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Today on the Salesforce Admins Podcast, we talk to Abhishek Saxena, Technical Architect at Copado. Join us as we chat about how he learned Data Cloud and why understanding context is the key to making Agentforce shine.
You should subscribe for the full episode, but here are a few takeaways from our conversation with Abhishek Saxena.
As a developer and architect, Abhishek isn’t lacking for technical knowledge about the Salesforce platform. But even he found it hard to get his head around what Data Cloud was and what it could do.
Abhishek attended community events, scoured LinkedIn posts, studied videos, and even read a book about Data Cloud. But there were so many new terms being thrown around, and he still couldn’t explain the difference between a data lake object, a data model object, and a data source object.
“Even though there was a lot of buzz around Data Cloud and how it is such an amazing, innovative solution,” Abhishek says, “I was not able to grasp what it does in an easy fashion.” Luckily, he had an “aha” moment that helped him see the big picture, and so he’s giving a presentation at Dreamforce to share what he’s learned.
Abhishek’s talk, “A Beginner’s Guide to Data Cloud,” will get you up to speed in 20 minutes or less. As he explains, the main thing to understand is that Data Cloud is about data unification.
If you have your data in a bunch of different places, you used to have to dedicate significant developer time to maintaining APIs that allowed Salesforce to share information with your other platforms. With Data Cloud, you have everything on one record, with Salesforce and Slack as the front door. You have a complete 360 view of your customer, regardless of where the information is.
Getting a complete picture of your customers is doubly important when it comes to Agentforce. AI agents are extremely context-dependent: they do a much better job when you “ground” them with extra parameters.
As Abhishek says, “If you give agents good data, your responses are going to be much more personalized and better.” Data Cloud allows you to give your AI agents a much more specific picture of your customers, opening the door for better and more effective automations.
If you’re coming to Dreamforce, make sure to come to Abhishek’s presentation so you can be a Data Cloud pro. And don’t forget to subscribe to the Salesforce Admins Podcast so you never miss an episode.
Social
Mike:
Abhishek:
Mike:
Abhishek:
But getting into Salesforce, that was a happy coincidence. My hometown, where I’m originally from, it’s called Jaipur, it’s in India, and that’s where I did my engineering from as well, Jaipur is traditionally not touted as a tech hub, but for some divine reasons there were several Salesforce consultancies that were trying to make it big in that area when I was just graduating, I got an offer to work for one of them as a Salesforce consultant after a series of intense grueling interviews. But yeah, that’s how I got started, and I have never looked back since then.
Mike:
Abhishek:
Mike:
Abhishek:
Mike:
Abhishek:
So Trailhead modules weren’t baked out completely. There weren’t any demo environments that I could get hands on, and it just felt a little bit overwhelming. I knew my friends who were doing Marketing Cloud, Einstein, CDP, that sort of stuff, knew what was going on, but us commoners who were just working on the core clouds.
Mike:
Abhishek:
Mike:
Abhishek:
But at this point, now I had several months of experience trying to learn Data Cloud, I thought that, okay, let me go ahead and do the Data Cloud certification as well just to quiz myself if I know enough. I did that and I passed. So that was the validation I was seeking that, okay, now I am somewhat of a Data Cloud consultant. But I wanted to share this journey with everyone else because I consider myself fairly technical with a consultant and a developer background, and if it took me a lot of time to get through, then I would not blame anyone else in the ecosystem who’s not as technical to not completely understand that, Hey, why Data Cloud? What is Data Cloud? Why is this important? So that’s why I thought that yes, I need to share my knowledge with everyone else.
Mike:
Abhishek:
Mike:
Abhishek:
So I’ll try to explain this and I go into much more detail in my session as well. If anyone in our listeners is in the attendance, I would love to have you in my session. But just to give you a recap or a quick preview of what I’m going to talk about is that let’s say your company uses Salesforce, your company also uses SAP for something else. Your company maybe uses Trello for tracking some stuff as well. So you have your record your identity as, since my name is Abhishek, all these systems have my identity there in SAP or ServiceNow, Abhishek can do certain things, maybe that has my personal email for some reason, or maybe a different phone number. And then the Abhishek on the Salesforce ecosystem, that record, that contact or user, has slightly different details. Maybe the address I put in is different. Maybe the phone number I put in is my work phone, and in the other one I put in my personal phone.
So what Data Cloud ends up doing is that from these different identities of Abhishek that exist in these separate platforms that are not linked, it allows you to create one record where all of your identities are linked. So in case I want to get Abhishek’s email in SAP, I can just call out to Data Cloud and Data Cloud will give that to me instead of myself having to write three or four different APIs trying to de-duplicate records, trying to find some common way or how it’s called an external key of linking that, okay, this Abhishek in Salesforce and that Abhishek in SAP are the same person.
Data Cloud takes all of that complexity out of this and just tells you that, okay, Abhishek’s record exists in five systems, here are the values of different things in those five systems. And I could just get that. So once I understood this, I was like, wow, this unified data that Data Cloud is giving you could have so many ramifications. And that’s again, one of those things that I explored in that presentation that how agents that need this sort of information can benefit from Data Cloud.
Mike:
And so you would have these really robust time management or project management apps and the platform could more than easily handle it. And you didn’t have to be a coder, you could build a project management app with a few objects and a couple dozen fields and some relationships, and there you’re ready to go. And then it kind of became like, well, wait a minute, why are we spending all this time building on this platform when we can just connect things? But there was no sense of unification there. And I think in your description, what I heard is finally now you can have an entire enterprise where the front door is Salesforce or Slack and it can access all of that data and you’re getting a complete view of a customer regardless of where the system information is, and that allows other applications and other things to run and do their job just well, but you still get that unified pull back in, and then you don’t have the burden of a developer maintaining 200 APIs on the back end.
Abhishek:
Mike:
Abhishek:
Mike:
Abhishek:
Mike:
Abhishek:
Now, if you provide the agent with good context that whenever agent responds, it knows that I’m working for Coral Cloud Resorts, I am responsible for handling bookings, I can refund things, I can access customer details and which objects to look at, where to get the information from. If your agent has these informations, or again, a simpler example that if you are in ChatGPT and tell it that, okay, I want to write a sales email as a customer service agent for Coral Clouds, my name is Abhishek Saxena, when you start your email, start with the salutation. This is intended to be for the guests who are staying at the resort. And if I give all of these details and then hit enter, the response I’m going to get is going to be a lot more personalized.
And that’s how you can automate it to send to any user that is using your agent. That’s what I mean by why context is so important for any AI to work. And with Data Cloud, as we have discussed in the podcast so far, it gives you that unified profile. It gives you the customer 360 so that your agents have all the information about your particular user who is asking the question or to wherever you’re trying to use it. Because good data, if you give it good data, your responses are going to be much more personalized and better.
Mike:
Abhishek:
Mike:
Abhishek:
So that’s sort of basics of data processing that a typical data engineer knows, but a typical Salesforce consultant, admin developer does not, that was somewhat difficult for me to wrap my head around because in my training on working on Salesforce platform for so many years, I have been accustomed to think about data in terms of objects, Socket queries, and that form. But with Data Cloud, it’s a little bit different. So that was one of the things that threw me off initially, and I had to look at some resources even outside of Salesforce’s Data Cloud trainings to understand that data lake is not actually a lake. Data warehouse is not a big factory in which there are tons of books with data. So yes, that was something that threw me off initially.
Mike:
Abhishek, this has been a fun conversation. I think it’s going to be a very compelling presentation at Dreamforce, but also I think it’s been very inspirational, at least for me, that even the hard stuff is still not that hard to learn. I go back to a saying, everything in the world is created by somebody at some time, and if that somebody can figure it out, you certainly can too. So Data Cloud and Data Lakes was created by somebody, which means they figured it out, so it can’t be that hard for anyone else to figure it out.
Abhishek:
Mike:
Abhishek:
Mike:
So be sure to catch his session if you’re going to dream for us and share this episode with a fellow Salesforce admin maybe who’s also struggling to understand some new technology or just getting started with Data Cloud. Either way, until next time, we’ll see you in the cloud.
The post Making Data Cloud Understandable for Admins appeared first on Salesforce Admins.
4.7
200200 ratings
Today on the Salesforce Admins Podcast, we talk to Abhishek Saxena, Technical Architect at Copado. Join us as we chat about how he learned Data Cloud and why understanding context is the key to making Agentforce shine.
You should subscribe for the full episode, but here are a few takeaways from our conversation with Abhishek Saxena.
As a developer and architect, Abhishek isn’t lacking for technical knowledge about the Salesforce platform. But even he found it hard to get his head around what Data Cloud was and what it could do.
Abhishek attended community events, scoured LinkedIn posts, studied videos, and even read a book about Data Cloud. But there were so many new terms being thrown around, and he still couldn’t explain the difference between a data lake object, a data model object, and a data source object.
“Even though there was a lot of buzz around Data Cloud and how it is such an amazing, innovative solution,” Abhishek says, “I was not able to grasp what it does in an easy fashion.” Luckily, he had an “aha” moment that helped him see the big picture, and so he’s giving a presentation at Dreamforce to share what he’s learned.
Abhishek’s talk, “A Beginner’s Guide to Data Cloud,” will get you up to speed in 20 minutes or less. As he explains, the main thing to understand is that Data Cloud is about data unification.
If you have your data in a bunch of different places, you used to have to dedicate significant developer time to maintaining APIs that allowed Salesforce to share information with your other platforms. With Data Cloud, you have everything on one record, with Salesforce and Slack as the front door. You have a complete 360 view of your customer, regardless of where the information is.
Getting a complete picture of your customers is doubly important when it comes to Agentforce. AI agents are extremely context-dependent: they do a much better job when you “ground” them with extra parameters.
As Abhishek says, “If you give agents good data, your responses are going to be much more personalized and better.” Data Cloud allows you to give your AI agents a much more specific picture of your customers, opening the door for better and more effective automations.
If you’re coming to Dreamforce, make sure to come to Abhishek’s presentation so you can be a Data Cloud pro. And don’t forget to subscribe to the Salesforce Admins Podcast so you never miss an episode.
Social
Mike:
Abhishek:
Mike:
Abhishek:
But getting into Salesforce, that was a happy coincidence. My hometown, where I’m originally from, it’s called Jaipur, it’s in India, and that’s where I did my engineering from as well, Jaipur is traditionally not touted as a tech hub, but for some divine reasons there were several Salesforce consultancies that were trying to make it big in that area when I was just graduating, I got an offer to work for one of them as a Salesforce consultant after a series of intense grueling interviews. But yeah, that’s how I got started, and I have never looked back since then.
Mike:
Abhishek:
Mike:
Abhishek:
Mike:
Abhishek:
So Trailhead modules weren’t baked out completely. There weren’t any demo environments that I could get hands on, and it just felt a little bit overwhelming. I knew my friends who were doing Marketing Cloud, Einstein, CDP, that sort of stuff, knew what was going on, but us commoners who were just working on the core clouds.
Mike:
Abhishek:
Mike:
Abhishek:
But at this point, now I had several months of experience trying to learn Data Cloud, I thought that, okay, let me go ahead and do the Data Cloud certification as well just to quiz myself if I know enough. I did that and I passed. So that was the validation I was seeking that, okay, now I am somewhat of a Data Cloud consultant. But I wanted to share this journey with everyone else because I consider myself fairly technical with a consultant and a developer background, and if it took me a lot of time to get through, then I would not blame anyone else in the ecosystem who’s not as technical to not completely understand that, Hey, why Data Cloud? What is Data Cloud? Why is this important? So that’s why I thought that yes, I need to share my knowledge with everyone else.
Mike:
Abhishek:
Mike:
Abhishek:
So I’ll try to explain this and I go into much more detail in my session as well. If anyone in our listeners is in the attendance, I would love to have you in my session. But just to give you a recap or a quick preview of what I’m going to talk about is that let’s say your company uses Salesforce, your company also uses SAP for something else. Your company maybe uses Trello for tracking some stuff as well. So you have your record your identity as, since my name is Abhishek, all these systems have my identity there in SAP or ServiceNow, Abhishek can do certain things, maybe that has my personal email for some reason, or maybe a different phone number. And then the Abhishek on the Salesforce ecosystem, that record, that contact or user, has slightly different details. Maybe the address I put in is different. Maybe the phone number I put in is my work phone, and in the other one I put in my personal phone.
So what Data Cloud ends up doing is that from these different identities of Abhishek that exist in these separate platforms that are not linked, it allows you to create one record where all of your identities are linked. So in case I want to get Abhishek’s email in SAP, I can just call out to Data Cloud and Data Cloud will give that to me instead of myself having to write three or four different APIs trying to de-duplicate records, trying to find some common way or how it’s called an external key of linking that, okay, this Abhishek in Salesforce and that Abhishek in SAP are the same person.
Data Cloud takes all of that complexity out of this and just tells you that, okay, Abhishek’s record exists in five systems, here are the values of different things in those five systems. And I could just get that. So once I understood this, I was like, wow, this unified data that Data Cloud is giving you could have so many ramifications. And that’s again, one of those things that I explored in that presentation that how agents that need this sort of information can benefit from Data Cloud.
Mike:
And so you would have these really robust time management or project management apps and the platform could more than easily handle it. And you didn’t have to be a coder, you could build a project management app with a few objects and a couple dozen fields and some relationships, and there you’re ready to go. And then it kind of became like, well, wait a minute, why are we spending all this time building on this platform when we can just connect things? But there was no sense of unification there. And I think in your description, what I heard is finally now you can have an entire enterprise where the front door is Salesforce or Slack and it can access all of that data and you’re getting a complete view of a customer regardless of where the system information is, and that allows other applications and other things to run and do their job just well, but you still get that unified pull back in, and then you don’t have the burden of a developer maintaining 200 APIs on the back end.
Abhishek:
Mike:
Abhishek:
Mike:
Abhishek:
Mike:
Abhishek:
Now, if you provide the agent with good context that whenever agent responds, it knows that I’m working for Coral Cloud Resorts, I am responsible for handling bookings, I can refund things, I can access customer details and which objects to look at, where to get the information from. If your agent has these informations, or again, a simpler example that if you are in ChatGPT and tell it that, okay, I want to write a sales email as a customer service agent for Coral Clouds, my name is Abhishek Saxena, when you start your email, start with the salutation. This is intended to be for the guests who are staying at the resort. And if I give all of these details and then hit enter, the response I’m going to get is going to be a lot more personalized.
And that’s how you can automate it to send to any user that is using your agent. That’s what I mean by why context is so important for any AI to work. And with Data Cloud, as we have discussed in the podcast so far, it gives you that unified profile. It gives you the customer 360 so that your agents have all the information about your particular user who is asking the question or to wherever you’re trying to use it. Because good data, if you give it good data, your responses are going to be much more personalized and better.
Mike:
Abhishek:
Mike:
Abhishek:
So that’s sort of basics of data processing that a typical data engineer knows, but a typical Salesforce consultant, admin developer does not, that was somewhat difficult for me to wrap my head around because in my training on working on Salesforce platform for so many years, I have been accustomed to think about data in terms of objects, Socket queries, and that form. But with Data Cloud, it’s a little bit different. So that was one of the things that threw me off initially, and I had to look at some resources even outside of Salesforce’s Data Cloud trainings to understand that data lake is not actually a lake. Data warehouse is not a big factory in which there are tons of books with data. So yes, that was something that threw me off initially.
Mike:
Abhishek, this has been a fun conversation. I think it’s going to be a very compelling presentation at Dreamforce, but also I think it’s been very inspirational, at least for me, that even the hard stuff is still not that hard to learn. I go back to a saying, everything in the world is created by somebody at some time, and if that somebody can figure it out, you certainly can too. So Data Cloud and Data Lakes was created by somebody, which means they figured it out, so it can’t be that hard for anyone else to figure it out.
Abhishek:
Mike:
Abhishek:
Mike:
So be sure to catch his session if you’re going to dream for us and share this episode with a fellow Salesforce admin maybe who’s also struggling to understand some new technology or just getting started with Data Cloud. Either way, until next time, we’ll see you in the cloud.
The post Making Data Cloud Understandable for Admins appeared first on Salesforce Admins.
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