the consulting side. I used to work for Anson Young, Deloitte and Accenture's of the world where I actually started a lot my journey with Talend, to be honest, looking at Talend and building that Talend. During the first phase of Hadoops and stuff where people really didn't know how to use that Talend, came in and said, we'll tell you how to use Hadoop the right way, et cetera. And really taking a different lens on so-called ETL. Don't make it rocket science. It's data, transformation of data, it should be as simple. If you can see it, you can do it, right? That was the motto. And I think they've kept on to that as well. And Qlik and Talend coming together was even more interesting because honestly, the race for AI, the winner is the one that will have access to the data the fastest. It's not about having the data, it's having access to the data. How soon can you move the data close to the model? How soon can you execute it? A lot of people will have data, but how soon can you act on it is going to be that winner. I often say this from our side, banking institutions, everyone's running a customer churn model. Everyone's running a customer acquisition model. It's not about that. It is how soon can you take that data and act upon it is going to be the ultimate winner. So for a lesson learned for a lot of companies is bring the data closer to that. How soon can you move it? Because when data moves, money moves.
Bob Laliberte
>> Absolutely.>> And you guys are in growth mode right now of the company.
Mike Capone
>> Yeah.>> Take us through your thinking around how you're looking at the data. Obviously the one-stop shop that Qlik has a lot of, again, tools in the platform.
Harveer Singh
>> So for us, there are two sides of this equation. One is obviously modernizing our tech stack. Truist as a bank came together about three to five years ago, two smaller regional banks merged to become, they call it the super regional, right? We are very proud of our heritage. With any new mergers, there are issues that multiple technologies exist. So we took a hard stance in the last few years where we said if either we fix the issues that we currently have, and there were a lot, or we go modernize where we have to spend less time working on the issues, more time servicing our clients and customers. So for us it was a speed at which we could use tools like Talend and Qlik to modernize the stack, then worry about investing in ancient... Not ancient, but at least... It's still modern technology, but modern-legacy technology. Hadoop is still active and alive, but I'm almost calling it modern-legacy. But do we want to stay with modern-legacy or do we want to be modern-modern? Because again, by the time we are done, something else will come out. So it's the speed at which we want to execute. It was the key. So we trying to build this myself, it'll take three years by the time something else will come in. This is where I think Qlik and Talend came in together and say, "You guys do this fast. We are going to support you with whatever you guys need." So it's been a great 9 to 12 months last and we've already made things live in production. It's running in Snowflake today. Six months ago it wasn't there. So having a major turnaround like this in a financial institution with and with all the risk and the controls, it's almost unheard of. I'm super proud of that as well and super proud of the partnership that these guys brought to the table.>> That's a huge accomplishment, by the way. I just want to amplify that. The resilience bar that you have to hurdle over is massive. When just putting it perspective, what's your reaction to that? It's a great testimonial. Talk about how that comes about. Is it the platform? What is the main driver on the Qlik side that's enabling him to move faster and clear those hurdles and get stuff into production?
Mike Capone
>> Yeah, look, I think it is not having to be a construction worker and not having to actually cobble together five or six different tools to build an AI data pipeline. I mean, they really have really doubled down on Qlik and Snowflake. We work great with Snowflake to build these data pipelines, land it in Snowflake and run their business. And again, I wore two hats too, right? So I was a CIO, I was a CTO for many, many years of ADP and I was the one buying all these tools and it was super frustrating to have to be a systems integrator. And so having trusted partners who I knew were interested in my outcome, not just in selling me software at the end of the quarter, but actually showing what's possible. And I know what Tom says is, "Man, you guys are all so flexible in how you contract with us. Our success is your success, all those things." But it makes me really proud because this is what we've gone for. We've gone for success. Did your project succeed the way you wanted it to? That's our measure of success, not how many dollars we get from >> One of the trends I want to get your both reaction to is the platformization, I call this, at RSA mainly in security, but security is pretty much a good proxy for the AI market. There's a lot of data involved security. Platforms can be the best of breed point solutions that were once standalone companies now are featured. You're starting to see, I'm overgeneralizing, but the point is a platform has to be highly robust and work. Do you see platforms becoming key here? And is that what you're thinking is?
Harveer Singh
>> Platform is a key, and again, the more you have means more moving parts. My goal is to eliminate as many moving parts as possible, keep a simplified architecture because simplified architecture is easy to maintain, more cost-effective, total cost of ownership. And if the data doesn't move that much, it means that you're relatively able to access it and democratize it much faster. Now, a term that is used in a lot of recently or mostly is I want to be real-time. The question is why? I want to be batched. The question is why? Why can't you just be just in time for you to act upon certain things. Take out that notion of real-time and batch, just in time is the key to go. And that is the platform. Platformization is behind the scene as long as the data is available just in time, the business users, the application owners, it should not matter how it got there at the end of the day.>> how would you define simplified architecture? What would be an example of-
Harveer Singh
>> One, the medallion architecture actually helps simplify this. Snowflake has helped simplify a lot of things because once data lands in Snowflake, at least for us, we don't really move it around too much. We make access points available from Snowflake to consume. We don't want to have pipelines going from point to point. We are not into the business of maintaining those pipelines. So for us it's more around, you have, I'm almost going back to the back to the hub and spoke model. Once it's there, please come and get it from here. Don't force me to make a replica out there. Don't force me to make a copy out there. Every tool, every SaaS vendor that I've spoken to in the recent past, they're saying that we are building something called a zero copy. We'll be able to read it from Snowflake. Great. Fantastic. Come get it there. Golden copy of the data exists there. Come and get it from there.
Bob Laliberte
>> Yeah. So Mike, I wanted to go back to you. During your keynote, you made a couple of comments about one, starting off with, hey, there's a lot of people who aspire to use AI technology, but very few who are getting there and also commenting on the need to really accelerate the time to get there, to be able to execute and doing it faster is going to be really important coming into the next few years. I'm wondering if you could provide a few examples of how you think you're helping customers do that and be able to, obviously your company itself is executing, bringing these products, integrating them, pulling them together, making them simplified for the end users. But then I was wondering if you could share some highlights on where you think you're going to really be able to turn the needle for a lot of these organizations and help them accelerate their adoption of AI and agentic AI?
Mike Capone
>> Yeah, sure. Yeah, you saw the stats. So 87% of companies have an AI strategy, but only 24% are getting any value out of that strategy. So it's not a great formula for success. And what you heard me say today was you have to lean in. Everybody at this conference is here because they believe that data analytics and AI can change the fortunes of their company for the better. And so the way we help is, to your point, it's the data. We help people harness the data. Everybody, oh, there's a lot of disillusionment because people just try to plug in a model and some magic was going to happen somehow, right? And that's not how it works. And so our ability to actually connect to data, any source, any target, land it in any target quickly, six months, Harveer talked about to get up and running, is our magic. And our platform, you talked about having a bunch of different things together, it's not really a platform. So our religion is always, if we're going to do something, we actually will rewrite it onto our platform so it's completely seamless, so it's simplified architecture. Really, really important. And then the last thing I'll say is we're completely agnostic. So what happens is we say, you know what? We'll do business with you, you do business with us. So you want Snowflake? Terrific. You want Databricks? Terrific. You want both? Great. We do that too. Or AWS or Azure or anything else. And that makes it easy for customers because our answer isn't give us all your data and we'll solve your problem. It is tell us what your reference architecture is and we'll work inside of that to make you successful.>> You mentioned that you were the CTO, you were the buyer of the tools. As the CEO now, what is the relationship with your customers? Obviously Tristan's here, other customers, other CEOs you talk to. What is their consumption preference? Obviously Bill, he wants to get stuff, zero copy output, new architecture, everything's good, Iceberg's great. What is the vibe from a consumption standpoint as you as a supplier, you think in very neutral position, we'll work with anyone, we'll find the value. How is that translated on the other side? He's happy, obviously, loves it. Share some of that content.
Mike Capone
>> Yeah. Well, when I was at ADP, I had a billion and a half dollar IT budget. We were responsible for paying one in five people in the US and so I spent a lot of money. And the vendors that I didn't like were the ones that showed up at the end of the quarter with an order form saying like, "Hey, sign this." The ones that I love were like, "What outcome are you trying to achieve? And then what does success look like for you? What does success look like for you?" And then aligning the contractual terms with that success. And more and more that's becoming sort of capacity-based, consumption-based pricing. If I'm successful and this project works and I'm moving data where I need to move it, or in the case of Qlik Answers, if my employees are all using the product and I don't have a lot of shelfware, I'll pay you. If they don't use it, I'm not going to pay, right? Oh, but wait, you have a contract, you can commit it to all, that's really bad. Those things are bad. So it really is finding that, what does success looks like and then how do we share in that success versus one person winning, one person loses.>> So relationship less transactional, hey...
Mike Capone
>> It's totally relationship->> you, and then get you the contract at the end of the month, handout.
Mike Capone
>> Well, you got to get in the bed with me, right? It's like you really got to figure out, you can't win and drive your Ferrari up because you sold me a lot of software if I didn't get my job done as CTO or CIO. Right? So that's all. It's that simple.
Bob Laliberte
>> Yeah, no, absolutely. I think, yeah, and you had commented also on the importance of the team. So it's not like you're going to be going in and doing this by yourself all the time. There's going to be an ecosystem of partners that you go in and strategically partner with your customers. I'm wondering also, Haveer, if you could talk about that as well, maybe in that.
Harveer Singh
>> Yeah, so one of the criteria of picking software, is the Talend available? Is the community that is out there? And interestingly, good that Talend and Qlik has built a great community of developers and administrators and stuff that I can hire people off the street and get them up and running very quickly. Second is how well they're doing their training programs, how well they're jumping in with us and guiding us through that process. The architects that are being given to us to saying, "Let's make sure you are doing the best architect solution. Let's make sure your cloud infrastructure is optimized for best use." I think that adds up a lot of value. There are a lot of these, I'm going to say thankless goodies that comes with it, which is very important. Mike being on the other side, I'm sure he appreciate it on that side as well. I look at it very seriously because I need to get my people trained. I have staff that has been with us for like 35 years. How do I get them motivated to start using a tool and saying, "From now on, you're not going to use your green screen, you're going to use a completely different tool?" It matters. The community matters. The recognition matters. How many people are talking about the tool matters. So I think that way the buildup is pretty impressive as well.>> I appreciate your commentary about the simplified architecture and the Qliks benefits, but I have to ask you a personal question. On your job as chief data officer, what's it like right now? I mean, you can talk about stress levels, but I mean terms of how you're thinking systematically. There's a lot of side order effects going on. Data's critical. Obviously the relationship here, you pointed that out. What's it like these days to be a chief data officer? Has it changed since Mike was running the trillions of dollars of budget he had over at ADP or modern-legacy, what does that even mean? So take us through that.
Harveer Singh
>> So my job as a chief data officer for consumer and small business banking, obviously my boss is the group chief data analytics and AI officer. I hate to be in his position. He probably has more sleepless nights than I do. So for me, I have to balance two folds. One is ensure compliance and regulatory rigor. Second, making sure we are modernizing. And third, I call myself an internal sales consultant because everybody in the organization wants to be a data analyst. Everybody wants to run data analytics. So it's like, when do I need to put a gate down and when do I need to let them up? That's the key here. How many people do I get them access to? How much can I democratize? How much should be democratized? So look, I'm in this because I enjoy it. I love it. I call it, I wanted it. I have a 3M strategy. I said manifestation, it's motivation, and it's movement. You do one without the other two, it's a disaster. I'm pretty sure I manifested this. I'm fully motivated and now I'm moving towards it. So keep it interesting, I would say.
Mike Capone
>> That's great.>> Got to have the action. Mike, how's business? Obviously this show's a success. Strategy, execution. What's next for you? What's on your roadmap to think about next year? More customers, more customer testimonials, brand expansion? What's the journey look like for you at the helm?
Mike Capone
>> All the above. All the above for sure. You're never done with any of this stuff. Look, I mean for me, obviously business is... We're growing nicely. The business is going great. What I would say is I'm looking forward to coming back next year and having more people like Haveer here talking about how they did it. We built our AI data pipelines, we use Qliktown Cloud, we built out our platform, and we're seeing business success out of it. And people are understanding now that this is how you have to do AI. You got to do data differently, which is our tagline for this conference, "Do data differently." And if we can do that, then the rest will take care of itself.>> Haveer, for you, your to-do list going forward.
Harveer Singh
>> So my to-do list is one, make sure I experiment with something called "How does the data pipeline get developed itself by using JDI agentic AI," which is, if I have a BRD, or a business requirement document, technical requirement, and why is it not still possible for it to say, "I know where the data is, I'll go move it from point A to point B." That would be interesting. And I see the industry moving towards that because everyone that I've been speaking to, it's all about automation, it's all about agentic. I think the time has come for real data to become, I would call it boundary-less, seamless. You should know what is going on under the hood. As long as it's governed, it's available. The pipelines can automatically start. I mean, this was a vision, I think seven, eight years ago, I had started putting together a concept for marketplace where data gets moved around automatically. It never saw the light because the technology wasn't available at that point of time. I clearly see this happening now by simple commands as, "Hey, can you bring the customer data into Snowflake? I'd like to analyze something," as simple as that.>> Yeah, a Qlik. Literally. I have to ask you about AI readiness as agentic. You mentioned that's on your radar. How prepared are you? What's your view on this? How do you usher that era of greatness into the bank?
Harveer Singh
>> I think it's an evolving journey because AI relies on three things. It's the amount of data, the variety of data, and the quality of data. I've not seen any organization, even when I was in consulting, they have all of that three available at the same time. It's either you have all the data but not the quality. If you have the quality, you don't have all the data. So the aspirational goal is to get all of that three. Are you ever ready to have a baby? No, but you still have a baby. And that's the approach. Let's start to get there and we can keep adding on top of it. So I think we are as ready as we can be given our stance as a regulatory-governed organization. We are as ready as we can be, and we are experimenting. And our low-hanging fruit are obviously going to be mostly automation ones, and we'll get to the more interesting, the shiny objects at some point, given the stance of the business that we are in.>> You motivate me to do a blog post on legacy, modern-legacy, legacy-plus.
Harveer Singh
>> Modern-plus-plus.>> I mean, the data convergence, and AI is a good scenario. Mike, final thoughts on the end of the segment?
Mike Capone
>> Well, look, first, I want to thank Haveer for being here with me. It's really, really terrific and what a great partnership we have here. Thank you guys for having us on. And then, look, do you feel this? I mean, I feel it and just heard, I think that was our analytics roadmap session where that applause just came from. So great energy, great excitement, and looking forward to another phenomenal year and seeing you guys back here next year.>> Yeah, it's fun to cover you guys. Product-market fit on the right spots, humble and relevant. Thanks for coming on. Appreciate it. Okay. I'm John Furrier with Bob Laliberte and Kristen Nicole Martin is on the ground doing roving report. The whole CUBE team is bringing the data just in time here on theCUBE. Thanks for watching.
Bob Laliberte