Transcript:

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Welcome everyone to the next episode of Did You Know? from Prodly. This is Prodly does sandbox seeding and syncing. So I'm your host, Scott Teeple. Welcome to the second episode. With me is Jen, the Customer Success Manager. Hopefully you've watched the first episode, so we don't necessarily need an introduction, but just really quick, I am the Director of Customer Success.

And Jen, just a quick introduction for yourself. Yeah, I'm a customer success manager here at Prodly. Yeah, so we've both been here a long time. Jen was in support before. I'm sure everybody knows her and you've had lots of conversations. So we will jump right in. So Prodly does sandbox seeding and syncing. So you might be wondering, you know, Prodly does more than just complex data and it's kind of the channel that we're working on at the moment in this series of videos.

So why should you trust Prodly with your sandbox seeding and syncing? I think that our journey really brought us into the complex data of CPQ. So Jen, maybe why should you trust us for your sandbox seeding and syncing?

Yeah, absolutely. Thanks, Scott.

So I think the best reason here really is that Prodly can handle all of your data deployments, right, when you're going work to org. So it's really smart to have Prodly handling your seeding as well, because the seeding is really kind of the first step there. And it's also putting you in a perfect position to be able to fully leverage Prodly, as well as our virtual external ID record matching.

So I think really the power there is in our ability to move data, of course, but in general, seeding with Prodly is really kind of a best practice as well when you're getting started with Prodly. But why should you trust us? I mean, again, you trust Prodly to move your data to multiple environments. Why wouldn't you trust us to seed your environment? But also, you know, it kind of to speak to some of the points on the slide here.

This is really something we're hearing a lot is this tech stack consolidation, right? It's top of the mind for a lot of users right now. So ultimately, everyone's looking for that one tool that fits all. So Prodly, as far as your seeding, can definitely handle it there. So if you're looking elsewhere for your seeding, but you use Prodly for your org to org data migrations, I would Prodly recommend that you check out Prodly for seeding. We make it really easy for you as well with our pre -built templates, which I think we'll talk about a little more later. Yeah, yeah.

So not to turn this into a commercial for Prodly, you know, maybe I'm fresh, maybe I'm new to Salesforce and the overall administration and development. They kind of sound the same to me, seeding and syncing. Aren't they the same? Not necessarily. So when we talk about seeding, we're talking about actually getting data into an org. So whether that's like a dev org, that's fresh, after refresh, nothing in it, let's say, you need data to get in there. But this same rule kind of applies to all of your lower environments. And of course, let's not forget the purpose of seeding your lower environments is obviously to promote your changes and have them go through extensive testing within all of those lower environments. And really you can think of it more that syncing is making sure that all of those environments contain the same data.

And obviously that's relevant because you you're you're putting your your work items through testing in there. And so differences between your environments is really skewing your testing altogether in order for you to really feel like you have a controlled test. You need to have control over the data that's in your lower environments as well because you know testing against one set of data might not yield the same results as testing against a different set of data. So yeah, that really is the main use case here right is around you have these requests that are coming in for you to make changes. We don't want to make them in production, right, where the data actually is. So we need to put those changes in a lower environment. How are we sure that the changes that we're making will actually go into production successfully, without issues, without errors? And the only way to do that is to test in production. Don't want to do that. So how do we get an environment that is as close to production as possible?

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And this is how you would actually achieve that is to ensure that you have the same environments as close as possible. And how do you do that? Well, you need to use a seeding and syncing tool. So then when you think about the basics of a seeding and syncing tool, specifically around Salesforce, a couple of features kind of come top of mind. So when you think about data generation, data masking, can you talk a little bit of some of these features and why this matters.

Yeah, absolutely. So obviously data generation is kind of the whole purpose here, right? Is to be able to create data in your lower environments. And so that's the main purpose and Prodly definitely fulfills that need. We also have data masking features that exists right within your data set. So while you're seeding your environments, you could also be simultaneously masking that data in the destination when you're deploying it. And I should say as a side note, Prodly also has ways to mask the data within a single org that's kind of outside of seeding, but just as a FYI, it can be done. That's good. That's good.

So yeah, so then you start going through this list and you look at automation scheduling, performance optimization, logging and reporting, version control rollback. So these are all kind of features of what Prodly kind of brings to the surface. then, know, kind of the series is really around everything that you need, nothing that you don't, right? I'm sure that there are some really expensive, some really crazy tools that maybe do some of some of these features in product. But really, at the end of the day, the application that you bought in Prodly already does all this work for you. And it goes back to the first point on the last slide, you know, which is tech tech consolidation.

How do you reduce your overall operating expenses and get the full benefit of the tool that you already own? So, so good. So when we think about some of the conversations that we've had with customers, some of the topics that have really come top of mind when we have some of these conversations, it's like, yeah, but you know, I have sensitive data and security concerns. How does Prodly help me through this sensitive data and security and this ever changing world of security concerns?

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Absolutely. So I mean, first and foremost, Prodly has access controls that you can put in place, right? To make sure that only certain changes are making certain certain user making certain changes. But when it comes to, know, sensitive data, this kind of thing, that's really falling under that masking category again. So being able to have those controls in place to mask those emails and all that, you know, sensitive information. So that's kind of top of mind when it comes to security and sensitive data.

And obviously, as we mentioned, this is something that Prodly can do for you upon seeding as well. So you don't have to run a separate deployment after. You can just seed and mask within a single deployment, which is really handy. Saves you time later as well. Yeah, but I have a really complex environment. And I have an awful lot of integrations and workflows in my production. It's just like, is it Prodly going to help me in my scenario?

Yeah, well, I think it depends, of course, what the workflows, what integrations, this kind of thing. If you're referring to like workflows that you have in production, if you're looking to replicate those in your lower environments, you can definitely do that with Prodly. We do have a full metadata tool where you can deploy all of your metadata into your lower environment. So when it comes to seeding, obviously best practice, first things first, you want to make sure that your metadata is in sync or at least the relevant metadata as to what your seeding is in sync.

First things first, you want to be able to compare your source and your destination, make sure the metadata is in sync, and also sync those changes if they're not. So you can do that with Prodly's metadata tool. And so you're setting it up so that way the metadata in your destination is matching that of your source. So when you go and deploy the data with Prodly and you actually go and start seeding, you're not going to run into any barriers there where certain fields don't exist or you have certain workflows that are not existing, this kind of thing.

Yeah, so you brought up metadata. So if you haven't watched episode one, please make sure you go back and watch that because did you know Prodly also does metadata. So so now I'm syncing about me being, you know, really within quality QA team. I've got a really robust operations and test cases and all this. I really have to have access to realistic and accurate data. Is Prodly going to help me with that. Yeah, absolutely.

So when we talk about seeding, what we really mean is moving data from your production order down to your lower environments. And then when we talk about syncing, what we mean is making sure that all of the data in your lower environments is in sync, meaning it's all matching. And so you're asking about realistic and accurate data, that data is actually coming from production, right? And this, course, is where the masking comes in too, right? Maybe you don't necessarily want all that information in your lower environments. Maybe there's some things you want to hide, but generally speaking, you want your data to be as close, if not identical, to production as possible. So when we refer to seeding, what we really mean is just deploying those records from production to your lower environments, which by the way, you can do in one shot with Prodly up to five environments, five destinations in a single shot. So that makes it really convenient. And then from there, when we talk about syncing and refreshing that data, again, you're just doing a seeding back from production to your lower environments again. And what that's doing is it's updating all of the records in your lower environments and also making sure that they match across all of your environments again to reflect production. So the data is coming from. Yeah, but my production data has like some pretty important data like the email addresses and workflows and emails that are going to be sent. Like I'm a little scared to just copy all that data down. Like what are you going to do to help me not send emails to my entire customer base?

Yeah, so we have like a prefix post fix value option for emails if you want that you can use. It's kind of a quick fix to this issue where you could just do a post fix of dot invalid on all the emails so that way they're not when they're going in being in certain destinations and they're not firing off any emails or anything like that. So yeah, I would I would Prodly recommend that you follow that kind of flow there with them with some of those masking and obfuscating options that we offer.

Yeah. Well, and the last one here, right? It's like, hey, I work in a highly regulated organization, right? Whether it's HIPAA and health care or SOX or whatever that case may be, I just really have some concerns about how data is being moved. What does Prodly do to help me with my regulatory and compliance concerns?

Glad you asked. We have a newer, I would say it's a little newer, tool called Compliance Center that can definitely help you with this. So you can kind of think of Compliance Center as a monitoring tool. So you can actually monitor the environments that you care to monitor and track those changes to see what changes are being made. Are they adhering to compliance? Are they outside of it? That's up for you to decide. But ultimately, you can run those reports as well, especially if you ever need to show that information to an auditor or something like that, you'll have all that information ready to go for you.

Yeah, very cool, very cool. Yeah, and without further ado, maybe we'll just jump right in and Jen, if you want to just share your screen here and we can just jump into a quick little demo to let everybody know kind of how what it will look like. Yep, absolutely. Just one sec. Here we go.

Alright, so to get started with seeding with Prodly, I mean, I always recommend checking out our templates, right? It saves you a bunch of time in case you don't have your Data Sets in your deployment plans. Assuming you can find a template that works for your use case, I would recommend starting here. So you can see that these are all built for you. You can choose if you have something that works for your use case. Today we're going to work with. Where is it? We're just going to work with the sales cloud.

So I've already opened this up in another tab here. So for this Data Set, this is one that we provide you, so one of our templates. I did go in here just to make a change on the masking options just to show you. So first things first, just to give you an idea of what's included in here, you can see this is just your kind of basic Sales Cloud data that I'm going to be seeding. But then I've just gone and made a couple changes. So I just made an update for the email field on contact. So I've added the set random value here, but I'll also quickly just show you guys the options that we have. So if I wanted to set it as empty, I could do that. I chose set random value. So this is just going to give me kind of like a mock email in email format, but it's just not going to be a valid email. And then if I wanted to do some sort of fixed value, I could do that. And then this is also where you would do that dot invalid that you're looking for. So if you ever need to do that, you can use that here but we'll just go with the set random value today. So I've already made my changes and I'm ready to go. I would save those changes and then just hit deploy here. So I did just run this earlier just to kind of save some time on our call today. So let me just open up my results here. So, and actually just to show you guys, I would have deployed this to up to five destinations at a time. I'm only going to deploy it to the two here today.

Toggle on my data and find my data set. And then at the bottom here, I can give this a name.

Go ahead, link your work item.

And then when you're ready, you can go ahead and deploy. Keep in mind, if you ever need to, you can also deactivate events in your destination. So if for some reason, you know that you might have some custom validation rules or something like this that might prevent us from inserting records, I would recommend just enabling this toggle here. We'll leave it for now, but I'll go ahead and just hit deploy. So this will kick off two deployments for me now to both of my environments, one to each. And again, that's that's gonna go and seed that sales cloud data into my lower environments. And I'm also expecting that it's going to mask that data while it's deploying it.

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All right, and then just to show you the results that I ran earlier again, this is what your seeding results will Prodly look something like. So I can see all the records that I went and deployed. I can see some of those in this case. OK, they were updates. Didn't insert them all into my destination. But a normal seeding example Prodly would be mainly inserts. And then I just want to show that I did have some contacts go in there.

Let me just see if I can compare these.

So I can see that in my source, the email for this contact was my own email. And this is just a demo work, but yeah. And then after I deployed, I can see that that email is now a different email. Again, it's going to follow that email format. It's just not going to be a real or valid email. So if I had done .invalid, what I'd be seeing here is the same email that I have from the source, just with a .invalid at the end. And then, of course, you can always go and run through this example with any of our other templates. Doesn't have to be Sales Cloud. Probably one of our most popular is our CPQ deployment plan. So if you're a CPQ user, please check this one out. Going to save you so much time. All right. And think that's all I got for you today on the demo.

All right. Well, I hopefully you see the value of sandbox seeding and syncing to keep your environments truly in a state where you can feel comfortable with your testing in your lower environments and reduce the overall issues that could potentially show up in production by not having the right pieces of data. So what's next? So we have a new series coming up. So another episode three will coming.

But please reach out to us if you have any questions around sandbox seeding and or syncing of course Jen as a CSM, me an account management and CSM, so reach out to us if you don't know who your account manager or your CSM. I will be happy to get you in contact and and get you going to get you successful within Prodly, so talk to you guys all in the next episode. Thanks, Jen!

Thanks guys!

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