Salesforce Simplified: The History and Future of Salesforce Data Cloud

Data Cloud is the fastest growing organically built product in Salesforce’s history (i.e. Salesforce built it themselves, not via acquisitions). Data Cloud could be described as the ‘Holy Grail of CRM’, meaning that the data problem that’s existed since the infancy of CRM is now finally solvable.

A Salesforce study revealed that the average company has 928 systems – so a big company has thousands, and a small company likely has hundreds. As soon as you have more  than one system, identity resolution becomes a challenge.  

Salesforce has expanded into AI-powered CRM, the focus being on combining AI and data. Without data, AI cannot function to its full potential.  

Data Cloud is the foundation that speeds up the connectivity between different ‘clouds’ across the platform. However, Data Cloud is also a product that can be purchased. While not all Salesforce customers have licensed Data Cloud, being at the foundation means they are still taking advantage of Data Cloud to a degree – but this all becomes even stronger with Data Cloud as a personalization and data unification platform.  

So, what’s the journey this somewhat elusive Salesforce product/infrastructure has been on? We’ll take a look back in time to understand where we’ve come from, why Data Cloud stands strong in a crowded market, and finally, take a glimpse into the future.

Host: Andy Whiteside
Co-host: Derek Cassese

Transcript

WEBVTT

1
00:00:02.170 --> 00:00:13.749
Andy Whiteside: Everyone welcome to episode 2 of salesforce simplified. I'm your host, Andy Whiteside. I've got Derek. Cassie's with me. Derek. How's it going? How's it going?

2
00:00:13.790 --> 00:00:24.129
Derek Cassese: Yes, it's good. It's going good, you know. You work from home. You gotta deal with a couple of hurdles here and there, and so we'll we'll we'll do the best we can, you know. Got an old dog, and she ended up

3
00:00:24.500 --> 00:00:35.880
Derek Cassese: Shannon. I'm getting into some stuff. So it's all good. Our podcast was delayed because they're kind of at a moment. And all's good dogs fine cleaned up enough to get through the podcast yes.

4
00:00:36.430 --> 00:00:44.390
Andy Whiteside: alright, it's real life. Oh, I know what else is mentioned. Here's why, here's what I meant to mention. I want to start all these podcasts, all the podcast we do with

5
00:00:44.550 --> 00:00:47.530
the the tagline context matters.

6
00:00:47.760 --> 00:00:56.940
Andy Whiteside: And we'll end with context matters cause that's that's, we do these podcasts, we do these podcasts because we want people to see value in us as a partner in this case with salesforce.

7
00:00:57.030 --> 00:01:12.059
If you're working with a partner and you're not getting the value out of salesforce, either because the partner, because of salesforce or somebody's not bringing it all together. That's what we want to do. That's one of the reasons why we do the podcast we we use blogs. We got one from salesforce Ben today that we're gonna go over around data cloud.

8
00:01:12.360 --> 00:01:28.749
Andy Whiteside: And I'll hit that here in a second. But we use blogs. But then we add our context around it and our thoughts and our topics, because reading this in a vacuum by yourself is one thing, us talking through it, and you hearing us have a conversation around it is, we believe, super valuable. So tagline context matters.

9
00:01:28.760 --> 00:01:31.419
That's why we do these podcasts. Derek, what do you think?

10
00:01:31.580 --> 00:01:34.530
Derek Cassese: Yeah, I agree? 100%. I mean.

11
00:01:34.750 --> 00:01:42.710
Derek Cassese: we do. We need to be able to, you know, paint this in a picture where it makes sense. And we need to, you know, articulate that, especially with the topics that we're covering various podcasts.

12
00:01:42.900 --> 00:01:51.230
Andy Whiteside: And that's one of the reasons why, in general, I mean, you have your your bonus episodes, but in general we do it. You know 2 people do it together, so you can have a discussion, and people can listen.

13
00:01:51.410 --> 00:01:55.239
Andy Whiteside: and it makes it extremely valuable when you do it that way. We believe at least.

14
00:01:56.510 --> 00:02:19.910
Derek Cassese: Alright the blog from the day is from salesforce. Ben, it's it's I've never seen this before. I heard you mentioned it, but never seen it, and I think the the title of the blog is the history and future of salesforce data cloud before we jump into Ben, I guess his blog. See? Right next to it, Lucy. She she's the one that wrote it.

15
00:02:19.910 --> 00:02:40.369
Derek Cassese: Okay. Well, tell us about the the the site first, and then let's talk about the fact. Lucy wrote this, and let's jump in and talk about it. Yeah, well, so you know, most of the most of the salesforce community is probably well familiar with salesforce. Ben. It's you know, website. He's a consultant got a website, tons of information blog articles.

16
00:02:40.620 --> 00:02:47.859
Derek Cassese: And you know, it's it's an area. If you do some Google searching, more than likely it's going to be one of the top. You know, one of the top

17
00:02:48.700 --> 00:02:56.259
Derek Cassese: results when you search for particular content or topics around salesforce products, topics, etc.,

18
00:02:56.320 --> 00:02:57.810
Derek Cassese: and the drift.

19
00:02:57.840 --> 00:03:04.560
Derek Cassese: I guess a you know, I was just kind of searching around and found this. The the drip is kind of a

20
00:03:04.640 --> 00:03:11.290
Derek Cassese: a a piece of the salesforce, Ben company, right? So, Lucy, it says. Here is the

21
00:03:11.420 --> 00:03:23.970
Derek Cassese: founder of the Drip and she's the head of operations at Salesforce. Ben and she wrote this this blog, and it's recent. Well, it recent enough, right? August 22 or 2,023,

22
00:03:24.390 --> 00:03:45.219
Derek Cassese: and the can you pronounce Bluesy's last name just to give her credit for what we're going to review here. So, Derek, this conversation all the talk at Dreamforce. But why this blog? Why today? Why this blog from August 22,

23
00:03:45.440 --> 00:03:46.740
Derek Cassese: one of the

24
00:03:47.060 --> 00:03:53.330
Derek Cassese: one of the things. That was a center of topic. That dreamforce was data. Cloud

25
00:03:53.530 --> 00:03:55.709
was a huge

26
00:03:55.970 --> 00:04:01.960
Derek Cassese: topic. They announced that Enterprise edition. And up, we're getting data cloud for free

27
00:04:02.310 --> 00:04:03.979
10,000

28
00:04:04.170 --> 00:04:07.880
Derek Cassese: records. Credit basically is how they're doing it. And

29
00:04:08.280 --> 00:04:25.340
Derek Cassese: so I, you know, I kind of wanted to dig into that, because, having come from salesforce. You know, I had to kind of come across different products that did something similar. And I wanted to. I wanted to just make sure that my thought process and assumptions around what data cloud is were accurate. And so this basically

30
00:04:25.510 --> 00:04:27.409
Derek Cassese: answers the questions that I had

31
00:04:28.840 --> 00:04:48.170
Andy Whiteside: so coming out of dreamforce. Don't talk about data, Cloud, and some people getting it for free. And you and I were like, Well, what does that mean? And and what the you know what's the limits on that? I think you've covered that. But do it again if you if you haven't. And then the the opening paragraph or 2 here, kind of talks about some things that as to why this matters as well.

32
00:04:50.090 --> 00:04:52.799
Derek Cassese: Yeah, yeah. I mean, it's so.

33
00:04:53.080 --> 00:05:15.180
Derek Cassese: I mean, we could dig into the like the beginning part of the history of here. But you know, essentially data, you know, and data cloud is from a historical perspective. And I found this interesting. But it's the fastest growing salesforce built product. And that whole like salesforce built product is interesting like it wasn't. It wasn't an acquisition.

34
00:05:15.280 --> 00:05:20.189
We all know that, you know. There's a lot of pieces of the salesforce portfolio that are acquired. Slack

35
00:05:20.350 --> 00:05:34.960
Derek Cassese: right? Is one of the bigger ones. Tableau. Other pieces of that inside the platform. Rp are potentially pieces of acquisitions that are then folded into the platform. However, this was built kind of from the ground up.

36
00:05:35.260 --> 00:05:38.260
Derek Cassese: Over the past several years, and

37
00:05:38.530 --> 00:05:54.349
Derek Cassese: you know I didn't know that I thought that was kind of interesting, that you know that was one of the uniqueness is about this, and was also mentioned in here, is that they did a survey and found that, you know an average company has about 928 systems.

38
00:05:54.690 --> 00:06:04.680
Derek Cassese: And a system may be just a different platform, something right? Which means that larger companies probably have thousands. Smaller companies probably have hundreds.

39
00:06:05.070 --> 00:06:09.819
Derek Cassese: And it's creating in today's day and age kind of an issue with siloed data

40
00:06:10.070 --> 00:06:17.880
Andy Whiteside:  so it's not no longer app integration. It's platform integrations. And something's got to be the thing that brings the data together.

41
00:06:18.460 --> 00:06:21.970
Derek Cassese: Correct, right? And and what's really driving this

42
00:06:22.230 --> 00:06:26.730
Derek Cassese: is AI to be honest with you, and you know it's.

43
00:06:27.180 --> 00:06:34.719
Derek Cassese: you know. Chat GPT. Bursting on the scene, everybody talking about generative AI and all this good stuff. You know, the

44
00:06:34.810 --> 00:06:37.299
Derek Cassese: the foundation of AI is the data

45
00:06:37.380 --> 00:06:45.149
Derek Cassese: and having a good foundation of the data, will allow AI to execute at full potential. And that's.

46
00:06:45.480 --> 00:06:53.349
Derek Cassese: you know, kind of a theme here in what's what's trying to be accomplished, as far as you know, taking 2 separate systems and

47
00:06:53.360 --> 00:07:05.329
Andy Whiteside: and you'd find them. Is this, is this a matter of giving something like your AI engine access to all these different data sets, or bringing all the data sets into one place where the AI or the engine, or whatever the application is.

48
00:07:05.370 --> 00:07:09.130
Andy Whiteside: has a better chance of doing it quick and and well.

49
00:07:09.510 --> 00:07:22.530
Derek Cassese: it's it's that it's it's they call it harmonizing the data. So that if you think about it, if we've got, I'm just gonna make it easy. If we have 5 different systems. And your customer is represented in those 5 different systems.

50
00:07:22.940 --> 00:07:25.969
Derek Cassese: potentially have a lot of duplicate

51
00:07:26.150 --> 00:07:37.439
Derek Cassese: information and data. You may have different customer ids. And if something happens within one system, does the other one know about it? And can you see all of that in one place?

52
00:07:37.880 --> 00:07:42.939
Derek Cassese: So that's where you know, data clap. The concept of it is to you is to bring all of this together.

53
00:07:42.990 --> 00:07:53.800
Derek Cassese: unify the customer, unify whatever it is like, whatever object or entity, whether it be a customer, a patient in healthcare. But put that into the context so that

54
00:07:54.290 --> 00:08:00.499
Derek Cassese: each system can be aware of the other systems, and you can then surface all of this stuff in one place.

55
00:08:00.990 --> 00:08:13.649
Derek Cassese: So Derek is the intro. And then now there's the history of data cloud, which I think you've kind of covered with the history of all the different products that let me dive into this real quick cause. I think this is this was an area

56
00:08:14.070 --> 00:08:17.169
Derek Cassese: of confusion for me. And so

57
00:08:17.310 --> 00:08:22.959
Derek Cassese: it's kind of interesting, right? The history of data cloud. And we we're going to go back real quick to 2020,

58
00:08:23.060 --> 00:08:26.980
Derek Cassese: 2020. There is a product customer 3 60 audiences

59
00:08:27.400 --> 00:08:39.769
Derek Cassese: which was the initial Cdp which stands for customer data platform and so that was the initial kind of foray into this type of a product.

60
00:08:39.909 --> 00:08:53.309
Derek Cassese: It was then renamed. you know, it was renamed a year later to salesforce Cdp, okay, same product, different name. We all know that that happens all the time. But it aligned with the market

61
00:08:53.390 --> 00:09:07.119
Derek Cassese: and Cdp products that were out there, as far as terminology goes. So you notice how now Cdp is in the name of the product. the next the next phase, and a year later it was renamed to marketing cloud customer data platform.

62
00:09:07.420 --> 00:09:08.870
Derek Cassese: That's because

63
00:09:08.900 --> 00:09:38.190
Derek Cassese: essentially the the marketing Cloud Division and product suite was being renamed. And there was some standardization going there. But you can tell that at this point this solution was really geared towards marketers, right? It was geared towards the marketing folks that had to do a lot of, you know, de-douping and kind of unifying of customers in different, you know. Different sets of you know, maybe leads and all that good stuff it was. It was mostly in the marketing side. Right then.

64
00:09:39.020 --> 00:09:46.039
Derek Cassese: you know, at Dreamforce, in 2022 salesforce announced a product called Salesforce Genie. If anybody remembers

65
00:09:46.180 --> 00:09:48.190
Derek Cassese: and salesforce Jeannie

66
00:09:48.420 --> 00:10:01.820
Derek Cassese: was the renaming of the marketing cloud customer data platform to but it was. But it's not necessarily just the the name. This is what's so interesting is that the name? As these names change, you can kind of follow the

67
00:10:01.910 --> 00:10:05.230
Derek Cassese: the shift of how this technology is being used.

68
00:10:05.320 --> 00:10:22.390
Derek Cassese: And so now it's being it's being named such that it's a much broader use. Case right? You no longer have marketing the name. It's Salesforce Jeannie, to signifying that shift in use cases and sales and service across the entire platform right? And

69
00:10:23.040 --> 00:10:25.569
Derek Cassese: in this year 2023,

70
00:10:25.640 --> 00:10:32.969
Derek Cassese: Jeannie. The name was dropped. The mascot obviously stayed the same. But that's when it became data cloud.

71
00:10:33.200 --> 00:10:40.350
Derek Cassese: And that's kind of the evolution of that product which you know, as this article points out, was a pretty important

72
00:10:40.510 --> 00:10:51.160
Derek Cassese: investment from a salesforce perspective, but also because it's powering the like. The generative AI innovations that were very prevalent at at Dreamforce 2,023.

73
00:10:51.350 --> 00:10:59.080
Andy Whiteside: II like it. I'm sitting here thinking about the name going. I like the name data cloud for AI and more

74
00:10:59.110 --> 00:11:13.900
Andy Whiteside: or something, you know, cause you and I, you know we walked around with our data cloud, all at dreamforce. And I got it. But it just didn't pop right out to me that this was, you know, the enabler for AI. And then the minute you start talking about it a minute ago, I was like, well, of course, that's what this is.

75
00:11:14.790 --> 00:11:19.380
Derek Cassese: Yep. So so that I mean, and and that right? There was kind of the the

76
00:11:19.960 --> 00:11:34.279
Derek Cassese: one of the answered one of my big questions, right? So not to confuse it. You know these are all separate products. But th, these are. This is an evolution of a product that has, you know, evolved over time, and is now a pretty important piece to this larger

77
00:11:34.660 --> 00:12:01.760
Andy Whiteside: puzzle that we're we're solving when it comes to leveraging data for business data, driven businesses. AI, etc. So going back to our commercial about, hey, are you working with a partner that's really trying to educate you and get you up to speed. I don't know if you watch college football, pro football on Youtube TV these days, but every time I turn it on. I'm always, you know, an hour late, or whatever. I am always late. And it says, Would you like to watch the key place to figure out how we got here. I'm like, well, heck, yeah, boom.

78
00:12:01.810 --> 00:12:16.060
Derek Cassese: that's what we do as a partner. So I do this podcast too. So that we can try to bring some of that stuff stuff to the surface, because sometimes, just understanding where it came from and what the the naming things, the history of the names. It just makes it all makes sense.

79
00:12:16.170 --> 00:12:18.209
Derek Cassese: Yeah. And it just clears it up, because.

80
00:12:18.310 --> 00:12:47.330
Derek Cassese: you know, it's it's hard with the, with the renaming. And and who knows? Right? It may not. It may change again. But it's important to understand right now that when we talk about salesforce data cloud. Right? That's the evolution of that product center stage at Dreamforce this year, Derek. It's not. It may change, it will change. They're they're doing what they have to do to get the technology in front of the people with the right name. It's it's just how it works, just how it works. We all can't be coca cola forever. And, by the way, they even try to change the name at some point

81
00:12:48.710 --> 00:12:51.760
Andy Whiteside: alright. Anything else around the history of data Cloud. You want to cover?

82
00:12:52.520 --> 00:12:55.160
No, I think that that's that was basically the

83
00:12:55.550 --> 00:13:02.909
Derek Cassese: the really important piece from my perspective was just following that Yup. And and I will say, actually, yeah, there is. One more thing is that

84
00:13:03.150 --> 00:13:10.479
Derek Cassese: one of the last sentences in this section was, you know, salesforce is built a general purpose, data, lake.

85
00:13:11.600 --> 00:13:29.920
Derek Cassese: And I and I find that to be an important sentence, because that's what you know. You can think of this as is a data link, right? You can think of it as data flowing in from not, you know, from various third party systems. But it's it's tightly integrated with your Crm.

86
00:13:30.560 --> 00:13:31.320
Andy Whiteside: yeah.

87
00:13:32.130 --> 00:13:38.479
Andy Whiteside: So, Dirk, the next section says how data harmonization was achieved in the past.

88
00:13:38.730 --> 00:13:47.479
Derek Cassese: Just like everything else, you know, knowing the knowing, the history of this is super valuable to figure out where we're going next. So how do we cover that? Yeah. So this is

89
00:13:47.520 --> 00:14:07.769
Derek Cassese: so, I like to look at this section very similar to how you might explain how AI used to be done like 10 years ago, right? And data scientists, you know, they would spend a lot of time. And very few people had access to that type of technology. And if you were to list how to do it, it would. You know, you'd have a lot of steps, and it would be very difficult. Thus a lot of people didn't use it.

90
00:14:08.560 --> 00:14:17.299
So what this is talking about is how data harmonization was achieved in the past. And it's, you know, there's a lot of steps here. Acquire a data cloud warehouse

91
00:14:17.320 --> 00:14:34.430
Derek Cassese: build what they call it Star schema. They go through, you know, taking an Enterprise service bus that you can drill into and learn more about. That's basically, you know the communication channels, right? Etl jobs there. Basically, what this is is showing is that it was hard

92
00:14:34.640 --> 00:14:43.450
Derek Cassese: to do this right to perform data harmonization. Was not a trivial task. And to contrast that

93
00:14:43.470 --> 00:14:47.519
Derek Cassese: with what you're able to do now with data cloud.

94
00:14:47.680 --> 00:14:48.580
Derek Cassese: it's

95
00:14:48.860 --> 00:14:53.140
Derek Cassese: clicking. It's declarative meaning. It's it's clicks with the mouse

96
00:14:53.250 --> 00:15:07.069
Derek Cassese: to map your data points between salesforce and other systems. Right? And so you're saving, like massive amount of time to connect these systems. And like, they give an example. You know Google cloud sap payment system. Whatever it is, you have

97
00:15:07.120 --> 00:15:09.509
Derek Cassese: right? You can connect those

98
00:15:09.560 --> 00:15:17.769
Derek Cassese: in a visual way with the harmonization. Piece of data cloud. And how you actually do that

99
00:15:18.000 --> 00:15:39.719
Andy Whiteside: there, to me that sounds like a a see it to believe it. Kind of thing which is easily demonstratable these days. Had a moment the other day. Where I forget rocket money or something is some app they advertise all time, and I saw the Commercial where it actually just added all your streaming services into one place and hit a button that says, Show me where I'm spending too much money when I saw that. Bring that data together. That app.

100
00:15:39.780 --> 00:15:46.480
Andy Whiteside: they brought data together. It's pulling it from all these different places versus putting all. One place like this is but just just magical.

101
00:15:46.500 --> 00:15:49.880
Andy Whiteside: What that means to me from a consumer perspective.

102
00:15:49.940 --> 00:15:55.290
Derek Cassese: Yeah? And I think that so and what salesforce has done is pretty smart in that.

103
00:15:55.320 --> 00:16:13.440
Derek Cassese: you know. If you've got Enterprise edition or hire, you can go and provision your own data. Cloud. Oh, how I do that. Okay, go to your account, go into your products, and you'll notice that there's a data cloud there for $0. You click, add it to the cart check out. You have to, you know, fill a couple of things out. And

104
00:16:13.490 --> 00:16:20.190
Derek Cassese: you know, in a couple of hours or whatnot you'll have access to data cloud. And that is the the whole point. Right now. The barrier

105
00:16:20.280 --> 00:16:27.850
Derek Cassese: to entry to this type of technology is, you know, is completely simplified.

106
00:16:27.960 --> 00:16:36.469
Andy Whiteside: You don't. You don't have to hire a whole team to do this or set up a whole project, or, you know, Master Project, it's it's within reach. But yeah. And what I will say, though, is that

107
00:16:36.570 --> 00:16:39.049
Derek Cassese: while it's that easy, it doesn't

108
00:16:39.530 --> 00:16:45.439
Derek Cassese: remove the fact that you really, you know, you really should understand why you're doing it

109
00:16:45.510 --> 00:17:10.119
Derek Cassese: right. Understand where you are in the salesforce journey, where you know how mature is your environment? Do you have a lot of systems that you wanna you know that you wanna put together. There's one thing you don't wanna do is just, you know, set this up and kinda learn as you go in your live environment. And that's kind of where you know partners like us come in where we can actually sit down and do that mapping.

110
00:17:10.250 --> 00:17:17.509
Andy Whiteside: I think that's really important for for folks to understand. Yeah, yeah, just because it's a click away doesn't mean you should just do it without some

111
00:17:17.650 --> 00:17:18.569
Andy Whiteside: pre-work.

112
00:17:18.720 --> 00:17:26.850
Andy Whiteside: Correct. And I get out of jail plan, too. By the way, yes, absolutely. What do we call that? A

113
00:17:27.130 --> 00:17:31.570
Andy Whiteside: I'm I'm drawing a blank here. But the the fallback, our fallback method.

114
00:17:31.580 --> 00:17:34.790
Derek Cassese: Yeah, yeah, yeah. Feel safe.

115
00:17:34.940 --> 00:17:43.920
Derek Cassese: yeah. And then they, you know, they show you know, and those for those that are listening can't see this, but it's a it's a capability map, and I'm a big fan of capability maps, because it shows.

116
00:17:44.140 --> 00:17:54.619
Derek Cassese: you know it'll it'll either show that you're holistic across a lot of different use cases and or tactical across one use case. And what this is showing is that this solution

117
00:17:55.090 --> 00:18:02.919
Derek Cassese: is very holistic across, you know, a lot of different use cases, storage, big data, engine data, transformation, etc.

118
00:18:03.210 --> 00:18:06.639
Derek Cassese: So it's very, you know. It's it's a pretty strategic.

119
00:18:06.900 --> 00:18:10.710
Derek Cassese: It's a pretty strategic piece of the platform

120
00:18:10.990 --> 00:18:16.570
Andy Whiteside: now is that mapping exercise and visual? Or see on the screen. Here is that part of the product, or is that something you do in parallel?

121
00:18:17.100 --> 00:18:44.719
Derek Cassese: Well, this is this. So? Capability mapping is something that a lot of the salesforce. Technical architects will do with customers. And what they're showing here is they're just articulating what? Where this play. So, for example, you know where you see the where you see the product circle icons. That's means that certain products and the key up is up at the top Wi, you know where the products play right, showing that they've got solutions across all of these pieces.

122
00:18:45.200 --> 00:18:52.070
Derek Cassese: So this is this is a part of the product. It's a visual. It's a visual guide to help, you understand where these products fall.

123
00:18:52.270 --> 00:19:05.410
Andy Whiteside: Well, and that's another opportunity to do a little brief commercial. Here we are following Salesforce's services, consulting services methodology. So if you're working with us, you're gonna get this type of capability mapping as part of your engagement.

124
00:19:06.850 --> 00:19:27.589
Derek Cassese: Yeah, yeah, capability mapping is a really is a really useful tool that I don't think is used enough. But that's basically what that was showing. Alright. So the next section talks about salesforce data cloud differentiators. You want to cover that. I think I mentioned this. But it's it's pre wired to the odd, to the salesforce objects, meaning that

125
00:19:27.930 --> 00:19:30.260
Derek Cassese: you know the

126
00:19:31.050 --> 00:19:43.130
Derek Cassese: standard objects are available right there, so that you don't have to. You don't have to bring that whole schema in essentially what it looks like is, you know, you'll have. For example, you may have.

127
00:19:43.650 --> 00:20:00.469
Derek Cassese: instead of account. Id. It may be, you know, a id or act Id or some other field name coming from a third party system. And you can basically connect that to the appropriate field on the Crm side, so that it understands that it's the same account. It's the same person.

128
00:20:00.680 --> 00:20:12.539
Derek Cassese: It's all pre-wired right, and that's the whole point of it's easy, and you don't have to do all the schemas for everything. And you know that's the the other interesting thing here for industries is.

129
00:20:12.840 --> 00:20:20.450
Derek Cassese: you know, II come from a background in health and life sciences where I where I was with salesforce, you know. So you got health cloud and the health cloud data model.

130
00:20:20.490 --> 00:20:39.870
Derek Cassese: The industry. Did you know it's supporting a handful of these already that the industry data models right? So that goes into the concept of alright, if you're bringing things in from a third party solution and you've got a patient. Well, now, you can start, you know, matching that stuff up as well, and then.

131
00:20:39.940 --> 00:20:53.099
Derek Cassese: you know, I would just get out of the trust layer. This was something that was announced at Dreamforce as well. The Einstein Trust layer. And this is where we get into. Okay, this is all great. We've got this. AI, we've got, you know, generative. But how do we protect this

132
00:20:53.100 --> 00:21:11.780
Derek Cassese: and so the Einstein Trust layer is. You know how Salesforce is addressing that where you're able to mask particular information, so it doesn't get thrown into large language models. You're able to mask that data so that you understand what is and is not being used for particular AI features.

133
00:21:11.780 --> 00:21:17.380
Derek Cassese: Oh, it's awesome and and necessary. Very necessary. Yes.

134
00:21:18.130 --> 00:21:20.169
Andy Whiteside: anything else in this section, Derek.

135
00:21:20.390 --> 00:21:27.490
Derek Cassese: I think that's that's it. I mean, we I didn't get to too much prompt engineering is another bullet there.

136
00:21:27.610 --> 00:21:34.330
Derek Cassese: But that's probably a topic for another day. I mean, prompt is really all around. You know

137
00:21:35.050 --> 00:21:37.930
Derek Cassese: how you you know how you interact with these AI

138
00:21:38.180 --> 00:21:44.919
Derek Cassese: models. Prompt engineering is another whole section. And so I will just say that.

139
00:21:45.200 --> 00:22:05.700
Derek Cassese: you know, prompt studio is something that was announced at dreamforce, which is gonna allow admins to create user prompts. Right? So and what that means is like, what are you asking for? And that's them interacting with these generative AI solutions. That's kind of a Tbd, that's not out yet, I don't believe but that's gonna be baked in as well

140
00:22:05.830 --> 00:22:11.599
Derek Cassese: to the, to the data cloud. And the other thing. It's not really mentioned here. But I know you can do this is, you can trigger

141
00:22:11.660 --> 00:22:18.250
Derek Cassese: in data cloud on on data events. So if if it notices a change in data.

142
00:22:18.270 --> 00:22:30.839
Derek Cassese: I can trigger a flow within salesforce to do something, and that you know anybody that's knows flow. You can start thinking about all the things you could possibly do when data changes automatically.

143
00:22:31.120 --> 00:22:34.759
Andy Whiteside: And not only that, but yeah, yes.

144
00:22:35.120 --> 00:22:47.240
Andy Whiteside: Dinner to AI great. You can still have it, in most cases, in many cases, at least for a little while, or maybe forever, that that human interaction, and how to how to get it going in the right direction, so that you can then take the output and

145
00:22:47.300 --> 00:22:49.250
Andy Whiteside: do whatever the human needs to do with it.

146
00:22:49.380 --> 00:22:50.180
Derek Cassese: Yep.

147
00:22:51.170 --> 00:22:59.529
Andy Whiteside: Next section talks about the future of data cloud. Just kinda tell us what they're covering here and then jump into these individual call outs, if you want.

148
00:23:01.140 --> 00:23:13.740
Derek Cassese: Yeah. So like, we said, it's been, it's been 2 years, you know, it's been since 2020 with different releases and updates and names, and you know that you know, salesforce does releases 3 times a year.

149
00:23:14.030 --> 00:23:21.579
One that just went out recently in October winter, 20 winter. 24, or winter. 20. Yeah. Winter, 24,

150
00:23:23.330 --> 00:23:34.479
Derek Cassese: winter, 23. Gonna get my years, Max mixed up. But so essentially, what this is calling out is, you know. Where is this going? Right? Where? W. What can we expect? III you know, mentioned the prompt suite.

151
00:23:35.120 --> 00:23:37.320
Derek Cassese: So Einstein Gpt.

152
00:23:37.590 --> 00:23:42.370
Derek Cassese: Is something that you know we need to keep an eye on, because.

153
00:23:42.450 --> 00:23:52.799
Derek Cassese: you know, you know just as well as I do, Andy. When we were at Dreamforce there was a whole lot of generative AI capabilities that were are and being baked into this to this product.

154
00:23:52.850 --> 00:24:08.209
Derek Cassese: So you know, Einstein Gpt is something that I think most people are gonna wanna look into as far as how it can enable their sales. You know their sales, force their sales, reps and whatnot. They're leveraging. The Crm

155
00:24:08.370 --> 00:24:17.720
Derek Cassese: did like I mentioned data cloud for industries. So I think that's gonna continue to mature to to cover more industries as time goes on and then

156
00:24:17.850 --> 00:24:27.299
Derek Cassese: it calls out closing the skill gap which I thought was interesting. And this is all about, okay, this is great. But we're starting to get into some new areas. I mean.

157
00:24:27.600 --> 00:24:30.079
Derek Cassese: I even heard at Drinkor's like a new.

158
00:24:30.170 --> 00:24:39.940
Derek Cassese: a new job role. Prompt engineering is has been born. That's pretty interesting, right? And so this is just talking about the skills that are required

159
00:24:39.970 --> 00:24:56.200
Derek Cassese: to manage and maintain the things that we've talked about developer skills, you know, for implementing and updating events that are coming into the data cloud data management skills, analyst skills. And this I mean. This again, you know, is where I think

160
00:24:56.530 --> 00:25:05.639
Derek Cassese: you know, partners like ourselves and the partner ecosystem can really help customers. you know. So from a skill gap, perspective.

161
00:25:06.010 --> 00:25:09.499
Derek Cassese: No, this is this is where you know, getting

162
00:25:09.660 --> 00:25:19.679
Derek Cassese: getting us involved or talking with with somebody early in this, you know, in the process of this, so that you understand where you are, where you want to be, where you're going.

163
00:25:19.690 --> 00:25:23.459
Derek Cassese: To call these skill gaps out early is important.

164
00:25:23.860 --> 00:25:24.650
Andy Whiteside: right

165
00:25:26.900 --> 00:25:30.150
Andy Whiteside: and to the point where it's essentially a full time

166
00:25:30.290 --> 00:25:31.520
Andy Whiteside: role

167
00:25:31.680 --> 00:25:37.749
Andy Whiteside: on the prompt engineer side, like you call my attention big time when you saw some of the prompt engineer role. Like, what?

168
00:25:37.990 --> 00:25:39.359
Andy Whiteside: What would that person do?

169
00:25:39.640 --> 00:25:47.269
Derek Cassese: Yeah. So it's it's it's really about how you're interacting with the AI, and and I'll be honest, I mean, that's a that's a whole area that I'm not.

170
00:25:47.380 --> 00:26:09.359
Derek Cassese: I mean, it's new, right? So I'm not as familiar with prop engineering myself yet. So it's it's exciting. And I think that's the you know anybody that works in, you know, in this type of field and whatnot. We all know that you know, what we did 10 years ago is is not necessarily used today. What's new today is, you know, is new. So you gotta you gotta catch up. And

171
00:26:09.460 --> 00:26:13.969
Derek Cassese: but from a from a perspective of like prompting, I mean, that's.

172
00:26:14.310 --> 00:26:21.430
Derek Cassese: you know. That is how you interact. My understanding is how we're going to interact with these AI models and generative AI models.

173
00:26:21.470 --> 00:26:26.130
for example, instead of pulling up, you know, pulling up Chat Gp and saying.

174
00:26:26.340 --> 00:26:37.380
Derek Cassese: You know. you know. write me a message right? It's going to write something really random and generic. But if I said I really would like a message written about

175
00:26:37.990 --> 00:26:45.459
Derek Cassese: salesforce data cloud so that I can understand it and explain it to a 7 year old. Right now, you've actually.

176
00:26:45.600 --> 00:26:52.359
Derek Cassese: I've given it a lot of information, right? And that's the that's kind of a prompt for the AI model.

177
00:26:53.060 --> 00:27:07.000
Andy Whiteside: And so the more information, the more information you feed into these, the more accurate and actionable the response from these tools are going to be. And that's gonna be, that's the human human skill. But somebody needs to help teach, educate, transition translate.

178
00:27:07.340 --> 00:27:08.220
Derek Cassese: Yes.

179
00:27:08.430 --> 00:27:11.870
Andy Whiteside: the lack humans, lack of knowing what to put in

180
00:27:12.550 --> 00:27:19.610
Andy Whiteside: versus the tool's ability to produce it. Alright, anything else on this section around the future data cloud.

181
00:27:19.890 --> 00:27:23.969
Derek Cassese: I think that's you know. That's that's it. For that. I mean.

182
00:27:24.100 --> 00:27:28.530
Derek Cassese: I think we covered most of that area just to understand, you know. Again, you know.

183
00:27:28.570 --> 00:27:34.579
Derek Cassese: the Einstein Gpt stuff, the data cloud for industries. The gaps was really what that section's talking about.

184
00:27:35.130 --> 00:27:41.490
Andy Whiteside: Okay, so it goes. This goes to this point. Now, sorry for all the trying to get the words out summary like.

185
00:27:41.660 --> 00:27:45.490
Andy Whiteside: what does this mean after reading this blog?

186
00:27:45.660 --> 00:27:48.539
Andy Whiteside: Where is this going? What should happen next.

187
00:27:49.900 --> 00:27:59.110
Derek Cassese: Yeah. So you know. And they mentioned in this in this article that you know, data cloud could be described as the Holy Grail of Crm. It's pretty

188
00:27:59.780 --> 00:28:07.620
Derek Cassese: pretty bold statement. In that. The data problem that's been there for a long time is solvable. And

189
00:28:07.840 --> 00:28:11.790
Derek Cassese: so the data problem being that we've got data silos.

190
00:28:11.810 --> 00:28:22.699
Derek Cassese: And you know, right hand doesn't know what the left hand is doing. And or you're managing different environments with duplicate data. You don't have a true end end vision

191
00:28:22.780 --> 00:28:28.349
Derek Cassese: of your customers. Right? That that is where we're at right now. And I, you know

192
00:28:28.620 --> 00:28:31.080
Derek Cassese: I suggest everybody.

193
00:28:31.640 --> 00:28:39.609
Derek Cassese: you know, at least get educated enough so that you understand, you know what data Cloud could potentially do for your business, how you could leverage it.

194
00:28:39.840 --> 00:28:55.970
Derek Cassese: Obviously, there's you know, you could reach out, reach out to us. You could go out and take, you know, trail head. There's a lot of resources out there to, you know. Kinda get, you know. Get your foot in the water on this but this is gonna be a foundational piece

195
00:28:56.150 --> 00:28:59.560
Derek Cassese: of what they're calling the Einstein one platform

196
00:28:59.780 --> 00:29:12.449
Derek Cassese: which you know as we as we progress. And we start adding all these capabilities to the sales force. platform. You know, Einstein, one platform data cloud is going to be right at the center.

197
00:29:13.280 --> 00:29:16.870
Andy Whiteside: Well, you you brought up several times in our conversations now that

198
00:29:17.570 --> 00:29:37.759
Andy Whiteside: crypto and blockchain was all the rage a couple of years ago. So whether you know AI, you know, comes and goes without a doubt, what salesforce is doing here around getting data in a centralized, manageable, usable location. That is a guaranteed thing that has to continue to evolve.

199
00:29:38.050 --> 00:29:40.350
Derek Cassese: Absolutely. Right?

200
00:29:40.680 --> 00:29:44.220
Derek Cassese: I mean, if you want to like.

201
00:29:44.350 --> 00:29:54.910
Derek Cassese: compete with what the expectations are from a perspective of customers and where we're at today, you know, I you've got to be able to know, and all touch points.

202
00:29:54.960 --> 00:30:03.730
Derek Cassese: You need to be able to know that, and the only way to do that is to be able to combine all the touch points from various systems unless you're using one system which, as I mentioned, nobody's using one system.

203
00:30:03.960 --> 00:30:15.210
Derek Cassese: right? 900 plus 1,000 plus, I mean, there's multiple systems. So that's that's where we're at. And that's that's not gonna change. But harmonizing this so that you can actually leverage the data.

204
00:30:15.510 --> 00:30:17.489
Derek Cassese: embrace the A I

205
00:30:17.630 --> 00:30:33.589
Derek Cassese: to a point where it's actually, you know, enabling your business is is where we're at with this. And it's it's exciting. I think this is a really interesting piece, and a really interesting addition to an already impressive suite of tools that Salesforce has.

206
00:30:34.950 --> 00:30:44.649
Andy Whiteside: They're in an interesting spot. They have all this customer and user data. And you know, like you said, companies that are have tried to use one platform know that they can't.

207
00:30:44.840 --> 00:30:58.089
Andy Whiteside: A lot of companies are just given up on the idea, and they're they got the sprawl going on and that that may happen by business unit may happen by department may happen by both. You know the the centralized data lake

208
00:30:58.170 --> 00:31:12.010
Andy Whiteside: concept that's, you know, there, and ready to be consumed by things like AI and other salesforce related products. And third parties like, okay, I didn't ask that other. Once you have data cloud, what stops other

209
00:31:12.190 --> 00:31:16.560
Derek Cassese: platforms or products from using this data cloud. Nothing really right? No.

210
00:31:17.420 --> 00:31:30.660
Derek Cassese: But even so, I mean, so the data cloud is integrated into the like. If you look at an architectural diagram of the salesforce platform. Einstein, one platform. It's in the middle. It's in the center part. So

211
00:31:30.740 --> 00:31:42.709
Derek Cassese: it's essentially provisioned into your salesforce org. And it is the traffic cop out to the third party products. The third party product isn't going to be able to pull.

212
00:31:43.280 --> 00:31:50.369
Derek Cassese: you know, like that. That schema and a third party product is doesn't know about data. Cloud data. Cloud knows about it.

213
00:31:50.490 --> 00:31:53.840
Derek Cassese: Right? That makes sense. Right?

214
00:31:53.910 --> 00:32:01.179
Derek Cassese: and there's other. You know, there's other solutions out there like we mentioned that. Do this right. There's manual solutions out there. You could do your own daily.

215
00:32:01.200 --> 00:32:12.049
Derek Cassese:  so this isn't the end. All be all but from a perspective of salesforce. If you've got the Crm, I mean, this is a no brainer to

216
00:32:12.210 --> 00:32:22.059
Derek Cassese: to many right. And the the exciting thing, too, is that you know. we the integra, I mean, we are gonna go down this path as well. Right? So as

217
00:32:22.510 --> 00:32:33.349
Derek Cassese: time goes on, you know, we'll probably have future podcasts to update kind of where we're at on that journey talked about. So yeah, we didn't say that in the commercial, but with almost all products that we

218
00:32:33.400 --> 00:32:35.620
Andy Whiteside: consult around, we use them.

219
00:32:35.660 --> 00:32:44.559
Derek Cassese: and we are a working example of what to do in some cases, what not to do. But you know things that can be shared with customers who are in the same boat.

220
00:32:45.630 --> 00:32:54.860
Andy Whiteside: And on that note we've got our own nonprofit. We've got to move from success cloud to nonprofit cloud. At some point you mentioned that data cloud might be the key element.

221
00:32:54.970 --> 00:32:58.590
Derek Cassese: to be determined. Right? Yeah. Tbd, on that

222
00:32:59.080 --> 00:33:10.919
Derek Cassese: you know, doing a little bit of research on, you know where we're at with nonprofit cloud and and whatnot. So there's still a couple of things to to iron out on that. I know nonprofit cloud is is fairly new.

223
00:33:11.330 --> 00:33:23.839
Derek Cassese: But you know, from my perspective, the you know, the data cloud is is important in almost all aspects of what you're doing. I mean, unless you, unless you really don't have. unless you have everything in salesforce. And that's it.

224
00:33:23.860 --> 00:33:40.349
Andy Whiteside: Right, then it would. You don't have the need to harmonize data from other areas, then this is this is a solution that needs to be looked at. Well, but like in this case, if you had everything in salesforce which there may be some nonprofits that got on board early and put everything there, but they now have to move to nonprofit cloud. They still have the problem.

225
00:33:40.920 --> 00:33:49.180
Derek Cassese: Yeah, yeah. And that's and that's a that's the OP. You know, a topic for another another session for for us to dig into. But yeah, it's

226
00:33:49.260 --> 00:33:51.639
Derek Cassese: it's gonna be interesting to see where

227
00:33:51.800 --> 00:34:03.459
Derek Cassese: you know, because we all know right in the beginning, in the beginning stages some of these things, the use cases are what you think they are. And then what happens is people start using it, and all of a sudden you realize people are using it in different ways.

228
00:34:03.720 --> 00:34:17.240
Derek Cassese: So it's gonna be really interesting to see what those different ways are. And I think one of those different ways could be assisting in what you just said. Right? Assisting in some of the the nonprofit areas. How about this? They're the only thing consistent is change.

229
00:34:17.449 --> 00:34:31.640
Andy Whiteside: and the only reality around that is the data that was part of the the Pre. Before the Pre. Before the Pre is still relevant. If you know how to put it somewhere, you can use it and how to leverage it. Yep, that data is always valuable

230
00:34:32.010 --> 00:34:33.899
Andy Whiteside: if you have it where you need it.

231
00:34:34.179 --> 00:34:50.379
Derek Cassese: It's like, I just moved. I got a ton of stuff in a storage unit right now I start to think about what I need. I don't have the storage unit organized to the point where I can find stuff, so I might as well not even have it at this point. Yeah, you can't get to it. You don't know where it is. It's not organized, right? So it's

232
00:34:51.380 --> 00:34:58.449
Derek Cassese: yeah. It would take you. It would take you forever to get the stuff you need is exactly. That's the same thing with all, with the separate systems. Right?

233
00:34:58.820 --> 00:35:13.730
Andy Whiteside: But I will change. I will add this to it, and maybe this is where I'm at 50 years old. Gotten smarter. It's it's a single storage unit. It's a big storage unit. I left space to walk through the storage unit, and instead of putting things in brown boxes, they're in clear plastic storage containers

234
00:35:14.580 --> 00:35:18.670
Derek Cassese: right? So you? So what that shows is that you know that you need a better system.

235
00:35:18.690 --> 00:35:44.539
Derek Cassese: Right, you know that you need a better system to help you find the stuff. But you're still having to go and find the stuff. Yeah, and we go organize it again at some point soon, and and put things by buckets, and but I'll be able to see into the containers versus trying to read the marker writing on the side of it, which probably wasn't right anyway, else walks in there and doesn't understand the way that you organize it.

236
00:35:44.850 --> 00:35:48.020
Derek Cassese: Right? Do they understand what's what and what's where. That's

237
00:35:48.200 --> 00:36:04.340
Derek Cassese: that's the interesting part of that, too, right is that you know, the the goal is to harmonize and get data to a point where it's just usable and consumable from the folks that wanna use it. I mean, quite frankly, it shouldn't matter how that's done for somebody that's using it. Just like, you know, in your example.

238
00:36:04.570 --> 00:36:10.050
Andy Whiteside: that system works great for you, but so you know, if I walked in there, I may not know what's what

239
00:36:10.680 --> 00:36:13.380
Derek Cassese: part of the part of the process.

240
00:36:13.780 --> 00:36:18.220
Andy Whiteside: Well, Derek, appreciate you doing this on a Friday afternoon? We we

241
00:36:18.460 --> 00:36:33.039
Andy Whiteside: you wanted to get this one done. We didn't wanna skip a week on this salesforce podcast because it's it's paramount to what we're doing. It's a paramount to the business, you're building. And we know no, no, no. There's a ton of customers out there that need salesforce help that

242
00:36:33.080 --> 00:36:36.370
the way we do it, it's gonna be different. And we're gonna be able to help them.

243
00:36:36.590 --> 00:36:42.840
Derek Cassese: Yeah. yeah, these are. These are good. These are fun. I mean, we're all learning on some of the new stuff as we go. And

244
00:36:43.390 --> 00:36:59.800
Derek Cassese: you know, this is this is just gonna continue. We're gonna keep going through these things. And hopefully, hopefully, you know, we might have solved or answered a couple of questions to to the you know, some people listening to this. That would be great. Right? Cause that's what we're trying to do is is like the title, simplify some of this stuff.

245
00:36:59.910 --> 00:37:05.120
Andy Whiteside: Alright, Derek, I know you don't have a great answer to this one. When is your next

246
00:37:05.200 --> 00:37:20.410
Andy Whiteside: salesforce specific? What we call blueprint launch user peer discussion. Event coming up. II know you got a bunch that are going to come up as you start to have these on the calendar. I want to highlight them. They're all going to kick off next year.

247
00:37:20.520 --> 00:37:47.220
Derek Cassese: You know. And we're you know, we're targeting areas, you know, like Charlotte, North Carolina, Greensboro, North Carolina, Raleigh, New York, Florida. You know, just to name a few, but they're getting scheduled right now, and you know I'm looking forward to getting those things on the calendar and booked, and, you know, start getting some folks signed up for them. Yeah, I'm excited about it. It will essentially be our version of a Zintra salesforce specific user group

248
00:37:47.320 --> 00:38:03.890
Derek Cassese: thing. And that's not to diminish the salesforce user group. We're gonna participate in those and encourage people to go to those. But we're gonna we're gonna do more. And we're gonna do them, you know, focused around topics and around people talking about those topics openly with each other.

249
00:38:04.030 --> 00:38:14.249
Derek Cassese: You know what I enjoyed the most, and dreamforce is the peer to peer discussions right talking with other people that are there and learning about what they're doing and how they're solving. And that's

250
00:38:14.380 --> 00:38:22.750
Derek Cassese: what's gonna happen at these events. Let's get. Let's get folks in a room together. Let's start talking through how somebody's solving one issue. What's used case, are you using this for? And

251
00:38:22.820 --> 00:38:45.990
Derek Cassese: yeah, let's let's continue that you know that community that you saw and everybody that goes to dreamforcees. Let's continue that throughout the year, the the products these platforms are limitless, like literally limitless. But the conversations that need to happen in parallel are also limitless. Yeah, alright, sir. Have a good weekend, and we'll do it again next week. Sounds good.