​Carlos:             Compañeros! Welcome to another edition of the SQL Data Partners Podcast. My name is Carlos Chacon. This is Episode 201 and we are in Season 4. We’re going to continue to try out this video component and we’re very happy today to have Tricia Wilcox-Almas with us today. Welcome, Tricia.

Tricia:              Thank you. Happy to be here.

Carlos:             So, I met Tricia, let’s see, now all of a sudden, I’m try to re– oh, we met at Virginia Beach SQLSaturday.

Tricia:              Yes.

Carlos:             And yes, I was daring enough to talk about Power BI and we struck up a conversation and we started talking and I’m like, “hey, I’d really like to have you on my podcast.” It took us a little while, but we finally got here. And we should add that you are recently retired from Microsoft?

Tricia:              Yes.

Carlos:             You’re enjoying retired life?

Tricia:              I haven’t slowed down any. I really have not. I get to sleep in, but it just does not work that way.

Carlos:             Yeah, so we were talking yesterday about how the Microsoft folks, developers are getting on-call notices and things like that, so obviously they still left you with a pager. They’re still asking you to keep the Bat Phone. “Tricia, we need you.”

Tricia:              It is funny. I still do get calls once in a while for particular comparisons, because I have deep experience in a lot of toolsets.

Carlos:             Oh, there we go. Very cool. Well, we’re hoping you can help us shed a little light today on the Common Data Model. So, this is something that we did explore in a previous episode, but then you actually came in and spoke to us at our SQL Trail event in Richmond about this, and I thought, “hey, you know what? It’s probably a good idea that we get her involved and do that.” But before we, I guess, get into too much of that, I guess we’ve already talked about YouTube, so our show notes for today’s episode, we have a couple of images and whatnot, will be available at sqldatapartners.com/cdm or at /201. Now, I can remember, and this is actually in your slide deck, so I want to say it was Ignite. I was following online, and Satya gets up with a representative from Adobe and a representative from SAP, and they start talking, and I’m kind of like, “what are we doing here?”

Tricia:              Yes.

Carlos:             And then at the end they start singing Kumbaya. So, knuckle-dragging Neanderthal that I am, I did not realize at the time that they were ultimately laying out or introducing the Common Data Model and talking about some of the, “hey, here’s how it’s going to help us.” So maybe, I guess, take us back a little bit, let’s review quickly what the Common Data Model is and maybe how it came to be, and then we’ll go from there.

Tricia:              Yes. Okay, so yes, the Common Data Model is a collaborative experiment, I will say, between Adobe, SAP and Microsoft, and I think Satya Nadella, our fearless leader at Microsoft, really has ushered in a new era of collaboration and open-ness, support for open data systems, open tools, and not being quite so proprietary. And the hope there is that this better integration is going to lead to better insights, better data. And the Common Data Model is that new language that we can use that will span purpose-built business applications, and analytic applications. And in order to understand the impact of that, I think we have to take a little trip back in time to when data warehousing first started, and I hate to say it, but I was around back then. And the first data warehouse that I ever worked on was for Amerigroup in Virginia Beach here, who became WellPoint, which got bought by Anthem. But they had a 14GB data warehouse on SQL Server 6.5 and my initial consulting gig with them was to babysit that warehouse over the weekend to make sure it wouldn’t go down, because it was too large to back up and we had to migrate to SQL 7.0 and upgrade all the stored procedures and triggers and everything else that went along with it, and all the reports that came off of it. And there was a huge change in structure between SQL 6.5 and 7.0, so that was no trivial task. But it was exciting, because it kind of gave me a peek into what you could get if you had integrated data. If you could see the customer and all their transactions in the call center, and all of their claims that they had filed, and all of the nurse follow-up notes that went with that, that you could really get better insights and deliver better care based on those insights. So, that was the first of many data warehouses that I worked on, but what we started out with was basically some on-premise data sources of different varieties. Some of them were in Sybase, some of them were in IMB, DB2, you know, it was kind of all over the place, and we had to figure out data quality, we had to do some master data management, because you had customer records coming from different systems, and so, we learned a lot at that point about what data actually is, how it lives, and how you handle it. Okay, so we go along with data warehousing in the traditional sense for a while. Now we start getting these cloud-based apps that are coming into the picture. Well, how do you consume that into an on-premise data warehouse? Things just got more complicated. You just had to triple your number of ETL runs and data cleansing runs and all of that, and then you start wondering, “well, maybe it’s better if I put my data in the cloud and make it easier to consume and manage.” And so, then you have a whole new toolset to learn, and new procedures and new– right? Everybody’s got to learn a different way of doing things. So, the Common Data Model is really an attempt to solve some of those problems. It’s standardized, it’s modular and it’s extensible, and those three factors, I think, give developers a lot of promise for what can be done. Especially now that we have to consume social media data, data that’s in different kinds of data stores, maybe in Hadoop or NoSQL. And all of those things have to come together, and you have to have a way to rationalize it and put context around it. So that is where this collaboration between Adobe, SAP and Microsoft can really lead the way, I think. Of course, I drank the Microsoft Kool-Aid a long time ago.

Eugene:           I think a lot of us have. I get paid very well to drink Kool-Aid.

Carlos:             That’s right.

Eugene:           That’s it. I’ve got some of the Microsoft stuff right here, it’s real good.

Carlos:             Well, so, now having said that, so that– was it 2017?

Tricia:              Yes.

Carlos:             Yeah, okay. So, we have the three organizations, and then you’ve just listed all the cloud– I mean, Hadoop even, is not necessarily– well, I guess it’s kind of in the Microsoft ecosystem, if you will, but they’re not those three companies. So, do we get a sense, or do we have any idea of, what’s been the adoption like so far? Cause one of the things that we kind of chatted about last time was, well, I don’t know ‘if how serious we should take it’, but like how prevalent is it? How much is this going to help me, because like data cleansing, like changing data structures, not easy. Now, if I’m building something, that’s a different story, but I already have my data– I guess a couple of questions here, and I apologize. You can take them as you wish, but are other organizations starting to adopt this? Are you starting to see that in, I don’t know, Twitter or the social media pieces? And then, a follow-up, if you remember is, what do you think about customers, or what kind of guidance are you giving them in terms of, “hey, you should probably start adopting this?”

Tricia:              Yes, I am seeing an uptick on adoption for a couple of specific use cases. One, in prototyping, and especially if the customer is using Azure Data Lake Generation2. I guess it’s just Azure Data Lake now; they’ve probably retired Generation1.

Eugene:           No, One’s still around. I was doing a course on Event Hubs and you can still write it to Gen1.

Kevin:              Yeah, for the three locales where you can actually use Gen1.

Eugene:           Oh sure, yeah, yeah. Just because it’s available doesn’t mean it’s available, right?

Tricia:              Yeah. That’s right, that’s right. So, in Generation2, Common Data Model and Common Data Services are baked in. So, one of the cool things about Azure Data Lake and using Common Data Model, is that it preserves the data kind of as it is, and it writes out to Excel files in a particular format that includes metadata. So, you can use that same datastore for machine learning or other kinds of AI investigations or reporting that you want to do. As well as consume into Power BI for graphical reporting and dashboarding. So I’ve seen the adoption in the Common Data Model mostly for places that want to protype and show really quick results on data integration and presenting back to end users. Especially if they have adopted the other components of the Power Platform, like Power Apps and dataflows, who rationalize their information. Does that make sense?

Carlos:             So, if we’re building new stuff, then it’s the perfect time to use it, particularly cloud technologies. I mean, is that fair?

Tricia:              Absolutely, yes.

Eugene:           That makes sense.

Tricia:              Yes, absolutely. And like I said, you can do it so quickly. Instead of doing ETL, extract, transform, load, we do extracts, load them into ADLS, then transform and consume on the ingest, and with Power BI and Azure Data Lake, you can do that in days, instead of months.

Carlos:             Sure, because you’re ultimately following the CDM and saying, “hey, here’s how I’m going to partition my data,” and then you have more plug and play, if you will, for the reporting pieces. Okay. That makes sense.

Tricia:              Yes.

Carlos:             So, Eugene, are you going to hop in there, or–

Eugene:           You know, I think she was on a roll with things, but I definitely have a bunch of thoughts. It’s interesting. So, whenever that whole announcement about the open data initiative or whatever it was called came out, I wrote blogpost about that and some other things, and I was having like a mid-career crisis; although, I hope my career lasts more than another like 7 years. Because the announcement came out around the same time that I was at the Power Platform Summit when it was in Phoenix, and this was the first time I had seen like, I don’t know, probably like 5000 or 3000 business professionals all in the same building. Like Power BI was this tiny piece, and then you had like Dynamics for miles and miles and miles, and it really opened my eyes to the fact that there’s this whole market of people who are interested in the Power Platform that I just never run into. You know, they’re dark matter to me. I’m used to coming in from the SQL side and like I know what the SQL people want. They want SSRS but better and all this kind of– I get all that, but like CDM, coming from the SQL side, makes no sense. Like, I used to have to support Dynamics Great Plains, and I would ne–

Tricia:              That was fun.

Eugene:           Yeah, oh yeah, no. Any time I see a Robert Morris license plate, I think it’s a table, because it’s RM and then like 5 digits instead of being receivables management. So, this is my life, right, yeah. And I would never, I would never want to put my ERP system on a non-relational engine. And so, you think about Dynamics Online– I mean, to my understanding, correct me if I’m wrong, but Dynamics Online uses CDM, it uses this as kind of its backing store for the data, and like, as a SQL person, that’s crazy. But as a business user, being able to throw together a model-based power app in minutes and stat implementing business logic without having to pay $60,000 to some outside developer to build something, that’s awesome. And so, when this initial announcement came out, I had a lot of whiplash understanding what this is for. Cause as a former DBA, makes no sense to me, seems crazy, you know?

Tricia:              I think you’re getting at a good point, and that is our traditional data people, database administrators, that is going to change a lot. And more and more system administrators are going to take over the data maintenance capabilities and procedures for Azure data management. And I think DBAs are going to shift more into being either data analysts or data scientists. You know, that seems to be the way that we’re trending now.

Eugene:           To kind of paraphrase what you’re saying, it seems like whenever you make it so that a lot of this data platform is more of a platform as a service, you basically push things out. So, what used to be a specialized role is now either the data engineering, which is more on the IT side, it’s much more manageable by IT and sysadmins; or you push them to the end of the data pipeline so that they become those data scientists or those data analysts. We don’t have as much of a need for somebody in the middle. There’s more of a need for a sysadmin who understands Azure as a whole, or somebody who understands the final product and how to get insights out of it.

Tricia:              Yep, I definitely agree.

Carlos:             So, you mentioned the adoption of Azure Data Lake is kind of the ‘where CDM really shines’. Again, this is just an audio piece, although we have our lovely faces here, but in terms of, we’re not necessarily demoing anything here, but maybe give us the nickel tour in the sense when it comes to Azure Data Lake and you mentioned some of the components that CDM would use. I guess, could we get that nickel tour of what that looks like?

Tricia:              Okay, so the implementation of Common Data Model in Azure Data Lake is a series of folders and they’re organized under each entity. So, in a very relational way, those things– I have a slide of it, would you like me to share?

Carlos:             Sure, let’s try that.

Tricia:              Okay, let me–

Eugene:           We’re still new to this whole video thing. Carlos didn’t give me any warning, to my recollection, that we were switching to video, so this is the second time I’ve done the video podcast, but I found my webcam hiding in my travel bag, so I’m happy to have some better quality, here.

Tricia:              One second, let me find–

Kevin:              So, for people on audio, Carlos will render every picture, every screenshot as a wonderful display of vocabulary, explaining it in metaphor.

Eugene:           Oh, man, I was hoping for more of a rotoscope like, you know, ‘Take On Me’ kind of thing.

Kevin:              Or for people watching on video, Carlos will also do the slides, but as interpretive dance.

Tricia:              I love that.

Carlos:             Oh boy, I don’t see that on the agenda.

Kevin:              The best part is he’s going to do both of them at once, which is just mind-blowing.

Eugene:           Alright, so we’ve got this slide here. Go ahead.

Tricia:              Okay, so, the way that it’s organized is by source. So, in this example, you’ll see that the very top folder is Dynamics 365, and then there’s an organization under that. And then each one of these other folders are by entity, so accounts, leads, opportunities. And within those folders would be Excel files with exactly the same data format, with variable numbers of rows, and also a metadata file that describes the structure of those files.

Carlos:             So, just helping connect the dots, is that literally, when you go and you spin up Azure Data Lake, you’re like, “hey, I want to use Common Data Model,” it’s going to plunk these in there for you?

Tricia:              It has the metadata already embedded, so say I import a file that I want to match up to my account entity, and I go through and I map it, the structure’s already provided for me by Common Data Model, so I just have to map what fields of mine map to that entity, and it will consume it that way. So, it’s funny, I remember way long time ago, when I first started data modeling, and having to do master data management before there were any tools for that, and you’d find your name field had 25 characters in one source, and it’d be 55 characters in the other source, so then you have to make a decision about what you’re going to do. Are you going to truncate, are you going to pad, what are you going to do? Common Data Model takes care of all of that for you; all of that kind of interpretive work, right? So, if you have a good understanding of what entities are being used by which systems, this really is a rapid way to do that data integration.

Eugene:           So, I want to make a clarification about Azure Data Lake Storage Gen2, because I had to learn what this was for my previous course, and I was trying to write out a slide that said, “okay, here’s the difference between Azure Blob Storage and Azure Data Lake Storage Gen2,” because those are the two places you might write to for Event Hubs. And my current understanding is there is almost no difference. It’s literally a checkbox for hierarchical name spaces, which is basically the fancy word for folders. So, the backing engine, obviously it’s an amazing accomplishment they did, but I think something that our audience would really do well to understand, because I didn’t understand this three months ago, is Azure Data Lake Storage Gen2, Gen1’s its own beast, but Gen2, it’s just Blob storage with proper folder support.

Tricia:              Yes, which hierarchy.

Eugene:           Yeah, because Azure blobs, they have pretend folders based on filenames, but if you need to rename a whole folder with 10,000 files, it’s going to have to do that for each file.

Tricia:              Exactly.

Eugene:           You turn on hierarchical name spaces, you get actual folder-based operations. That’s all that’s different, that’s the switch. But on top of that, you get all these interactions with the Hadoop ecospace, so all these tools can talk to Blob storage. But there’s no magic in Azure Data Lake, which is what’s supporting the Common Data Modeling. At first, when you look at it, it seems like it’s just this amazing, awesome tool, but it’s an iteration on existing Azure technology, and that took me a while to get.

Tricia:              Yes, it definitely was an evolution, and I think it arose because all of us data geeks were giving feedback to the Azure product team that, you know, blob’s great, but it just isn’t going to cut it for what we need to do for our customers.

Eugene:           Yeah, absolutely.

Tricia:              And yeah, it’s a huge improvement.

Eugene:           Yeah, but this whole folder structure with Common Data Model fits in perfectly with the way that, at least to my limited understanding, people are using Data Lake Storage. It makes perfect sense what’s going on, here.

Tricia:              Yes, yes. And so, the other thing that I think is going to be the next evolution is being able to use more graph-oriented queries against it for Power BI and reporting. So, I really think graph is the next big thing, when it comes to understanding data, because it’s based on relationships, and that is so extensible. And the more that you know about the data and the context that you get from those relationships, the better insights that you’ll get from it.

Carlos:             Yeah, that’s interesting and I guess working on those hierarchies, we think about relational and other storage methods, it seems natural that graph would then play a bigger role, potentially in some of that. Okay, well, yeah, so that is helpful. So admittedly, I don’t know that those dots were connecting quite, for me.

Eugene:           Yeah, well, and it’s worth thinking about where this came from, cause again, like since I just learned a lot of this stuff over the past three months, I’m going to pretend like I’m an expert, because I’m just really excited about it, that it finally clicked. But a lot of this stuff comes from the fact that when you’re dealing with big data, data ingestion is a big deal. So again, Event Hubs, IoT, that kind of stuff, you’ve got all of this data coming in rapidly. Whenever you can store it as these .csv files, especially when you’re dealing with normal Data Lake kind of ingestion and you can split it up based on timestamp and that sort of thing, you can scale out so much better. A lot of where this structure that seems weird to us DBAs came from, is how do you make storage that can scale out in general, so you can support petabytes of data but can also scale out in terms of volume of data ingestion. If you’re doing that whole ELT thing, how do you optimize for DL? Because you have data that’s coming in fast, you have data that’s big, and you have data that’s sometimes in these weird structures, and so what kind of happens is we figured out a solution for those like 3 or 5 or 15 Vs of big data, volume, velocity, variety, Vin Diesel, whatever.

Kevin:              Verisimilitude.

Eugene:           Yeah. And then, I think Microsoft said, “okay, well, how can we take that existing set of solutions and bring some of the Office 365 magic over to it, or the Power Platform magic over to it so we can take advantage of the benefits we get there”, with the analytics and all the stuff that, you know, Tricia’s talked about. That’s how I see it is we had a solution for an existing problem, and then we brought over the business side to get the benefits of that.

Tricia:              Yeah, I agree, and I think you can see how when Azure first started, before the ingestion hub for IoT, there was Stream Insights and now that has evolved. And the platform will continue to evolve, and I can tell you that engineering is always looking at what’s out there, what’s next, and how are we going to address those customer needs.

Carlos:             Yeah, that’s cool. So I had a friend reach out to me after our last episode and she’s like, “hey, I’ve actually used the Common Data Model,” and she’s like, “I’m not an IT person”, but she is on that analyst side, and she did talk about how it just made it much more approachable, I mean, the very things you were saying, there earlier. And so yeah, it’ll be interesting to see how this continues to evolve and we think about making things easier for our end-users, then this could be a way, particularly as we build new pieces.

Tricia:              Absolutely, and I think now that I’m retired, ha, and I’m looking at different kinds of data, cause in my career I’ve worked a lot with the military and big companies. Now I’m working with small companies and influencers and a lot more marketing data and influencer data and social media data. And when you’re doing audience research, you have lots of survey data that you have to ingest. You want to combine that with their social media posts to try and get a flavor for sentiment and things like that, and Common Data Model just makes that a lot easier.

Carlos:             Very cool. Well, thank you for that. I think that was helpful in helping us identify a couple of use cases, talk a little bit more about how that would be approachable, and so we appreciate the conversation.

Tricia:              Oh, yeah.

Carlos:             Last thoughts, or should we jump into SQL Family?

Eugene:           I think one last thought for me is I’ve definitely found this conversation helpful, because Carlos said we explored the topic before; it was basically an hour of us going, “we’re not sure what this is for.”

Tricia:              I did listen to that podcast.

Eugene:           And you’re like, “I need to fix the record. These Dumbo’s don’t know what they’re doing.” No, yes.

Tricia:              No, it’s funny, because working with Microsoft, you get to work with a lot of really big companies. Sometimes they are not the first to adopt new technology.

Eugene:           Yeah, I’ve noticed that.

Tricia:              Right? Because they don’t want to take the risk. So, I had to get some experience working with a little bit smaller-midsize companies, where they were actually using it, in order to see the real power and capability of Common Data Model.

Eugene:           So yeah, big point is, I want to say this is definitely a helpful conversation, so, that’s my final thoughts.

Carlos:             There you go. Awesome, shall we do SQL Family?

Eugene:           Yeah.

Carlos:             So, Tricia, how’d you first get started with SQL Server? I think you talked a little bit about that maybe earlier, but–

Tricia:              I did. I did. I had been a project manager and a database administrator using Informix and Sybase and when I moved to Virginia Beach, my first consulting gig was with Amerigroup; I can say that now, because they’re not in business anymore. And they had SQL Server 6.5 as well as some minicomputer systems, which probably nobody would recognize now, and that really got me hooked. I had been using Oracle and PLSQL for some time, and Ingress was another big database platform that I used on at the Coast Guard. But I just found SQL Server was just so much easier, so much more straightforward and logical and it was really easy to pick up, so, drank the Kool-Aid right then.

Carlos:             There you go. A couple of weekends, you know, banging your head and the rest was as they say, history.

Tricia:              Yes.

Carlos:             Now, we all go through evolutions, obviously now from a career perspective, you’re at the other end, but what advice would you give someone wanting to pursue a career similar to yours?

Tricia:              I don’t know if anybody would want a career similar to mine. I am not a programmer and I never learned programming. I’d tried several times. I just don’t think like that. I’m a systems analyst. And so, I think one of the things that really helped me was that I wasn’t a programmer and it made it easier to talk to end users. Right? But I knew enough about programming so that I could supervise them and get them to give me their best work, and I worked with some really good developers. But I think for anybody to have a good career, you have to have curiosity. So, find out that thing that you’re curious about and focus.

Carlos:             There we go. Stay curious, compañeros. I totally agree with that one. Okay, so what is one thing that can instantly make your day better?

Tricia:              Oh, that one’s easy. Just look at pictures of babies or puppies. You know, if I’m really upset about something or I just can’t watch the TV streaming riots anymore, take a break, go on Facebook and look at puppies.

Eugene:           Yeah, my chihuahua has not been doing it for me, because he’s not been handling the social isolation well either, because he seems to be barking a lot more at random stuff. You know what I mean? I have to look at other people’s dogs.

Tricia:              Oh, I know, I feel sorry for the delivery guys, the Amazon Prime delivery guys, because I have two dogs, and they always have to greet him.

Eugene:           Yeah, well it’s funny, I love my dad, but he’s not the best with people and he’s not the best with animals, and so my pet dog hates him. Hates his guts, and he’s this little tiny chihuahua. I’ll be holding him, and he’ll struggle out of my hands to go after my dad. And my dad is kind of hippy-dippy-naturalist, so he brings me goat’s milk, because he thinks it’s healthier for me and it probably is. So, my dog has learned that if I have an empty milk jug in the living room, that means my dad’s nearby and he’ll start going insane. He’ll start barking up a storm because he knows that I leave the kitchen with an empty milk jug, you know, Mr. Meidinger’s somewhere around and so it’s just the funniest thing.

Carlos:             That’s funny. Okay, you have $10,000. What computer or tech would you purchase?

Tricia:              Oh, that one’s easy, because I never have that much money to blow on equipment and I am a gadget geek. I am a junkie. I can tell you I had the first Palm Pilot that ever came out. I would buy a 3D printer. That’s what I would get.

Eugene:           I’ve got one of those, and it’s been helping keep me sane. I’ve been doing the resin printing, which is messier, but you get real fine detail.

Tricia:              Oh nice.

Eugene:           Yeah.

Carlos:             Oh, that’s actually 3D printing, huh? Okay. For your models.

Eugene:           It’s a 3D print and then I painted it. Yeah, and so it’s going to be– I play a game called Gaslands, which is like Mad Max but with Hot Wheels cars, basically. I kid you not.

Tricia:              Oh, I like it.

Eugene:           Like your models, you buy a Hot Wheels car and then you slap on like a 3D printed gun and it’s like Mad Max. It’s great. And so, this is going to be, like whenever COVID’s over, this is going to be terrain that you have to avoid.

Carlos:             Nice!

Tricia:              Cool!

Eugene:           Yeah! Yeah, it’s been real fun. I made a whole art room in the basement; it’s been keeping me sane during this crazy stuff.

Carlos:             There you go. So now, do you have something that you have in mind for your 3D printing?

Tricia:              Actually, this is going to sound crazy, but I would probably do knee braces for my husband. He has really bad knees, he can’t get knee braces that fit, and it just seems like something that would be easy to engineer.

Carlos:             There you go. Man, now you’ve got me thinking, 3D printing, like–

Eugene:           Don’t buy a resin printer for that. it’s good for small little detail, but I can’t print anything wider than my phone, so get the filament deposit models.

Carlos:             There we go. Now, we talked about this, and we can change this, so which famous person in history or current events, would you want to spend the day with?

Tricia:              Yes, my first choice would be somebody still living and that’s Neil deGrasse Tyson, cause I’m a totally science geek. I love Cosmos. I watched it when Carl Sagan did it and as soon as Neil brought it back, I’ve been a big fan. And I think that he is particularly tuned into the science of this time, so I think it’d be really interesting to hear his take on some of it.

Carlos:             So, have you purchased his MasterClass?

Tricia:              No.

Carlos:             So, I see those commercials and they’re quite enticing.

Eugene:           They’re very good commercials. They almost get you. You’ll like hear Neil Gaiman talk about writing books or Neil deGrasse talk about scientific thinking, you’re like, “I want to be that. I wanna do that.”

Carlos:             Yeah, yeah, and I’m almost like “eh, eh.” Yeah, anyway. Okay, and our last new SQL Family question is what’s your favorite ice cream topping?

Tricia:              Oh, that’s easy, caramel. The problem is, it probably will pull out my fillings. But I like it.

Carlos:             The thick caramel, then, huh?

Tricia:              Yeah, I like it so much better than chocolate.

Carlos:             There we go. Now, if you’re having caramel, there’s a follow-up question, here. So, what flavor ice cream are you putting that caramel on?

Tricia:              Oh, butter pecan.

Carlos:             Ooo, there we go.

Tricia:              It’s a very nice combo.

Carlos:             Awesome. Well, very good. Well, thanks so much again, Tricia, for taking some time to chat with us. We do appreciate it. Before we end, we do have a couple of compañero shout-outs. Gina Mer– oh gosh.

Kevin:              Meronek.

Carlos:             Meronek? Or just Meron?

Kevin:              Meronek, yeah.

Carlos:             Do you know Gina?

Kevin:              Yeah, she’s up in the Madison area.

Carlos:             Oh, there we go.

Eugene:           I see her on Twitter a lot.

Kevin:              She helps run the Madison SQLSaturday.

Carlos:             There we go, sorry, Gina. Thank you, Kevin, for coming to my rescue, there. Kevin Wilkie. We have to mention Kevin’s name because it’s been too long since we’ve said Kevin’s name. Longtime listener, bigtime– he’s always trying to razz me about something. So, Kevin, thank you for letting us know you’re still out there. Eric Smith connected with me on LinkedIn and has enjoyed the podcast. And Mark Beedle, he’s one of those ones that found the Power BI and Power Platform topics interesting. And I think Tricia, you’ve got one as well.

Tricia:              Yes, I want to give a shout-out to Dr. Peter Aiken. He’s an Associate Professor there in Richmond.

Carlos:             Yeah, he’s in my neck of the woods, yeah.

Tricia:              Yes, and I’m a longtime fan of his. He spoke for me at a conference once, and I just want to give Data Blueprint a plug, cause data geeks unite!

Carlos:             Yeah, there we go. Yeah, so I’m sure the Common Data Model, he’s all over that, because it seemed like Data Blueprint is into, I guess, the planning and the structure of data.

Tricia:              Yes, and data governance, it’s a big focus on data governance, which is hugely important if you want to actually manage your information.

Carlos:             Right. Yeah, he’s very interesting. I’ve heard him speak several times, and yeah, great guy. So, thank you for that shout-out. Okay, that’s going to do it for today’s episode, compañeros. Thanks again for tuning in. As always, you can reach out to us on social media or connect with us if you have questions or comments. Tricia, how might people reach out to you?

Tricia:              You can reach me at [email protected] or on LinkedIn.

Carlos:             There we go. Eugene?

Eugene:           You can find me on Twitter @sqlgene.

Carlos:             Kevin?

Kevin:              You can actually find my details if you look inside the Contoso East Asia directory. You have to search in the metadata and read it backwards, but that’s how you’ll be able to find where I hang out on Instagram.

Carlos:             Yes. Now, what language you have to translate that back into, we’re a little unsure at that point.

Kevin:              That’s part of the challenge.

Carlos:             That’s right, part of the challenge. And compañeros–

Tricia:              The PowerShell script.

Carlos:             You can reach out to me on social media. I am at Carlos L Chacon. Thanks again for tuning in wherever you might be. We hope that you are safe and well and we’ll see you on the SQL Trail.