Today on the Salesforce Admins Podcast, we talk to Skip Sauls, Senior Director of Product Management at Salesforce. Join us as we chat about why data is so important to reporting, what some big-data terms are, and some fun hobbies that Skip enjoys outside of building awesome products for Salesforce Admins.

You should subscribe for the full episode, but here are a few takeaways from our conversation with Skip Sauls.

The data lakehouse

Skip is the product manager in charge of the ecosystem for Data Cloud, which unifies data from Salesforce and other sources to give you a single source of truth for everything your organization knows about your customers. This will make it easier to do everything from generating reports and dashboards to implementing new apps across the organization using the data you have, no matter where it’s coming from.

For admins, Data Cloud will remove the need to move data around every time you want to use it somewhere else. This reduces the risk of using old data or accidentally opening up a security vulnerability. Instead, you’ll keep your data in a centralized “Data Lakehouse” (both a data lake and a data warehouse) and pull it from there when you need to use it for something.

What you get from centralizing data

Centralizing your data management in one place has a number of other benefits. For one thing, it gives you a framework for making important decisions about which source is the most authoritative so you can resolve any conflicts that may come up when there’s a disagreement. What’s more, it’ll minimize situations where reports and dashboards don’t match up because they were created from different sources or pulled at different times.

Today, when new data comes in from somewhere, you can’t necessarily be sure how long it will take to update in your other orgs. With Data Cloud it’s all in one place, which means any changes will be reflected everywhere simultaneously. And if you need to figure out why a report is telling you something different today than it did yesterday, you can go back and look at a snapshot without having to dig through multiple orgs.

The future of Salesforce

Going forward, the hope is to build more and more Salesforce features that are used in multiple orgs on top of Data Cloud, separate from individual platforms. This gives every platform you use access to the same powerful tools like advanced analytics. It’ll also make it possible for third party platforms to work directly with Salesforce capabilities, offering more flexibility for your org. 

This all gets even more exciting when Skip starts talking about the possibility for building apps that can be reused throughout an org, or even users creating things with generative AI. The streamlining provided by Data Cloud will make all of that possible.

Be sure to listen to the full episode for more of Skip’s thoughts on the future, and what Evel Knievel’s stunt bike can tell us about where technology is headed.

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Full show transcript

Mike: With Salesforce Data Cloud, you can organize and unify data across Salesforce and other data sources. After data has been ingested in Data Cloud, it can be used to drive personalization and engagement through the creation of audience segments. This week I’m talking with Skip Sauls, product manager in charge of the ecosystem for Data Cloud. Skip is going to help us understand why data is so important for admins, and the reporting that we need to do. He’s also going to give us some insight into terms that we’ve been hearing, or at least I’ve been hearing, around data. Before we get into the episode, I want to be sure that you are following the Salesforce Admins Podcast on iTunes, or wherever you get your podcast. That way, you get a new episode every Thursday right on your phone. Let’s talk data with Skip.

Skip, welcome to the podcast.

Skip Sauls: Thanks Mike, enjoy the invitation.

Mike: It’s been a while since we’ve chatted. I know we’ve passed each other quite a few times at events here and there. Just get everybody level set on what you do at Salesforce.

Skip Sauls: I’m a PM on the Data Cloud, and my specific role is around the data cloud ecosystem, which is largely defined as our SI partners, also known as alliance partners, and then our ISV partners, which are largely around app exchange. That means all the things related to making those two groups successful, a lot of that relates to things in the dev and admin world, which is why this is an interesting crowd to talk to. This is everything from the dev experience to packaging to ALM, application lifecycle management, to all the things we need to do. A big passion of mine, as many of from my previous life, is around the admin install experience, so making sure that we can get these apps up and running inside of all these disparate orgs easily.

Mike: For an admin who’s just hearing about Data Cloud, how would you explain Data Cloud?

Skip Sauls: The plan for Data Cloud is to have it be the data platform for all things Salesforce going forward. Over the next several releases and years, you’ll see more and more of our app clouds and properties, and teams, et cetera, moving to use the Data Cloud, and you’ll see some of those in the very near future. This is not a far future thing for a lot of them. The basic idea is to give our customers a more flexible and powerful platform for data than standard Salesforce core, and importantly, unify all that data in one place, so we don’t have the silos of data like we do today, so lots of ambitious things around it.

It came out of the marketing cloud. There’s the customer data platform you’ve heard of, but the features themselves are also designed for use in all data scenarios, and lets you operate on the data in one place, no matter how many different orgs you might be, in the case of the admins, working with, and not have to have movement of data between all the different orgs, like we do today. We’re trying to really make it much more rational, if you will, as to how we deal with data.

Mike: Does Data Cloud really just apply for data movement and reporting between orgs, or does it also apply, you mentioned Marketing Cloud, in between clouds as well?

Skip Sauls: A picture I would paint is that all of the clouds will eventually move to or support Data Cloud, and instead of having each org having its own data, or each product stack having its own data, you’ll have data in one place, the data lake house, as people like to refer to it. You could have data related that’s to customers, or to other business entities, and sales service, marketing, analytics, all the industries would all pull from that common data cloud instead of having the, I hate to say siloed, it sounds so negative, but today you have to move things between the clouds in a more manual fashion.

Mike: I’m trying to put that picture together, and really, how I’m envisioning it is, Sales Cloud or Marketing Cloud is almost the input for how data is then gathered.

Skip Sauls: Exactly.

Mike: Gotcha. As somebody who grew up in Sales Cloud, it feels very different.

Skip Sauls: I would say that to the end user, they won’t necessarily notice a difference. They’re still going to be using a sales app, or a service app. To an admin, you’re going to have the ability to say, “Let’s go to manage it effectively on the data cloud.” In theory, I could manage the objects in one place, and then multiple other orgs can point at that data cloud org, if you want to think of it that way, and they won’t have to have as much data themselves. Things that are currently in core may end up being mostly the metadata, and things like that, but not a lot of the pure data itself.

Mike: One of the things I think people, and you probably run into this a lot, they suddenly care about their data when they need to run reports, which is one of the themes of a lot of the content we’re putting out currently. Data is important for reports, because one, if you don’t have the data, there’s no report; but two, if you have bad data, there’s no report. I think the third thing, the reason why I wanted to have you come on is, there’s also a lot of places currently for data to live, which is why Data Cloud exists. Can you touch on, as an admin sitting down hearing this, thinking, “Okay, I want to take reporting in my organization to the next level,” what are some of the things I should be thinking about with Data Cloud, and with just good data collection and habits?

Skip Sauls: On that point, one of our partners, recently we had a discussion, and they were mentioning what they called a golden record, and what some people call the single version of the truth. That’s where I think a lot of people will leverage Data Cloud. There may be multiple sources of truth, you might have things that come from Salesforce core, maybe have things that come from somewhere on Amazon, or Google, or Microsoft, pulling it in, and the Data Cloud representations are considered to be the single version of the truth, and that is the agreed upon version of the truth for your company.

Now, that sounds politically charged, because it’s the version of the truth, but that is what people want, the ability to effectively curate the data. You’ve got data lineage, data catalogs that prove that it’s the correct data, but what you’re presenting could be effectively controlled and curated by people on the Data Cloud. Your reports can draw from that instead of trying to go across multiple data stores and data sources. If you need to do some data cleansing, checking accuracy, if you want to do things for compliance checking, you can do it on the Data Cloud instead of having to do it in each individual siloed data store like we do today.

Mike: Wow. I was just thinking, many years back I actually went through an exercise where we were looking at an organization that had what everybody thought was multiple sources of truth, and combining them into a master data record, and then sitting down and trying to figure out, what were the resolutions to conflicts, and who can update who and when, and then, who wins? I’m sure these are all terms. For example, if we update a record in Salesforce, and then Oracle Financial gets an update, who pushes to the master data record, and what’s the conflict? Who wins?

Skip Sauls: I’m not working on those features, but the whole resolution aspect of it is something that people bring up. There’s identity resolution right now, which is one of the features of Marketing Cloud. You can take all these disparate representations of a user in this case, and determine that this is actually the same user, even though they’re coming from all these different marketing data sources. The data accuracy piece is one that would probably run in the data cloud itself, and say, “Okay, this is the agreed upon source of truth here, and we’re making sure that it’s correct.”

All the things around the process side that you mentioned, of who gets to update it, is going to be done through Data Cloud. The flows teams are all working on Data Cloud, all the events on Data Clouds. All these things that you’re familiar with in core are being enabled on the Data Cloud. You’d be able to say, based upon something, kick off an action, kick off a flow, just like you do today, and there’ll be some ability to say, “Let that be the thing that determines what gets updated” in a hopefully more structured fashion. You have more control over it.

Mike: Right. Back to something you mentioned earlier, which is interesting, did you say source of truth at the time for data? I always try to explain stuff like this to executives. There’s a lot of talk around realtime data, too, but source of truth at the time, you can run a dashboard at 1:30 in the afternoon, and by 1:35 the dashboard’s out of date because the data’s out of date. If you had to explain source of truth at the time, or multiple sources of truth, isn’t that what’s going on? It’s not that somebody is really fudging the data, the time is also a factor when you’re looking at data.

Skip Sauls: Exactly, and we see this even with standard reports and charts today, where somebody will question, “This is not what we saw in some other presentation.” Somebody else just took a snapshot at a different point in time. I don’t know that Data Cloud’s going to solve that, but in theory, you’re pulling it from one place, and everybody’s getting the same representation of it. Because it’s in a big data lake house, the opportunity to store those snapshots in time is greater. You’re not just looking at the most current record, but you could also have a history of things, and in theory, look back at data at a certain point, and say, “Here it was at 1:30. This is what it was accurately, and it has changed, because it is not necessarily bound to just the current database-style store.”

I think that’s a interesting area. The realtime thing is one that comes up, and that refers a lot to the ability to stream data in. It’s not meant to imply that it’s a realtime system in the classic computer science sense. We’re not changing things so radically that everything is real time, but the goal is to make it feel real time to the average human user who needs to update something and see it reflected somewhere else in a reasonable amount of time. That’s what they’re getting at. The realtime thing is a charged label, as you can imagine. That’s something today that, with a lot of the Salesforce clouds, we struggle with, as to how soon it’s going to show up somewhere else, if you’ve got it in the report, or chart. I think the potential for making that more near real time is there.

Mike: Yeah. Actually, I’m glad you touched on that. I know you’ve said real time in a few answers, and I wanted to come back and be like, “What does that mean?” To me, real time feels like watching the stock ticker at the bottom of a financial network, and you’re like, “It’s happening in real time.” That stock was probably updated, and then it had to go to a system, and then it had to go to another system, and then it had to get fed into this ticker system, so it’s a minute and a half behind, two minutes at best.

Skip Sauls: Exactly.

Mike: Another term you’ve said, and some of this is just the soft landing into this new world, I’ll call it, of CRM. You’ve said data lake a few times. I remember, as I started to get into the world of data and databases, “Okay, this makes sense to me,” and then big data stuff came out, and I started hearing the term data lake. Can you help admins understand what a data lake is? I think you’ve also mentioned a data lake house, which obviously, sounds really cool. Maybe I want to live there, I don’t know.

Skip Sauls: I’m probably not the right one to describe those really deeply, but the idea is that it’s a place for you to store your data. Lake house is data Lake, data warehouse combined together. I would be out of my depth trying to dig into all the specifics around it, but our vision for it is the single place for data. The future, if you will, is that even your single source of truth data, your things that are database-centric today would eventually live there.

If we fast-forward, I don’t even know what the release date would be for this kind of thing, but if you imagine, you’re creating things that are actually living in that world, directly in the Data Cloud, not in core. They’re not creating things anymore in the standard Salesforce core, and you have more potential for large volumes of data. You can handle huge amounts of data compared to classic Salesforce, and even bigger volumes than you can handle with things like some of our analytics products that have large data sets. I’m not sure I’d be the right one to describe the-

Mike: No, I appreciate you taking a swing at it, because I feel like, even if you’re not right, it still helps. How in context would you explain this? That’s often the position that an admin is put in. “That’s a good question. Let me jump into that a little bit more.”

I’m also just scrolling through our page, looking at everything Data Cloud. I think we’ve talked a lot about inputs. Data Cloud is also built to work with all of our analytics platforms, Tableau and stuff like that. If you’re a Tableau user, you’re able to pull these really great visualizations out.

Skip Sauls: Today there’s Tableau connectors that can pull from the Data Cloud. For CRM analytics, there is a direct query into the Data Cloud, so you can actually have a dashboard that’s interacting with it. Over time, we’ll unify a lot of our analytics features on top of the Data Cloud. That’s where things are going, if you will. The vision is that all the tools, analytics tools included, will all pull directly from that Data Cloud in the future.

Mike: Gotcha.

Skip Sauls: That even opens it up to, non Salesforce tooling becomes easier to do, because everything can pull from it in the same fashion. We would have our own products, but competitor products could potentially use it in the same way, which I think is interesting. It’s very different from the very specific tool and data store model that we have today for a lot of things.

Mike: I think there definitely was a period of time when, for an organization or a company, you looked at, how do we go all in on this platform, and use everything? You quickly realize that some parts of the platform don’t do what you need it to do. I think now, 2023, what I see in working with a lot of admins is, organizations find the right tool for what they need. Then it’s, how do we stitch these tools together, which to me, makes Data Cloud the most important thing that we have, because this can act as that foundational layer for, how does everybody, regardless of the tool, get the right information?

Skip Sauls: Exactly, and an example of that is, some of our partners today are looking at what they would do on Data Cloud. They’ve in the past had specific integrations for sales, and service, and industries, and the picture we’re trying to paint is, you would actually have your objects living in this Data Cloud, and your apps could be something that could work more easily with something else. It’d be easier for somebody to wire it together through an app builder, or through some other declarative tech, because they’re all working against the common Data Cloud, the models. It’s not so specific to a particular product or data store. I think that’s very interesting, and that leads into what I love to call ad hoc applications. This is not my idea, it’s what I’ve just heard people talk about. “I need an app that will do something very specific, and I don’t care if it’s highly scalable or lives forever, because I’m not building it for that. I just need to get that job done.”

It may be a throwaway app, or it maybe something a lot of people want to use, and then an admin can take it and make it available to other people. What I’d like to see us get to is letting even end users build these apps, because everything is in a well-defined and controlled environment. They’re wiring it together, or maybe they’re using the generative AI to say, “Build this app for me,” and the app is built using these building blocks that are from Salesforce, from our partners, the customer writes them themselves, and they all work together against the data cloud. It’s easier in theory, because you’re not trying to piece it together across all the different platforms and data stores. That to me is very exciting. I think we’re finally at a point where we can actually realize a lot of that. The Data Cloud is part of that picture, the generative AI that everybody’s excited about is another big part of that.

Mike: Well, that leads perfectly into my last question, which was going to be, where do you see the future of Data Cloud, especially since it seems everybody can’t stop talking about AI, and GPT, and machine learning?

Skip Sauls: The one thing that may not be obvious is that most, if not all of the generative AI tech will be running on Data Cloud. You’ll hear people say, “You probably should be using Data Cloud if you want to use this kind of technology.” Part of that is because, some of the AI tech runs better off core, or what we think of as being near core, meaning that it’s still within the Salesforce-walled garden, but it’s not the classic Salesforce core platform. It’s on the public cloud platforms. The end user won’t know that they’re using another cloud provider. They’re not using a public cloud directly, they’re still using Salesforce, but the underlying pieces of it are running on this new platform, and the data platform is part of that. I would say, if you’re interested in generative AI, look at the Data Cloud as the thing that enables most if not all of that.

On the flip side, the partners and customers who use this can put their data into the Data Cloud, and use generative AI against it more easily than you can with the current Salesforce model. There’s all sorts of issues to work through around this, of data privacy and security, but we as Salesforce can secure it better than if you say, “I need to export this out to a public cloud and run something there, and then import the results back in.” That causes a lot of our customers to have heartache, heartburn, trying to think about how to handle that. We can say now, “Data Cloud is within that Salesforce security model, in the circle of trust, if you will.”

That’s exciting to me. I honestly think that a lot of what we call Data Cloud, the perfect thing that will happen is that no one will talk about Data Cloud in the future, because it’s just part of the Salesforce platform. It’s Salesforce, Data cloud is an enabling tech for it. It’s not a thing you’re going to, if that makes sense.

Mike: No, it does. The irony is that it’s actually so performant and so well-built that it’s invisible.

Skip Sauls: Exactly.

Mike: Isn’t that the whole idea of technology? Technology is almost magic if it’s built really well.

Skip Sauls: Exactly. The stuff that disappears in the background, you don’t think about using it, everybody just intuitively uses these things. That’s the big success point. For our admins, we want our admins to feel like, “Hey, I’m a Salesforce admin, I’m not a Data Cloud admin.” We’re doing persona UX research right now, and everybody keeps coming back to the fact that we don’t really need a Data Cloud admin persona. We have a Salesforce admin persona that will manage these Data Cloud entities, if you will. I think that should be music to the ears of the admin community, because we’re not trying to reinvent the wheel and force you to go to something else to do all these things.

Mike: I think that’s also the fear of customers, too. If you keep adding products and features, do I have to keep adding headcount?

Skip Sauls: Exactly.

Mike: If you have a skilled workforce, in theory, they should be able to handle all of that. Skip, we covered a ton in a little bit of time. I always like to end on something fun. In the years of doing this podcast, I had a product manager on that smelted metal as a hobby, and one of them collected board games. I’ll just put you on the spot, outside of Data Cloud, and generative AI, and everything we just talked about, data lakes, is there some fun stuff that Skip likes to do?

Skip Sauls: Yeah, two things. I love to ride dirt bikes with my son, and I like to build PCs. I think you have a motorsports passion yourself. I used to race cars, but dirt bikes are something I can do with my son, because he’s not of the driving age yet. I’m a gear head.

Mike: Do you have a place to go ride?

Skip Sauls: Yeah, we have three tracks not far from here, they’re motocross tracks. I’m an older guy, so I don’t do the crazy stuff. My kid does the big jumps. I get out there and have fun whenever we can.

Mike: Yeah, those guy… and man, dirt bikes. If you ever want to see something evolve at rapid pace, if you look up what a dirt bike was in the 1970s to what one can do now, it is just phenomenal. The technology, the metal, where we have come with our understanding of how to shape metal, and the tensile strength of metal, and the stuff that we can ask it to do, is just fascinating. I say that because, coming off World Tour DC, we were at the National Air and Space Museum, and they had a dirt bike there, it’s relevant, that Evel Knievel used in one of his jumps. This is late 1970s, and you look at it, and the heft, and the size that some of those bikes were, and how under horse-powered they are compared to now, and how light swing arms are, and how light torsion bars are, and how much horsepower can come out of a two-stroke motor.

Skip Sauls: When I see the old Evel Knievel videos, I’m like, “I can’t believe he’s doing that on that bike.”

Mike: Yeah, it’s a lead weight with a motor. Oh man. Skip, I appreciate you coming on and talking Data Cloud. I’m sure we will see more of your work, or maybe not, actually. Isn’t that the goal? Maybe we won’t see more of your work, it’ll just slip into the background, and we’ll all be very thankful for it.

Skip Sauls: I think that would be the best thing. I do look forward to meeting up with people in the community, maybe at some of the upcoming world tour events. When we do, we try to go to the admin or dev user groups, and present. I would love to meet with you folks in the field.

Mike: Fabulous. Thanks so much, Skip.

Skip Sauls: Yeah, thank you. This was great.

Mike: Well, that was a fun discussion with Skip. I might have spent a little extra time talking dirt bikes with him. I hope you didn’t mind that at the end. If you enjoyed this episode, share it with one person. If you’re listening on iTunes, just tap the three dots, and choose “Share episode.” Then you can post it to social or text it to a friend, your call. If you’re looking for more great resources, your one stop for everything admin is We’ve got everything there, including a transcript of the show. Be sure to join our conversation in the Admin Trailblazer group in the Trailblazer community. Of course, there’s links to the show notes below. Until next week, we’ll see you in the cloud.


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