Databricks Data + AI Summit 2026 | Simon Davies, Databricks & Anish Shah, Jio Platforms

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More from Databricks Data + AI Summit 2026

Simon Davies

SVP & GM, APJ

Databricks

Anish Shah

COO

Jio Platforms

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Simon Davies, Databricks & Anish Shah, Jio Platforms

Simon Davies

SVP & GM, APJ Databricks

Anish Shah

COO Jio Platforms

In this interview from Databricks Data + AI Summit 2026, Simon Davies, senior vice president and general manager of APJ at Databricks, joins Anish Shah, chief operating officer of Jio Platforms, to talk with theCUBE's John Furrier about how a data foundation built at massive scale is accelerating the shift from fragmented enterprise data to production-ready AI. Shah details how Jio Platforms — spanning telecom, retail, media and energy for 190 million users — migrated 25 petabytes of data into Databricks in just six months, consolidating more than 12,000 tabl... Read more

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How does Reliance manage and process data at scale, and what has been its experience using Databricks? add

How has integrating assets across telecom, media, retail and energy, and using a unified data platform (e.g., Databricks), enabled cross‑pollination and delivered customer value? add

How are you using Genie to enable business users to access and build use cases from your data? add

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Simon Davies, Databricks & Anish Shah, Jio Platforms

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John Furrier

>> Watching the evolution and escape velocity of a very successful company, they made a big bet on data and open source. It's paying off. This next interview is really going to talk about the scale benefits of leveraging the right architecture at the right time. We've got two great guests. Simon Davies, who's the SVP and GM of APJ for Databricks. Thanks for coming on.

Simon Davies

>> Great to be here.

John Furrier

>> Territory. Anish Shah, president and CEO of Jio Platforms. They're large, huge 190 million user base. They got telecom, they got digital media, full scale production. Gentlemen, thank you for coming on theCUBE.

Anish Shah

>> Thank you. Thank you, John.

John Furrier

>> Packed house. 31,000 people. I was going to bust out at the seams here.

Simon Davies

>> It's a huge conference, isn't it? The energy here is pretty amazing.

John Furrier

>> It's amazing. It gets loud. We'll keep it as tight as possible. I want to talk about scale because the show here kind of puts the final piece of the puzzle together for Databricks. You got the transactional piece. So it's all kind of coming together. Now people are putting AI into their business. They're injecting intelligence. That comes from the data. So we're hearing all that here. So when you look at the data piece, what's that mean for you guys? Give us some examples of what you're doing with Databricks, but talk about what that translates into scale and how you are operating your business.

Anish Shah

>> Sure. I think as you introduce, Reliance is a big conglomerate. We have many large businesses, telecom, media, energy, retail, and they're pretty large. And again, all of them generate a lot of data, especially telecom and retail, billions of data points which we generate. So obviously for us, anything which we want to do with data, we have to do it at scale. And I think since the time we have been working with Databricks, a lot of these things we have now start. For example, we are the fastest company moving 25 petabyte of data into Databricks in just six months. More than 12,000 tables we have just moved. And we have more than 1,500 jobs running to get all these things done. So when you talk about data at scale, I think Databricks proves it very clearly that it can run at scale.

John Furrier

>> What's great about what you guys are doing is you have all the secret pieces. You got the network, you got the energy, and you got the data.

Anish Shah

>> Yes.

John Furrier

>> And scale.

Anish Shah

>> And scale.

John Furrier

>> So when you look at all the AI , NVIDIA, supercomputing, they all talk about the five layer cake, energy and networking and empower.

Anish Shah

>> Yes.

John Furrier

>> So when you get to all that, how does that translate when the data comes together? What are some of the things you guys see as opportunities that were not possible in the past?

Anish Shah

>> Yeah, I think one of the greatest thing which we have learned and by doing foundation, which I mean, Databricks helps you to build that solid, strong foundation. And this foundation is the only thing which is required if you want to do anything with AI. Contextualizing anything in general, you can't do it if you don't have AI. And for that, you need data. And I think that's the solid foundation you get here. And as you rightly said, whether it is energy, whether it is telecom, you need to have that strong foundation.

John Furrier

>> It's an AI factory, the whole system.

Anish Shah

>> Exactly. Yes.

John Furrier

>> Simon, talk about Databricks' international growth because we're in a global economy right now. Sovereignty is big, it's been around for cloud, data protection, data privacy, but now you have economies running. Businesses, large, medium, and small, getting superpowers as they start to protect their intelligence of their business. We saw that in the transactional piece, the final piece of the puzzle. So this is going to be a really good opportunity for business.

Simon Davies

>> Yeah, absolutely. I mean, we've seen some pretty astounding growth in Asia Pacific. About 85% growth year on year last year. We're growing our team a lot. And in order to support our customers on that journey, we're really excited to announce recently we're targeting to train over 700,000 people across the region, helping to skill up in data and AI. Because as you said-

John Furrier

>> You said 100,000?

Simon Davies

>> 700,000. As you said, that really is the fuel that businesses are looking to unlock new capabilities.

John Furrier

>> What's your goals on staffing? What's the geographical spread? Just share the key areas you're focused on.

Simon Davies

>> Yeah, we're spread right across the region. We've got a big team in India. Japan is a very big market for us. I've got a strong team in Australia, New Zealand, great team in ASEAN, greater China. And then we see some really interesting use cases, particularly around the transactional stuff that you talked about, the lake based solution. Krafton, a gaming company out of Korea, is doing some really amazing user experience stuff. Super cool. Super interesting to see. So we see innovation right across the region.

John Furrier

>> I mean, gaming is definitely innovative in Asia Pacific, but the semiconductors as well. What's the overall forecast for the AI side of it? Where's the market opportunity for you guys?

Simon Davies

>> I think it's across the board. I think we're still a little bit earlier in the journey. We're seeing a lot of organizations, to Anish's point, about really focusing on how do they build that data foundation at this stage, but also there's a lot that really want to leapfrog much more into leveraging AI for core processes and what that means for them. So, awesome. Yeah.

John Furrier

>> Anish, talk about what's changed in the past year for you business-wise? What you were optimizing for and this shift we're seeing? When was the big aha moment? Was it last year, two years ago? And what's changed in the past year for you?

Anish Shah

>> I think the speed of change is something which is now happening very fast and that's something which ... And this is seen across all our businesses. Look at telecom, look at retail, look at energy. Just because we are now able to see things in real time, we are able to analyze things in real time, we are able to talk to our data, which was never possible in past. I think that's the change which people are able to not even fathom to say, "How can I now leverage this to do more?" And people are getting innovative ideas to say, "How do I do things more?"

Simon Davies

>> Yeah, yeah.

John Furrier

>> It's been a crossover lift between all that integration of assets, because you have a lot of asset cross pollination now that you got the data set up, digital media, energy and telecom. Let's just take telecom and media, which I know more than energy, but the crossover benefits of subscribers that were buying bandwidth are that prices going down, performance is going up, but this business in the digital side, that's a real interesting combo.

Anish Shah

>> Oh, yes. I think this is something which has been possible because of unified platform which we can build on Databricks. Because now we can get data points coming from retail, coming from media, coming from telecom, and you are now able to unify things for the customer and giving real value to the customer, which was not possible because earlier everything was in silos. Now that's the unified platform which we are able to do.

John Furrier

>> You were talking earlier about you have your own AI system prior to the hyperscalers.

Anish Shah

>> Yes.

John Furrier

>> Talk about that architectural decision, why you chose that, and the benefits you're seeing from that.

Anish Shah

>> I think one of the reason why we are doing it, because just the way we have built all this business, we are also getting into the business of intelligence. We want to build intelligence, consumer intelligence services, enterprise intelligence services. These are not platforms but these are actual services which we want to deliver to consumers and enterprise. Now of course to do that, you need to have all the stack from energy to compute to models to data, and then on top of it, you need to have agentic frameworks delivering those services.

John Furrier

>> Don't forget the spectrum.

Anish Shah

>> Of course. The spectrum is-

John Furrier

>> I mean, you got the wireless layer. I could be an enterprise customer-

Anish Shah

>> Activity, yes....

John Furrier

>> in one hour.

Anish Shah

>> Yes.

John Furrier

>> In the next hour, I could be gaming.

Anish Shah

>> Of course.

John Furrier

>> And you got to have a very intelligent access-

Anish Shah

>> Smart intelligent access to that. Yes. It's smart intelligent access. And I think with having all these layers, we believe that we can now get into the intelligence business. Now to get into the intelligence business, if you don't have this entire stack, then you can't get it done. So that's the reason why we have been involved in building this kind of architecture.

John Furrier

>> I mean, it's funny. You have pioneers like yourself, you're in the frontier. Companies like Uber did it last generation.

Anish Shah

>> Yes.

John Furrier

>> That was a unicorn. They were using columnar databases to the level no one saw. But then that became a template for everyone else. We hear DraftKings earlier. We had Addepar on , now you're here. The pattern is clear. There's an integration going on. How does a company build intelligence? Because what we're seeing here is that your data is your business brain.

Anish Shah

>> Yes.

John Furrier

>> What advice, how would you prescribe people watching what you're doing? Because that's the holy rail. People are trying to get to, "Hey, I want to inject intelligence in my business and then make intelligence my business model." That's kind of the trend here.

Anish Shah

>> I think it's very simple if you ask me. First is you need to go by foundation layer. You have to create layer by layer architecture. And at the foundation, you need to have your data architecture the best because anything you want to do agentic, anything you want to do intelligence without context, without data, it will just not work. And that is the foundation layer you have to build. On top of it, bring all your processes, bring all your systems, bring all your workflows, and then get it onto the agentic flow.

John Furrier

>> So I have to ask you, Simon, you can chime in too on your team. Your team must be going to town on the agents. They must love it.

Anish Shah

>> Yeah.

John Furrier

>> You got token factory, basically on premise.

Anish Shah

>> On-premise.

John Furrier

>> It's candy for the developers. And builders, not just developers.

Anish Shah

>> That's right.

John Furrier

>> People don't have to be a developer seeing that here. What's it been like for the organization? Is it faster innovation, happier people? What's been the impact? Obviously the engagement's high.

Anish Shah

>> Faster innovation, yes, because that's something which is really helping us to move it. But I think more importantly, we are able to now see our business end-to-end results. We are able to do it in every area, whether it is in operations, whether it is in our finance, whether it is in business services. Everywhere we are able to see this transparency, end-to-end visibility. That is helping us to really scaling up the businesses. That's really important.

Simon Davies

>> And you guys have done a great job deploying Genie-

Anish Shah

>> Oh, yes....

Simon Davies

>> across your business users, putting data not just in the hands of the data scientists and data engineers, bringing it to the business users.

John Furrier

>> Tell me how you're using Genie, because that's hard.

Anish Shah

>> Oh yeah. In fact, we were very first users the moment Genie came and it has been given to our business users. Innovatively, business users have come back with so many other use cases which our developers-

Simon Davies

>> We haven't even thought of, right?...

Anish Shah

>> have never thought about. And today I think we are able to now roll out so many use cases on Genie, not by our developers, by the business users themselves.

John Furrier

>> I'm getting the impression you're kind of humble. Simon, chime in. He's being humble. Explain what he's doing, because I think this is a real great example.

Simon Davies

>> Yeah. So they're basically making their business data available through the native language interface that Genie provides to let them query the data. Making it accessible to everybody, letting them take the use cases they want to build out across supply chain, finance, making decisions around carriers, making decisions around how you do the 5G towers, all of that data coming into Databricks and then being accessible in a way that's never been done before. And the Reliance team, you're right, he's being quite humble. They're kind of one of the best APAC customers we've got, just demonstrating the way that can be possible.

John Furrier

>> I love the vertical integration. I love that the full stack, even through the spectrum, I see a lot of opportunity there. Final question for you guys. What are you optimizing for? Anish, we'll start with you. What's your goals now that you get the table set? What's next?

Anish Shah

>> I think this was a very important step for us to reach to the next level. And for us now, we want to really build the intelligence business and we want to bring intelligence to every business. So whether it is retail, we are saying we want autonomous retail. We want autonomous telecom. We want autonomous energy services. We want autonomous financial services. So obviously a lot of things on agentic is what we want to bring. But more importantly, we are trying to build intelligence business for our consumers and enterprise. That's something which is very, very exciting.

John Furrier

>> Simon, you got a lot of growth ahead of you. What's your optimization plan? What's your focus?

Simon Davies

>> Well, I think there's a couple of engines for us that'll drive it. Certainly partnerships with organizations like Reliance. We're excited where we're bringing Databricks to the Jio Azure region for India, which will help us from a sovereign point of view, being able to support public sector much more. And then we're seeing just a lot of really interesting use cases. We've got organizations like the National Australia Bank down and ANZ that's really helping us push the boundaries of the Lakewatch, the new security capability that's coming there, as they unlock more and more value from their data. So for us, it's really just about how do we activate that? How do we support customers on that journey? How do we help economies build around the opportunity that data and AI will create?

John Furrier

>> Yeah, we had Patrick right on earlier, a great example. They were on last year. Well, congratulations and love. We'll keep following what you're doing. Great template.

Simon Davies

>> Yeah.

Anish Shah

>> Thank you. Thank you so much.

John Furrier

>> Congratulations. I'm John Furrier, host of theCUBE here live on the show floor of Databricks Data + AI Summit. More action coming after this short break. Stay with us.