Data + AI Summit 2025 | Dan Morris, Databricks

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Dan Morris

Global Head of Marketing Solutions GTM

Databricks

Inside Databricks’ AI revolution: 10 key takeaways from the Data + AI Summit

Artificial intelligence is becoming more intuitive, interactive and embedded, not just in systems, but in the way companies build, think and create. From live coding and autonomous agents to unified governance and automation, Databricks Inc. is moving AI closer to the application layer and aligning it with developer intent.TheCUBE Research’s John Furrier and George Gilbert break down the keynote analysis during Databricks’ Data + AI Summit.“You sort of tell the AI engineer, the software developer, an agent, what you want to do,” said George Gilbert, principal analyst for theCUBE Research. “In the past, all it did was generate code

play_circle_outline Data + AI Summit highlights the importance of Data Intelligence for Marketing at Databricks.

play_circle_outline Challenges include siloed data and dependency on tech teams affecting marketing efficiency.

play_circle_outline Data Intelligence for Marketing unifies data, AI, and consent for personalized customer experiences.

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Dan Morris, Databricks

Dan Morris

Global Head of Marketing Solutions GTM Databricks

Dan Morris, global head of marketing solutions GTM at Databricks Inc., joins theCUBE’s John Furrier at the Databricks Data + AI Summit 2025. The conversation examines how unified data and AI are revolutionizing marketing strategies across various industries.

Morris shares how a single source of truth enables faster decision-making, stronger campaign execution and improved brand performance. He emphasizes the importance of breaking down silos and aligning teams through shared data intelligence.

The discussion highlights how Databricks empower... Read more

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What is the significance of Data Intelligence for Marketing and what new solutions are being developed for it? add

What challenges do marketers face in utilizing data effectively for their campaigns? add

What is your perspective on the integration of Data Intelligence for Marketing within organizations? add

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Dan Morris, Databricks

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>> Welcome back, everyone. theCUBE's live coverage here in San Francisco for Databricks's Data + AI Summit. It's their annual event. My name's John Furrier, host of theCUBE. Our whole team is here. Dan Morris, head of marketing solutions, go to market for Databricks. Data Intelligence for Marketing is a big theme. If you look at AI, coding and sales and marketing are the two hottest areas. Of course, analytics has been around for a decade. That's continuing to vector into it, but the hot generative AI use cases are in sales and marketing and, of course, coding. Dan, welcome to theCUBE.

Dan Morris

>> Thank you for having me.

>> You're closing us out here on our big day. Thanks for coming on.

Dan Morris

>> Thank you for having me.

>> Data Intelligence for Marketing is kind of the topic that we want to drill into, but the news is pretty significant. You start to see the Agent Brick. That's going to bring up a lot of use cases, a lot of automated, human-assisted, and you got some intelligence there with the judges and all the algorithms. But sales and marketing has been really robust in the application use cases we've been seeing in the market. I mean, everyone I talked to is either taking customer databases and doing some RAG, doing some content development, "Hey. Write a LinkedIn post. Maybe build some literature." You're starting to see presentation, all kinds of action. So you guys have recently unveiled the Data Intelligence for Marketing. There's a whole nother level here. Can you share what that is? What are you guys working on? What is the marketing solutions for Databricks? I'm sure it's going to help add value to the people trying to use AI.

Dan Morris

>> Yep. So we talked to marketers across all industries, really across the globe, and there's some common themes that come up a lot. Right? We want to be hyper-personalizing experiences across all channels and touch points, consistent brand tone, brand voice. We want to be smarter with our campaigns, precision, more science. We need to be doubling down on self-service. We need to be leveraging and scaling AI, and while the North Star is clear, there tends to be challenges that are in the way. Right? So data is siloed, whether it's because of organizational boundaries, or maybe it's external because data's outside in external systems. Because of that, the idea of self-service becomes kind of elusive. Right?

>> Yeah.

Dan Morris

>> Marketers are dependent on tech teams. Tech teams aren't able to work on other things, and then your campaigns become inefficient, as well. And so what you ultimately need is a platform that allows you to move with speed and agility, and so that's where Data Intelligence for Marketing comes in. Right? So it gives you, really, that ability to unify all of your data, your AI, your consent, so you can build out unified views and personalized experiences.

>> So, I mean, all the great conversations with Databricks, look at all our headline customers, banks, big companies, big deployments, but really is transformative. If you think about marketing departments, marketing organizations, which try to drive sales demand and demand and sales for the company, they have tons of data. They had old martech stacks. Remember the old martech stack, that collage of zillion different vendors on it? I don't think goes away. I mean, some players go away, but it becomes abstracted. You're starting to see that data maybe look at, "Okay. A data lake could be better for me, because I don't yet not know what I want." Certainly better targeting, better personalization. These are low-hanging fruits. So the question to you is, what is the mindset of the CMO leaders and CXOs in kind of go-to-market teams where that's like, obviously, they want sales. Right? Everything's built to get more of business, which means customers. So obviously, customer focus. What are some of the things on their mind? Are they confused? Are they struggling? Is there a clear line of sight into a use case, a beachhead to land on? I mean, there seems to be a lot of different stakeholders, because what happens is everyone's like, "I'm the customer," internally, so you have to pour value in all the cups. What's your view on this? I mean, what's your reaction to what I just said? Do you agree? Comments?

Dan Morris

>> Yeah. So, I mean, we ultimately see Data Intelligence for Marketing as the combination of the Databricks Data Intelligence Platform and the marketing ecosystem. What I love about this is that it lets all personas get tools that are purpose-built for them, and what that ultimately means is we're aligning the office of the CMO with the office of the CTO with a single source of truth. That alone is what's bringing organizations together to move much quicker and with more agility.

>> What's some of the hot deployments, or integrations, or projects you guys have worked on? Again, I know Databricks. Have been following for years. You like to get in there, and then figure out the customer, and then identify the patterns.

Dan Morris

>> Yep.

>> Is it website traffic? Is it like ... Who designs the evaluation or the programming? What's it look like? What are some of the popular starting points, or how do people engage? What are the most popular areas now that are working?

Dan Morris

>> Sure. So there's really kind of three areas. Right? So one is around customer 360, so a lot of companies really trying to build out a better customer view to power everything. The next one would be around campaign management. We're seeing a lot around using AI to make those decisioning and really saying, "Here's some copy. Here's some creative. Help me figure out what works best for whom, when, and where." Then, the last piece would be around brand management and using that to really unlock insights and help kind of grow brand equity and protect it, as well.

>> I'd imagine the campaign stuff is pretty awesome.

Dan Morris

>> Yes.

>> I mean, can you share more on that? Because that's like, feels right, because you can feed it.

Dan Morris

>> Yep.

>> You can ground it with some data.

Dan Morris

>> Yeah. It's-

>> What are some examples there? Share.

Dan Morris

>> So PetSmart is an example. They actually presented at Data + AI Summit, public story, as well. They have a grooming business as part of their store, and it's an area where they obviously are trying to drive business. And so for them, they want to drive that business, and they know, "If I know people are going into the store and buying dog food, but they're not getting grooming, then I know that that's an opportunity." And so that's an area where they've leveraged this technology to drive really significant increases in terms of getting new people or existing customers onto their grooming business.

>> One of the things I've noticed, just kind of best 15s with the queue, and it affects a lot of marketing departments, innovative ones and slower-moving ones, you guys could help both kind of the slow laggers who didn't really invest a lot in marketing technology, others who have been more progressive. So I think it's a nice fit there.

Dan Morris

>> Yeah.

>> I've also noticed that they get stuck on, where's the data, a lot of privacy. That fits nicely into some of the Unity Catalog things. What are some of the data sources? Is there some commonality? Not every enterprise is the same. They do things differently, obviously. A lot of people do email marketing, do other things, but those are mechanisms. But is there data that you see consistently that are pillars?

Dan Morris

>> Yeah. Absolutely.

>> What's your observation on that?

Dan Morris

>> So everything really starts with the customer. Right? So it starts with, what's the information that may have been provided you in terms of first-party data, such as their email address? Then, you have behavioral data. So if you're a digital, a website, you have clickstream data that's coming in that you understand their behaviors. Then, from there, there's things like psychographic data that you can append to the profile, and all of this really builds out that view over time.

>> On websites, not that I'm, again, highly motivated to say ... I'll just be transparent. I'm interested from our own personal perspective. I got tons of IP interests. I got a data dump. I have more log data, years. I'd love to ... Can you guys help me with that? I mean, is that one of the ... I guess my question is, what are the out-of-the-box things that you have out of the box, and what can be done by the customer? So say I dump in the market intelligence, my data, is there an interface for that? Am I thinking about it the right way?

Dan Morris

>> Yeah. We provide tools, really, to work with your data across the entire lifecycle. I think probably one of the most exciting things is you take that data, you bring it into Databricks, you pop open Genie, which is a natural language interface, and now, I could start asking questions of my data using just English. You're now able to answer your toughest questions in literally seconds. And so we're seeing that really being game-changing from everything from, "How's my campaign performing?" to, "How do I best optimize ?"

>> "Find me a video that matches the copy."

Dan Morris

>> Exactly.

>> Maybe that's something. Yeah. So what's the most important thing you work on right now? Is it education? Is it more aligning? Is it change management? What are you running into from a customer's psychographic mindset? What are they thinking, "Help me. I'm drowning," or what are they ... Are they scratching their heads, saying, "Tell me more"? Are they exploring? Where are they in their journey?

Dan Morris

>> I would say obviously, there's a spectrum of use cases, but I think the two biggest areas are, one, really getting your customer data in order, especially just because of everything going on in the privacy space, and then, two, how do we better harness AI, whether it's to drive efficiency, whether it's to hyper-personalize experiences? Those are the two hotbeds that we're seeing.

>> All right. What's your goals in the next half a year? We're at halftime, right now, of the year. Jonathan said vibe coding was so 2024. Now, it's data AI engineering. So we're kind of in a new, kind of a scalable kind of reliable era now, where we got the enthusiasm side, but now, we're coming into practical, "Show me stability. Show me some reliability." What's your plans? Are you on that same track?

Dan Morris

>> Yeah. I mean, I think, really, I think what we're seeing with AI, gen AI is we're actually kind of seeing the rise of a 10X marketer. Now, if you look at things like AI, Bricks, there's an opportunity to really explode that in terms of the 10X marketer. So we really want to empower the marketers out there.

>> Do the CMOs understand the 10X engineer concept? Does that translate over? Again, when you say 10X, that's a step function.

Dan Morris

>> Yeah.

>> Are they like a deer in the headlights? Are they leaning in? What's it like for them, and do they have a path? What would be the path? "How do you make me a 10X marketer?" would be my question.

Dan Morris

>> So number one, it starts with the data. It really does. You really need to start unifying your data and having that unified data foundation, and everything hinges off of that. Once you have that, you could have your self-service, which frees up your marketers to work on other things. It unlocks insights. It gives you smarter campaigns. So it really fundamentally starts with the data.

>> What are some of the things that hold people back? We hear, again, with AI, you're starting to see the patterns, the grind, or the grunt work, or the toil, whatever word people use. There's always the blocking and tackling in marketing, specifically. What do you see getting taken away here from marketers?

Dan Morris

>> So I think it's actually enabling marketers to move a lot quicker. There are things where if you go back to the decisioning piece, you need more creative. To get more creative, you need to start having better metadata. And so it's actually shifting a little bit of the work that marketers are focusing on, but it's also helping kind of level.

>> Well, Dan, we definitely want to follow the work you're doing, because we love. We think marketing and sales, obviously, is really one of the most growing areas. Obviously, when you see people jumping into gen AI specifically, not data ... I think data really is everywhere else. I think that's solid. You guys are there, but the sales and marketing, everyone are, they're definitely getting their muscle going there.

Dan Morris

>> Yep.

>> You're also closing out the show. We heard the announcements. So I have to ask you, what's your assessment of the show? What's your takeaway? Obviously, you're internal, a little bit biased, because you work for Databricks. But I gave you guys an A overall on the keynote. It's hard to get an A+, but that's still a great grade. All the products here, the platform evolution's continuing to go.

Dan Morris

>> Yep.

>> What's your big takeaway from the keynote today if you had to kind of zoom out and write up the top story here?

Dan Morris

>> Yeah. So, I mean, I've worked at Databricks for four and a half years. I was a customer for five years before that. The trajectory of the company is amazing. I think everything that's getting announced, again, with AI Bricks and apps, there's amazing kind of trajectory of the company that's really going to help kind of supercharge what marketers are able to do.

>> All right. Dan, thank you for coming on theCUBE. Wrapping up our day here with Dan, and talk about the data marketing intelligence. This is the marketing opportunities out there, but the data and the speed that generative AI is going to allow is a 10X marketer, 10X engineer, 10X everything. I'd say 100X on the agents as they kick in. But Agent Brick is the big story. Apps are going to be generated on the fly. More engineering at the AI level. A lot of scale coming. Databricks Summit. Wrapping up theCUBE, I'm John Furrier with theCUBE. Thanks for watching.