Activate Trusted Data Everywhere | Data Cloud Keynote, Dreamforce 2025

We had a lot of fragmentation.

Puddles of customer information everywhere.

Sixteen different systems, none of it connected.

That problem is only getting worse. What's at risk is that we focus on the wrong things. Customer focus comes in jeopardy.

We have to unlock that somehow.

Using data Cloud. The data is available, the data is clean, the data can be trusted.

Bring it into one place.

Delivering much richer personalized content to delight.

You in the moment.

What used to be a series of.

Spaghetti integrations transformed into a single source.

Of truth for customers. And that in turn is the data that's activated into marketing cloud.

All together unified.

That's where we see the biggest value.

That's exactly what we need to make Generative AI successful with Salesforce.

We can move at a speed we've never been able to move before.

You simply activate your data cloud to give that agent access to real time.

Data and serving it up to Salesforce so that we can take action on it.

Data Cloud delivers and that's critical to give them that personalized experience. I can't think of a technology before that that would really accomplish that to that level.

That for me is really, really powerful.

Please welcome executive vice president and general.

Manager Salesforce Rahul Aradkar.

Okay, thank you, thank you. What an inspiring video that was. Every time I see it, it inspires me. I was here last year, about a year back, delivering the first Data Cloud keynote. Thanks to our customers, we have had an incredible year and thanks to our partners who have been helping our customers deliver the outcomes. Now, how about the data blazers? We started that community a year back. Now we have 70,000 of them. We have a few of them right here sitting amongst us. Yes, thank you. The employees who are watching this was sitting here. Your creativity, your dedication and your perseverance is the reason why we are here today. We are seeing success across every geo, every industry and every segment. Frankly, it's blown us away. It's very humbling. And your outcomes have been phenomenal. There are a lot of numbers here. We share a lot of numbers in terms of usage, numbers in trillions, numbers in quadrillions. But those really, what's behind those numbers are real customer stories. I was at the customer advisory board yesterday and a small business customer who is a physician, Romy Chopra, he's here with us or think he's here with us here today. Romi Chopra is a physician small business customer using data cloud and delivering value within weeks for his patients and saving over 1.5 million with a small footprint of data cloud. Or take the other end of the Spectrum somebody like indeed completely transforming their business to being an agentic enterprise. So it's the entire range that we have seen from a success standpoint. Now, the creativity and the experimentation and the outcomes that our customers have provided has been really behind what we do with innovation. It's been our fuel that drives innovation. Let me take an example. SiriusXM helped us learn about streaming data and what we need to do with streaming data. The customers in Japan told us about IBM mainframe data being zero copied into data cloud. Now, IBM mainframe data with iceberg standards is zero copy in data cloud. That's correct. You heard it right. Even their DB2 data, then there are databases telling us about unstructured data. You're going to hear a lot of that in the next few minutes about what we're doing with unstructured data. Now, for those of you who are using data cloud and who already are driving outcomes, there's a lot of innovation coming. And for those of you who are just getting started or want to get started and want to learn what's this all about? How does it work? What difference does it make? Let's unpack that together. You see, we have been. Data has always been the foundation for everything. Customer. Knowing your customers, engaging with your customers. We have built incredible systems over the years to store data, to ingest data, to analyze it, to drive insights, to know more about your customers, to engage with your customers. But here's the problem. All that knowledge is trapped, is siloed, is disconnected. And the paradox is that this very disconnected data is actually interconnected. Let me take an example, real story. My daughter and I were buying a car recently and we were researching the vehicle and we bought the car. And after that she gets incessant reach outs for the same car. What's the point in reaching out to her with the same car? It's unlikely she's going to buy the car again within a month. I get very expensive ads about the same car. I'm not buying another car with her within a week. So that's wasted media spend. That's wasted data that is sitting around, that is for that brand. It's wasted data and wasted media spent. So between the time that you engage with customers and what data you need, you've built a lot of pipelines. Those pipelines are brittle and they're not available in the moment that is needed for your customers. So what if the gap between knowing your customers and actioning on it disappeared? As my friend Rafa from Bradesco said yesterday at the cab, it is effectively connecting data to the place where it's needed at the time at which it's needed to deliver value across all the fragmented data. That is the vision that we have been living at Salesforce. That's the vision we have been partnering with you. That's the future we believe in and that's the future we are going towards, given that we are introducing Data360. Data360 is the new Data Cloud. It's the same product you have come to love and use, has a new name with a ton more innovation that is coming. So Data Cloud, simply put, is an evolution. Data360 is an evolution of Data Cloud. It is activating all your trusted data everywhere. We have talked about activation repeatedly. Pretty much everybody in the cab yesterday told us it's all about activation. Now what does that mean? It's simply two things. It's personalized experiences across all touch points, all modalities and all channels. Perhaps the most interesting thing you're going to hear for the rest of the conference is this word known as context. Providing context across all your fragmented data in a meaningful manner. In the moment that AI agents need. That agent that was trying to reach out to my daughter and me had no context. Now, going forward with the innovations that we're going to talk to you about today, that data will have, that interaction will have context. You came to this conference, you're hearing a lot about what could be, what should be with the data and AI transformation. What we're focused on for the next 40 minutes is what already is. There are three broadly used use cases here. Number one is we've seen significant focus on and our customers delivering value with digital engagement and delivering personalized real time experiences with it. The second one is what I refer to. Using context to deliver outcomes that AI agents can deliver on your behalf with humans and AI working together. The third one is binding the customer 360. So you have integrated experiences across the entire 360. So for the next 40 minutes we are going to unpack all of these three. To do that, I want to get started with the first one, delivering personalized real time experiences. I want to invite my colleague, a leader in Data Cloud Chandrika, to the stage.

Thank you, Rahul. I'm super excited to be here to Talk about how Data360 is enabling our customers to deliver personalized real time experiences. Now, across the industry, marketers are using Data360 to connect to data across their ecosystem, to unify and harmonize all that data. Know their customers and activate that data to reach their customers at the right moment with the right message. Who better to showcase this use case than Meta? Meta is actually using Data360 as their data platform. They're using that to power their B2B scenarios. They're connecting to all of their fragmented data across their ecosystem, unifying all of that to deliver personalized experiences for to their customers, advertisers in a consistent and connected fashion. Now let's hear how they're doing it and share more. In order to do that, I'd like to invite Nick Harris and Corbin Tho to stage. Welcome, Nick. Welcome Corbin. Thanks for being here. Now, before we begin, could you please introduce yourselves to the audience?

Thanks, Chandrika. Nick Harris, glad to be here. Lead a data analytics team at Meta.

Hey everyone, Excited to be here. Corbin Tho, I am the head of Martech platforms for our scaled business marketing group.

Now, before we begin, maybe you can start by talking a little bit about Meta's vision in the B2B space and how does that relate to data?

Sure.

So one of the main things that we're trying to do in the B2B marketing space is ensure that advertisers are clients like you all are able to reach your customers on our platforms at the right time. That starts with educating you about how to use our products, giving you the best, best practices on that, as well as ensuring that you know what to do so that you're reaching your customers to get the return that you want from advertising with us.

You know, a company your size has a vast swath of data, planet scale data. Right. And a lot of complexity that comes with that kind of handling, that kind of data. Can you share a little bit more about how you were dealing with that complexity before you took on the journey to go on with Data360?

Yeah, certainly. So we were effectively operating on two different martech stacks. Our small business team was operating on one set of tools. Our global business team was operating on a completely separate set of tools. And the result of that was fragmentation, not just within our marketing org, but also with product and sales as well. So building those integrations was very challenging. Passing that data back and forth was very messy. And this just resulted in a very inconsistent experience for our advertisers.

And that was the key right there. As Rahul mentioned, as customers are migrating from one part of our marketing funnel to another, or one part of our segment to another, we were losing the context because that lived in a different data ecosystem and we couldn't serve that customer with intelligence. Right when they needed it the most.

You know, this is so similar to everything that we heard at the CAB yesterday. Customer Advisory Board from many other enterprise customers as well. Tell us how Data360 helps solve this problem for you.

Yeah, certainly. So I alluded to already two different Martech stacks, but now we have a single platform where we can build a consistent connected experience for our advertisers. Not just that, we can actually see our advertisers as they start in the acquisition tier and as they graduate all the way up into our growth tier. And as we are bringing in signals and context into the platform, we're able to act on that data in a much more rapid fashion.

And as Corbin mentioned, we're trying to make the experience between marketing and sales a lot closer. And being able to provide those sales agents with qualified leads has been key to making this product successful for us.

That's impressive. I'm sure folks in the audience are wondering about the same question I am. What were the outcomes from using data 360? What were some business metrics you were able to achieve?

Yeah, the results, absolutely. We moved off six Martech platforms down into three and so we were able to save on operating and licensing expenses. And with that added efficiency we were able to deliver 20 to 30 plus campaigns quarter over quarter. Then on the growth side, we were able to target more specific audiences to drive some of that revenue. And then for the first time we were actually able to attribute revenue to our mid market audience, which was a major accomplishment for us this year.

And it's not just about the efficiencies or opportunities that we had as a company. It's also about our advertisers ensuring that they're able to reach their customers better as well. And so we're seeing that as a result of these actions as well.

Those are impressive numbers. It's been an amazing journey partnering with you. We've learned a lot along the way. I know you guys are thinking about the next set of use cases and how you're going to take B2B forward with AI. And we're looking forward to continuing that journey with you guys. Thank you so much for being on the stage here and sharing your insights. Thank you, Nick. Thank you, Corbin. Give it up for Nick and Corbin. Now folks, what you just heard is a powerful story of how the data 360 can be used to activate your data. And that's what Meta did. You know, that's not unlike how many of our customers are doing using data360 FedEx Air India, Heathrow, Elevance, Wyndham, all of them. That's the reason why Data360 is the number one CDP for marketers. It's also recognized by our industry analysts as the leading vendor in the B2B and B2C space. At the heart of it all is connectivity. You can connect to any data anywhere, unlock that data, whether you're ingesting that data or whether you're federating with that data through Zero Copy and make that available for your marketing scenarios. You can unify and harmonize all that data in data360 and personalize and create real time experiences for your customers anywhere. Whether you're using Customer360, sales, service, marketing, commerce, if you're driving AI and agentic scenarios, or, or if you're doing BI and analytics as well. And at the heart of it all is governance and security. You can tag your metadata, you can classify your metadata, and you can build policies using our unified policy framework. Whether it's access policies, security policies, masking policies, or you want to just do retention policies across the board, consistently across your metadata. So you can have confidence in targeting customers with precision and comprehension with your unified data. And of course, with our activation stack, you can reach your customers touch points anywhere they are with confidence across both paid and owned media. Now folks, that's not all. Now, as we talked to Meta and some of our other big customers, we realized that your customers don't just live just within the walls of your business. In fact, they live across your entire partner network, whether it's retailers, healthcare services, financial institutions, across all sorts of data systems. Right now that's a pain point. Wouldn't it be nice if you could collaborate across your entire partner network, across the vast swath of data that lives in their ecosystems, such that you can safeguard the sensitive data in a privacy safe way and discover new hidden audiences and target those audiences for additional campaigns, Grow your business, have happy customers. We think that's the next innovation. Today we're announcing data 360 clean rooms. Data 360 Clean Rooms is designed to give you a way to collaborate safely with your partners using that shared data. Now, it's all founded on the Zero Copy foundation, which means you can untrap, unlock all that trapped data that's located everywhere in your network and your partner network and make that available for collaboration and ensure that sensitive data is not shared. You can discover hidden audiences. This is all interoperable across many clouds, so you can access data, discover hidden audiences everywhere and anywhere. Of course, the insight that you gain from unlocking all of that, the aggregated anonymized insights can be turned into instant action across your entire ecosystem, across the salesforce's entire ecosystem, across customer 360, across AI and agent force, as well as BI and analytics. Now let's actually take an instance, a use case to talk through this. For all of you to be in this room here, you all traveled via different airlines, you're staying all at different hotels, Right? And if you're like me, you have preferred airlines, preferred hotels, and you're booking them separately. Of course, you're also tracking loyalty points across all of these separately. That's a big pain point, certainly for me. I'm sure it is all for you as well. Now, wouldn't it be nice if airlines and hotels could collaborate across all of the vast swath of data they have spread across their entire ecosystem and be able to find these hidden audiences across both of their systems, across both of their organizations in a secure fashion? Let's actually get into a demo now. I'm going to invite my demo partners here, April and David, to help me with the demo. April is a marketer at a fictitious hotel, Polonia Hotels, and she wants to collaborate with me, a media representative at Astro Airlines. Now she wants to be able to leverage my data such that she can pinpoint audiences, an overlap segment, if you will, in a clean room environment. So she can target that newfound segment, if you will, using my media network, feedback screens, mobile phones, emails potentially, and even signage at the gates as well. Now let's see how we do this. We're going to go into the clean room environment, April and I, and she's going to bring her high value customer. She cares about this segment deeply and she wants to map that with all the segments IaaS as Astro Airlines offers in the secure clean room environment. It's a neutral environment. Right. And so she queries high value customers against all of my segments to create this overlap segment. Let's take a look at the results. April, can you share with us and describe to us what this looks like, what this means?

Yeah, so we actually collaborate with a lot of different partners and this is our collaboration with you. I have all of my customer segments over here on the left and I have all of your customer segments that match on the right and I can just query those high value guests and see that international travelers and business travelers, that is where we're going to get the key prospective reach and get all of that information to you guys. Not just that though, is we are all integrated here and I can share this to Slack so that we can continue to collaborate to make the best campaign moving forward.

That's amazing to bring it all together to the pain point we just talked about earlier. First and foremost, this is a secure neutral clean room environment. I as Astro Airlines is a provider of data and I can securely safely bring the data that I choose to and pick the partner that I want to share this with. So these are anonymized aggregated segments I'm bringing to the table and April is interested in specifically finding pinpointed audiences prospects and combine that with my shared audiences to create this overlapping segment. Now it's a win win, right? April as a marketer can target the specific newly found audiences. I as Astro Airlines gets ad spend from Polonia and you all or we all as customers are able to leverage the two businesses collaborating together. Now we don't have to separately track them and map our identities to them. So that folks is the power of data 360 clean rooms. Now you might all be wondering how is our data 360 clean room any different than any of the solutions that are available in the market today? Database vendors, data lakehouse vendors offer clean room solutions, right? Let me tell you first and foremost with data360 clean rooms you are not moving raw tables. You're not having to deal with raw tables and have to have to then figure out what that means. Raw tables are not here. We're actually dealing with harmonized unified context rich context, aggregated, anonymized, chosen by the provider to share in the clean room secure clean room environment. Once you find that aggregated insight, you can have actionability right here in the flow of work within Salesforce. You can use your customer360 sales service, commerce marketing. You can use AI and agent force or you can use BI and analytics to immediately action on that newfound insight in the flow of your work as a business user. And of course governance and security is fully baked in. You can have policy controls over that data. You can choose who you want to share your data with and what query that organization that partner can run and on what columns you can set security policies over all of that and compliance is fully met in the secure environment. All of this is built on the Zero Copy foundation which means you can get at that trap data and unlock that trap data and make that available in the secure clean room environment. Now we're going to move on to the next innovation to talk about how Data360 is powering smarter more trusted AI agents with context. To do that, I'd like to invite my partner and friend and an Amazing leader in Data 360 marketing, Erica Early. Erica, take it away.

Thank you, Chandrika. Hello, databasers. I'm so happy to be here. I'm very grateful to learn about all the phenomenal innovation from many of our customers, just like Meta. And I've also been learning a lot from many of our customers who are doing Agent 4 solutions. And as someone that deeply loves and understands data and AI, I can tell you that a lot of the innovation that you're going to be seeing here today and throughout this event is going to completely transform the way that you drive trust and accuracy with your AI and agents. Now, we are in a great time and this is a time of AI. This is the era of innovation. This is the era where data is definitely a place where you can drive a lot. One of the things that I wanted to share today is no matter what kind of data you have, whether it's structured or unstructured data, you can process all that. And what really matters is a semantic understanding of all your data. But something that is interesting that's happening in the industry is a lot of our customers are telling us that it's hard to process data on AI. And MIT is saying that about 95% of Genai pilots are feeling. Why do you think it's that this is happening? Because agents need context to take action. And we've done a lot of advancements with unstructured data. You can process files like PDFs, images and videos, but there is a very interesting type of data, of unstructured, complex data that it's hard to process. The reason why this is interesting is because there's a lot of deep domain knowledge. And to truly drive understanding and be able to unify all your data, you need to understand domain knowledge so that you can drive trusted AI and insights. I'll give you a few examples. Imagine you have documents that have flowcharts or row tables or graphs. It's really hard to parse for AI. It's a hard problem, but there's a lot of knowledge in here and you need it to drive insights. Common AI models. If you use a common retrieval, augmented generation model or a large language model, it's going to be hard for them to process that. In fact, you might get about 30 to 40% accuracy. The reason why is they cannot really parse and understand this information. It's really hard for agents to see that. This is why today we're very excited to Announce that we're advancing our unstructured Data capabilities in Data 360 with intelligent context, you have now the easiest and fastest way to drive AI insights and trust and accuracy. You can process complex documents. The best part, you can do that with governance and with security. Think about this. You would not use your important information in a public AI tool. And this is why it matters. But what better way to talk about this than with a live demo? So let's talk about Cumulus Health. They are a leader in medicine, in healthcare and technology, and they have many, many patients. And one of those patients is Harper. And Harper has diabetes and she's been wondering if she's eligible for a clinical trial. So for that, let's go see how an employee of this clinic can work with agents and try to help this patient. So I'm going to bring back April and David to do an amazing demo.

Awesome. So I am going to play the part of the employee that's getting Harper's question. And I'm right here in my Helm Health, and I can just use Agent Force to query and see if Harper Clark is eligible for the trial. Erica, something seems to be a little off here.

Yeah, I mean, this information that you're seeing on the screen is not really going to help this patient. It's not understanding the context and the information from her or from the decision making process to tell her she's eligible. How do you think we can fix this?

Well, we could spend all day parsing through this lovely document that's up here and Harper's medical history, but I'm not sure the whole audience here wants to watch us do that.

Yes, but I want to pause here to say, look, in this document, there's a lot of deep domain knowledge and it's very important so that we can drive accuracy. You need to know the age of the patient, you need to know their lab results, all the medical notes, all that information is stored somewhere. Now, all the logic is here. What happens if we can use this document and use intelligent context to understand if we can solve this problem and help the patient, and then the employee can use AI and agents.

One step ahead of you. I already have my agent over here. Let me just go ahead and quickly kick that off to remind everyone. This over here, that's the statement that we don't want. Right? And while the agent is over here thinking really hard and compiling the information using our structured data, our unstructured data built in with governance, let's take a peek under the covers. All I did was upload a PDF and then let the agent take all the default configuration. And what it has done is taken this entire document, it has generated the chunks for me, and I can even ask AgentForce, how do you qualify for tier one? And it's going to parse all that information for me so that I can check for accuracy and even reference back each of those individual chunks to make sure that the agent is set up the way that I want to. Let's go back over here. And we can see the agent has already answered and Harper is conditionally eligible for Tier two. So my job is done in seconds and I can just get that information to her so that she can get started with the paperwork.

Okay, that's awesome. What we just saw is, look, we have all these customer information. We have the patient information stored. We also have lots of unstructured notes from the doctor. We also have now this document that we're able to process and it's working. Intelligent context is amazing and it's going to be a lot of difference in how we drive trust and accuracy. This is why data360 is really what's driving everything that you need for trust and accuracy. You can unify and harmonize and govern your data. Something important on the demo is this data is very secure. It's secure for our patients. So we can do this on a trusted foundation of governance and trust that is built into our platform. Now I have another amazing customer, Salesforce. Salesforce runs on Data360 and we have many different use cases from marketing to Agent Force and even more customer 360 apps. To talk about all the amazing innovation and how we build this. It's a true honor to welcome on stage Michael Andrew, our Chief Data officer. Take it away, Michael.

All right, thanks so much. Hi, everybody. So I'm going to talk to you a little bit about Salesforce and how we use data 360 to solve our own problems. Across the whole experience, from marketing to agents to the customer360 and I'm our Chief Data officer. And what does that mean? Well, first of all, I love data. I'm obsessed with data. If you know me, you'll know this is true. And I wake up every day saying, how can I help Salesforce get a little bit better at data? And I think so many of you have that same dream. You're trying to help your companies get better with data. You're trying to help your companies get smarter, take better action, whether it's turning it into insights and analytics, forecasting to make better decisions. Or ultimately into action where you can turn that data into agents, turn that data into better experiences across your customer360, activate that data for audiences to grow your business or automate your business to be more efficient. And you want all of that to be trusted and governed. Now, at Salesforce, we haven't always had our act all the way together. Our own data was fragmented. We had hundreds of millions of profiles and systems. We have hundreds of petabytes of data. We have a massive data lake on Amazon. We have a massive, amazing enterprise data warehouse on Snowflake. Hundreds of thousands of applications. And that meant we couldn't always sample route leads to the right sales team. When you filed a case, we didn't always have all the information we needed to solve your problem. And as we started to think about agents, we realized that our context and knowledge was all over the place. That was not going to help us build the agentiq enterprise. What I'm so excited to share with you is we believe we're making significant strides solving this with Data360. So Salesforce now runs on Data360. We've taken those fragmented profiles. We now have 153 million unified profiles with 68 billion signals attached to them. So every time you're opening an email, visiting the website, talking to our sales team, filing a ticket, coming to an event like this, or acting in trailhead, we can now unify that to you. Then our knowledge already more than 700,000 documents are in vector indexes that power the agents. And what does this mean? Now when you submit a lead, we can see who you are, score it, and route it to our 25,000 sellers around the world. Now, when you file a ticket, we might know more things like what's your trailhead badge, what are the certifications you've done have greater context on you. And this means we can now power agent experiences. On our website. We've now served more than 1.8 million of you helping to solve your problems. We now have almost 23,000 salespeople every day in Slack talking to agents to help them prepare for deals. And now our SCR agent is helping to respond to leads that we can never get to. And this is running 247365. When this sneezes, I'm getting alert, I'm getting pager duty. We're trying to solve it. If it doesn't solve it, I'm calling my friend Rahul and say, hey, we got to work on this.

And we do.

We figure it out. And this is what customer zero Means to us, our pain and where we solve our own pain turns into better software for all of you and solutions to help you and your business. But it's not just about running at scale. And by the way, obviously I didn't build this. I want to have a shout out to Janani and Abhishek. I don't know if they're in the room here today, but they were with us when we started with one Scrum team. So let's give a big hand to them. We've taken it from one Scrum team to now this. And of course so many in the teams made this possible. But it's not just about scale, it's about impact. And we're now seeing incredible results for our marketing teams. We'd be able to take data that was trapped and automate revenue and E commerce. As we start to take smarter data and target our ads, target our marketing, we're seeing huge lifts with more pertinent, relevant advertising paying off for our sales team. Now, year over year, every lead we send to them, we're way more likely to convert into a deal. Every time we have an alert, it helps to prioritize high interest prospects. And for our service with the help agent, we have now saved almost $100 million in costs. That's right, $100 million. How? Because if the agent can solve your problem right away, that means you never have to file a case. It never has to go to a support engineer. And that means our support engineers can spend more time helping all of you create success with your customers. But we would not have been able to do this without the power of the platform and zero copy. And we have a lot of data. We have more than 90, I think 95 trillion records in Snowflake, hundreds of petabytes on Amazon. I'm not going to get rid of that. We spent a lot of money and time building that infrastructure, but we used half into it. By our estimates, we've saved more than 10 million on engineering costs that we would have had to pay if we'd had to shuffle that data around. That means that we could take our data and turn it into action to drive our own results. But I want to actually show you this in action. So we're going to. Welcome back, April. Here we go. Let's do a demo. Let's actually show it. So this is our real production instance. And by the way, we're in production freeze during Dreamforce. We don't want to mess up anything for you. So there's a little friendly reminder. Everybody you can see we have about 1,000 data streams coming into our instance. Those data streams then get harmonized into the unified profile. So if you look kind of on the right, you can see all those profiles now. 46% consolidation. They were fragmented. Now they're unified down into single profiles. This means we can then take data. So let's take an example. Here's a table we have on Snowflake that our marketing data science team produced. It gives an estimate of the value of the touch points. Almost 23 million records. Now we want to use this. So look at this. We can now build a segment taking that same data, zero copy, no movement, and we're able to build it. We can go through this and wait, it's production. Please don't do that. Don't do that. It's production. All right, so this is a real 5 million segment population. It's real. It's real. We gave her access. We'll take it back later. Anyway, so let's now show you this every day. This is running. So you can see this segment publishes to our marketing cloud for European marketers. And I'm glad it actually was successful yesterday. It's a good history. Everyday publishing out. And this is showing you kind of what Meta showed you, right? How we activate data for better marketing. But it's not just activation. It's also about agents. So let's look at that help agent. So when you go to ask for help and you start to say, hey, tell me more about data cloud connectors. The answer is, of course we're going to have it right? We have all the answers. But how does the agent know that? Agent force think. You got it. Yes, yes, Here we go. It's telling you about it. Well, behind the scene, we have built those search indexes. So all those documents now come into knowledge indexes that every agent can take advantage of. And now every single agent you work with is coming from this data. The structured data about you as the customer and the indexes of knowledge that allow agentforce to give the right answers and serve you. But I want to talk a little more about zero copy. And who better to talk about zero copy than Christian Kleinerman? The EVP of product is Snowflake. Come on down, Christian. Let's talk about some data stuff. All right.

Hello, dreampours. How's it going?

Amazing. Well, Christian, we've done a lot of work together over the years. I'd love maybe you can talk a little bit about the history of our partnership and what we built together.

At.

The heart of What Snowflake does, it's all about helping organizations get more value out of their data. And of course that includes Salesforce data. And I think we saw many customers trying to integrate our technologies and leverage data. We built a connector, then we looked at where there was additional friction and we've systematically been making it better until we arrived at zero copy sharing, which is the marquee integration between us.

Amazing. Now what are some of the common pain points that our partnership is helping our customers solve together?

I think at the very top of the list is data copies. You said you wake up and you think about data. I don't think you think about I'm going to make a new copy today because copies are a pain. A because maintaining a new pipeline and how do you keep it running? All of that is painful. But the other one is security and governance. Now you have an extra copy to govern. That is why we're so excited about the ability to integrate and collaborate without having to make an extra copy.

Yeah, we showed the demo course taking our Snowflake data, activating it at the data cloud. But customers can go the other way, right? Can take from data cloud into Snowflake. I'm curious, what are you seeing as use cases that bidirectional fluidity of data?

Yeah, we see a lot of value on going having data going both directions. Kind of like an example Salesforce has great customer data. Someone may have product data in Snowflake. So you can say zero copy from Salesforce to Snowflake. I combine it with that product data. I can use old school machine learning that still exists and they still a thing and be able to do for example prediction creation or leads generation. And once I have those insights, I can use zero copy sharing back onto Salesforce and put it in front of the users. That's one of many use cases that we see on a regular basis. Our two technologies working great together.

Yeah, we're doing that all the time. Seems really great to share that now. I think zero copy is really part of a bigger story about openness. What does an open ecosystem mean to you and to Snowflake?

We're very committed to interoperability of technology and data in particular. And it goes at the bottom of the stack which is Apache iceberg based open data. We also do it for catalogs and it was Salesforce and Snowflake. A few weeks ago we're making an announcement sharing how we want semantic data, semantic models to be able to interoperate. We announced the formation of an open semantic interchange and it's again, us collaborating towards data and metadata not being locked in.

Amazing. And we've done so many great things together but there's a lot coming up. What excites you about the future? What's next?

At the heart of it, we're all living in amazing times. It's the era of AI, it's the era of agents. But in the enterprise the power of AI comes from data. I think that's where I see lots of additional opportunities for us to continue to collaborate and give more power and more use to those agents and those amazing solutions.

Amazing. Well, thank you so much Christian for coming today everybody. Please give a big round of applause to Christian.

Michael, thank you.

Really appreciate the partnership. We just showed you some success we're having with Zoom Zero copy in the ecosystem. But we're not alone. We're seeing so many companies really get success from Zero copy. And in fact nearly half of all the data in Data cloud in H1 this year was accessed from zero copy. And with the success we're seeing, we're really proud to announce a bigger zero copy network. So now we have IBM zero copy file federation and more than 108 new sources now available in for all of you to try. So no matter what kind of data system you have, you can seamlessly connect to the data cloud and activate your data to create success. Now with this I'm going to hand back over to my partner Rahul and take us on home.

Thank you Michael. Thank you. Thank you. So Michael and Salesforce are our first and best customer. Mark tells us that if we don't make Michael and customer Zero happy, we don't. We have not earned the right to ship software to you. So I'm delighted to see Michael being successful. I want to move on to another topic here and we are running behind on time here. I want to move fast. I want to acknowledge Informatica. Informatica was an acquisition that we agreement to acquire that we announced earlier this year. We're waiting for regulatory approval. We do have the leaders from Informatica here with us. Krish who is the CPO and Bala who is the cto. They're here today acknowledge them. So we at delighted about the fact that we are going to provide end to end data management experiences and data processing experiences, data fluidity that I've talked about across catalog or integration, governance, mdm, et cetera. They're going to be phenomenal synergies for you, the customers when Informatica really completes post close. So I want to switch to a topic that is near and dear to me, which is the databaser community. There's 70,000 strong. Now you can join the community. There's a QR code out there. I do want to switch and talk about a leader in the community who is really led in terms of what you can do and what the rest of you really have leveraged his services as well. Mehmet Oran, who's here today. Mehmet, there you are. I didn't see you walk up.

There you go.

So Mehmet, so you've been a Data Cloud customer and a databaser for a few few now been while. So tell us more about your experience with Data Cloud.

Prior to using Data Cloud I owned a large stack. We had MDM data lakes integration, a large team and a large maintenance budget that went with it. What I like about the fundamental philosophy behind Data Cloud is every key feature you need to bring data together, to improve it, to act on it, are all combined together under a common feature set. And you can still have the choice to leverage Snowflake or leverage Informatica mdm. That never goes away. That means a total lower cost of ownership and faster velocity. Our first implementation was more than a year ago. It was April of 2024 where we migrated from HubSpot to Salesforce CRM. In 3 weeks part time team of 4 we started presenting about it. We brought the historical data into Data Cloud that gave us the Data Foundation. In the meantime identified overlapping customers to ensure no unmanaged duplicates for marketing engagement. Fast forward to spring of this year. We went live with our sales agent that used the historical data. All those activities no one looked at plus our transactional data in Sales Cloud and Service cloud. Four weeks with a part time dream of three. Is Angelica in the room?

She might be.

I just met and I want to recognize her because last year we didn't have a lot of new features yet. So we figured out how to bring it together. It has been great. Our sales team is being more efficient and more effective. Powered by better data every day.

That's awesome. So agility. So you have really talked about going live in three weeks. Having migrated with HubSpot to data to Salesforce with Data Cloud as being the foundation. So what's been the magic? What's been the success there? What's the story behind the success?

Honestly, it's not the magic. Like you have a clear use case, you understand the capability of the platform, you find the right partner, you find the right people and then it's a matter of executing with focus and keeping on learning.

So tell us more about your role at the databaser community.

So I think the birth of this is a good story to tell because when people were skeptical that you could do something in three weeks, people wanted to know what we did. But then we quickly realized people wanted to know what we did but how we did it. So the one hour presentations turned into day long workshops. We show hands on practice how to deal with messy data, messy schemas and it is now a global group of everybody's helping each other because none of us have all the answers. But together we grow better together and our impact grows as well.

So I want to switch over to Roadmap. So you've been privy to our roadmap we've talked to you about lately about a few capabilities are coming up their upcoming capabilities. What excites you about them?

Look, not only we talked about it, I really appreciated the opportunity to try them out pre release and I'm excited to show what I have been spending the part of my time last month just experimenting.

So let's spend a minute if you want to show it to us.

So my day job is I'm the GM and data strategist at Pure Nova. We do software focused on data reliability so we want reliable data in return. But what I want to deliver to every one of my teams is better data, faster to make business decisions. So the first feature that we were looking at is Simple Start. And what it does is instead of coming to a homepage, as pretty as it may be, when I come to data streams, every single one of my home CRM objects are automatically ingested. And not only they are automatically ingested, they are mapped. So instead of spending the time finding a data model, looking at help and training, figure out what I need to do. Everything is ready within minutes of my having turned on Data cloud in my org. This means we can focus on acting on the data, figuring out what the business use cases are. Simple Start gives us the ability to go from turning on the feature to start working in almost no time at all. The second feature I want to focus on, which is even more meaningful, is how we use agents to bring additional data and improve the setup and maintenance experience. In this case I have account registration. This is getting data from Snowflake via Zero Copy. And what I want to do is ask my agent to map this object. Now ordinarily as a data architect you would look at help and training. You would look at the schema, confess if you will, create a spreadsheet for this and you're Going to try to find all of your target objects and hopefully drag and drop sufficiently and effectively to figure out what the right target needs to be.

So while that is thinking, the previous topic that he referred to, simple start where CRM data just showed up automatically inside data cloud that also got mapped. That is free right now. Yeah, that's correct. It's free. All CRM data is coming into data cloud now is free. You don't get charged at all and.

No reason not to bring it in to act on it now in the meantime, thanks for helping me fill the time. The mapping recommendations are already available on the screen and what you see here is because these agents know the target schema possibilities, it knows what is in the object I just pointed to. It gives me recommendations on what are all of the things I can map to and it doesn't take action on my behalf. I'm still accountable for the correct design, but I am now saving weeks worth of work to focus on the hard part.

One thing that I would say is that it's not just the mapping agents. We also have segmentation agents. We also have the agents that are for activation. They're all coming, they're all getting ga'd in January. So Mehmet, I think we want to wrap up with the segmentation agent. We can talk about it. We're coming very close on XM here.

So what I want to do, and I'll let this run in the background while it's happening, is the best data is not going to be powerful unless you can act on it. In order to drive business results. One of the things that the philosophies I'm embracing is if I can think something I want to do, I can type it, which brings me the results so I can test it. As a result, I tweak it. I'm the professional that's responsible.

And.

And weeks are becoming days, days are becoming hours. Rahul, someone is going to break our record, which we were so proud of. When does this become available?

It's right on the screen. It's all available in January. Thanks for your pilot. Thanks for running pilots with us and thanks for all the databases for running pilots with us. All of this is available in January. So you're excited about going zero to activation on your first day or in a single day?

I think this is going to be real.

Okay, so I do want to switch gears and talk a little bit about. Memetoron is the winner of our golden Hoodie, the first golden hoodie for Data Blazer. So can we get him the golden hoodie.

Here.

Thank you.

So all that green space, all the feedback, all the hours, it's been great to work with your team. Yeah.

So this is amazing. Thank you, Mehmet. Folks, so at this stage, I'm going to give you an. I would call people and tell them about what they should be doing. The cta, so to speak. Call to actions. Right. Would you do the honor of actually telling the folks what they should do at Dreamforce?

Yeah. Thank you. Thank you everyone. Look, I'm going to say that the way to be here to share success stories is the power of all of us. So go find another databaser. We are hosting a networking hour downstairs. Moscony west, second floor. Immediately following the keynote. Come find other customers that share their success stories. I'm going to do a session Wednesday with real production screenshots. You before, with better quality. I get permission to do this. And after. So you can learn from story and implement it yourself. Get your hands dirty with the labs. Experiment it in a safe setting. When you are skeptical, go to a roundtable, talk to customers, talk to consultants. Find out how they succeed so we can all be better together. And then break our record. Be on the stage instead of me. Tell your story. Let us learn from you, Rahul. Thank you.

Awesome. Thank you everybody. Have a great dream force. Mamet Oran. Thank you.