Sept. 3, 2024
Episode 337: In the Dynamics Corner Chair: Fabric meets Business Central in the Great Lakes
In this episode, Bert Verbeek speaks with Brad and Kris about Microsoft Fabric: what it is, how to use it, and how it integrates with Microsoft Dynamics 365 Business Central. The conversation also clarifies what we do with the Great Lakes—Data Lake and One Lake. They discuss how Microsoft Fabric is a powerful tool for businesses to leverage their data and make informed decisions.
#MSDyn365BC #BusinessCentral #BC #DynamicsCorner
Follow Kris and Brad for more content:
https://matalino.io/bio
https://bprendergast.bio.link/
00:00 - Exploring Dynamics 365 and Microsoft Fabric
18:01 - Data Management and Reporting in Fabric
30:53 - Utilizing Fabric and Dataverse in Businesses
44:03 - Understanding AI Prompting in Data Science
WEBVTT
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Welcome everyone to another episode of Dynamics Corner, the podcast where we dive deep into all things Microsoft Dynamics.
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Whether you're a seasoned expert or just starting your journey into the world of Dynamics 365, this is your place to gain insights, learn new tricks and what it takes to create a fabric.
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I'm your co-host, chris.
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And this is Brad.
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This episode was recorded on August 26th 2024.
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Chris, chris, chris Fabric.
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Every time I hear fabric, I think of clothing.
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What I'm wearing, yes yes, or sewing how it connects together, it woves together.
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See, this is where some of these names come from, I believe, and also we had the opportunity to talk about jumping into the lake With us today.
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We had the opportunity to speak with Bert.
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Hello, good afternoon, how are you doing?
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hi, good afternoon, I'm fine, thanks.
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Thanks for having me.
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How are?
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You uh brennan, chris ah, everything's going well over here.
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Chris and I were just talking about how we need to have, like, a pre-podcast pump-up song or something, because we sit and talk before the podcast and before whomever we're speaking with joins.
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We need something to rally us up, to get us a little excited, especially the time difference, because it's really early here.
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Wake me up here, maybe the song Eye of the Tiger.
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I always We'll have to try that, chris, later on to see.
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We're always excited, but I want to just have like an intro or something for us.
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Just like you know, I can picture like a football game or a sports game where people are in the locker room or the tunnel waiting to run out yeah, pumping the music, let's go, let's go, you know, or some sort of match it would be good, that does always thing right.
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If you play the right music I'm also also doing that with sports, indoor cycling then just a good music and a quite a good beat.
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Yeah yeah, no, it's good.
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It even works with workouts.
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I noticed I listened to some I techno music with upbeat music when I work out because it gives me that energy and drive to go through.
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Sometimes it's a little difficult.
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Do any of you do that when you're like, when you're focusing on work and you play music in the background, or at least through your headset, however, you listen?
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Do you ever any of you both do that?
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Yeah, I do that often.
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Yeah, that, however you listen, do you ever any of you both do that?
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Yeah, I do that often, yeah, yeah, yeah, I do that often.
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I listen to, to music, um, to kind of just keep me energized.
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To be honest with you, I listen to techno music, then sometimes country music for a certain point, but then also I found like classical music or symphony yeah, it's good you're focusing yeah, it's good for focusing.
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Yeah, it's good for focusing.
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Indeed, that's very correct, brett.
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When I also need to focus and concentrate on one thing, I play always some classical music with no voice, or just the classical.
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Yes it's amazing how it works.
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It helps you really get into the zone and focus.
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Albert, thank you for taking the time to speak with us this morning, this afternoon, this evening, whatever it is, wherever anyone is, and we've been looking forward to speaking with you.
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And before we jump into it, could you tell everyone who's listening who doesn't know a little bit about yourself?
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Yeah, thanks for having me, Brett and Chris.
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I'm Bert Beek.
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I am 41 years old, married, have three children, living in a small city in the Netherlands, the same city as AJ Kaufman I recently discovered.
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The beginning of this year, we were in a conference in Denmark and we said maybe we can drive together.
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And oh, where are you from?
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Barneveld?
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Oh, I'm exactly the same.
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So we didn't know that for a couple of years we are living in the same city.
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Over a couple of years we are living in the same city, never met each other there, and I'm working at 4PS as technical solution architect.
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They are working for 12 years, but 70 or 80 years working with Dynamics, na, nev and Business Central and mostly focusing on the technical part and also the functional part of Business Central.
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That's great.
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It's interesting.
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It's a small world, it's a really small world.
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I come across individuals everywhere that have some sort of connection, and it's cases such as yours, where you and AJ live in the same area.
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You said netherlands, did you watch the race?
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Did you go to the room?
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no, I don't go to the race, uh, because the price dates are quite expensive.
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Uh, I watched only the starting, and that that's maybe because, um, and that's maybe because last season it was perfectly because Max won and stuff like that, and now, yeah, it's a little bit getting annoying.
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Maybe that's the orange culture here.
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If you know Max is not winning, you don't watch.
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Ah, I am so happy when Max doesn't win and I'm happy to see that others are winning.
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It makes for a better race.
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I mean, it was a stretch of time there not to talk all about f1, but there was a stretch to have time where the you know, even on the television they were focusing on the middle of the pack because it was a better race, because max was always so far ahead.
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At least yesterday we could talk about it, because by the time this is released if someone doesn't know the results then you know they.
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They probably won't be watching it.
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But just to see norris finish so far ahead of max just made me happy yeah, indeed, but that that was very crazy.
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It was, uh, I'm not sure, 16 or 17 minutes, sorry, seconds before it's.
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It's just crazy how fast Norris was at the second half of the season.
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Oh, I like it.
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I can see, indeed for other countries, that there are some better competitions on it and truly had the better for Formula 1.
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But yeah, I'm a Dutch guy so I was hating it.
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No, no, I understand, you have to have loyalty.
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Just as a side note, I did go to F1 Miami, where Norris won his first race and started this whole trend of Max losing, which I'm so happy.
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Yeah, indeed, you know, it's like I I said it makes weird days, but to uh to bring it back, um, you know, one of the things that we were talking about and uh, that's, you know, strikes us some interest, uh, that I believe you also have some interest in is this whole, uh, fabric type stuff.
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This fabric type stuff, chris, I'm not talking fabric like to make clothes, I'm talking about a different type of fabric, and even more so because I've seen some articles and I've seen some information that Dynamics 365 Business Central now can work with fabric.
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I don't know what it's making, but it can work with Fabric.
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So if you would, bert, if you could help shed some light on, maybe, what is Fabric, what is MS Fabric, and then, how does it fit with Business Central and how does it fit in the Dynamics 365 ecosystem?
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There's a lot there.
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There's quite a lot and indeed I can know that people don't know Microsoft Fabric because it is quite a new product in this time.
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I thought in May last year Microsoft has launched Fabric and in November last year it went GA for it.
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And what you see mostly when you cut a data warehouse because Fabric is all about data warehousing and consulting and analyzing your data what the problem mostly is is that the integrations are very complex.
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When you move or starting to move from, for example, bicentral or Sales, or you have got another solution and you want to move that data to a data warehouse or a database, it is quite cumbersome and difficult, especially when you are upgrading your solutions and one data is stored in one database for analytics and another one in another database.
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You want to combine it and you have to move all the data and there you can see that people are losing interest Even right now.
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You've got quite good examples in Azure with Data Factory and Synapse Links and all that kind of stuff, and that's what Marks of Fabric wants to cover all Just a very easy to implement and to import data inside Marks of Fabric in it.
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That's in a few sentences from what Mark's Fabric is Just to have have easy import your data in it, analyze it and then show it to the world.
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In that case, oh okay, so is Microsoft Fabric in essence a different type of data warehouse or a data warehouse in Azure that is intended to have centralization of data or easier centralization of data?
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I hear of this fabric and I also see.
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I enjoy the terms because I associate them with many things Fabric I always think of sewing and clothing, and then MS Fabric also has another thing.
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It's called lakes and one lakes and data lakes, and I think of lakes as swimming lakes.
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So maybe you could shed some light on the terminology of a data lake or a lake and how it relates to fabric.
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Well, what I always say, what you say is, when you are similar to a lake, is how you can swim in it.
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In a lake, there are tons and millions of data in it.
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For example, you can swim in it and it's quite large and you don't know how large it is.
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And what Microsoft wants to cover is and that's also the marketing function of Microsoft is they call it One Lake Because first, before Fabric, you see that there are quite a couple of data lakes in it.
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Maybe you've got a data lake for your finance data, for your marketing data or HR data, and in one lake that is just all stored in one data lake.
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Underneath one lake there is Azure Data Lake, but it calls One Lake.
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So if you're importing the data inside the One Lake and everybody consumes that data in there, so you don't have to export it anymore to another data lake you can easily combine it just from one silo to another silo, and that's the perfect thing about the one lake in that.
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So what I said, you don't have to have separate data lakes anymore, you can just do it in one lake, and it's mostly similar to what you have in your OneDrive storage.
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Onedrive is all what you gather around, you put it in there and everybody can use it.
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You can share it, you can use it on your own, and that's just the one leg for data warehousing.
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In that case, so I guess I'm trying to have a bigger grasp, because back in early days when you're on-prem, you know, you just stand up a separate SQL database and then you're just like, oh, let's just throw everything in there, pull everything in one SQL database, and then you create SSRS, report or connect some other tools.
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So now that we're online, is this sort of a replacement, or is Fabric sort of a replacement of that concept back then?
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Sort of sort of back then Sort of sort of, because what you see in the SQL database it is all structured, it's all structured data and inside your one lake you can have unstructured data and structured data.
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In that case you have got a lake house or a warehouse.
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So an unstructured data is just data that you put in there and you really don't know what it is, what type of data is in there.
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It is all unstructured and that you are going to convert from an unstructured data set to a structured data set and that you are going to convert from an unstructured data set to a structured data set and there a warehouse is more.
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Yeah, the same.
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Chris, what you said is on an on-prem SQL server where you then connect all your tools on it.
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So that's mostly based here on a, a warehouse and what you can easily do also with a warehouse, also with a Lagos, that you can attach not attach, sorry you can see it like in SQL database in the front-end, so you can use your SQL commandlets and all that stuff you can use there.
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Also you connect with the other parties that can read SQL.
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But in the backend it is not stored in just tables but it's in a Delta Parquet format in it.
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So with it being unstructured?
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I hear a lot of structured and unstructured data so maybe we'll go all over the place.
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So with it being structured data, it's normalized in a sense of how we would think of like a customer table, where it's defined as you have these fields, elements and records in here.
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To come up with a customer, a data lake would be just data that anybody throws in there, as you're saying, because it's unstructured.
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But how would they get it in and get it out if it's not structured?
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Because is it unstructured in the sense that the application isn't holding the structure, but the user of the data is defining the structure of what they're putting in?
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Because if I had customer data in one system, could I put it in the data lake or the one lake and then retrieve that information out or combine it with customers of another system that may have a different structure.
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This whole I'm trying to visualize structure and unstructured data and and how we can associate or view it yeah, mostly what you can say about.
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Yeah, sometimes it is quite difficult because when you are, for example, base central, how you've got a customer table, you're importing that in your lake house and then you say, okay, it is unstructured, even though that in BIS Central it is structured because you've got rows and columns and stuff like that.
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But when you want to report something, you want a better structure on it, so like you've got some kind of dimensions on it.
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What's your open demands on it?
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All that kinds of dimensions you can create on there and that's how you combine also with other sources that you put in your warehouse where it is structured and where a user can immediately report on it in that case.
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So it's more like a structured data that the user can immediately build a Power BI, report on it without any merging or remove columns and create dimensions on it.
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This is interesting.
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How does that work with performance?
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See, I know SQL rather well so I'm trying to anyone else that may understand SQL or visualize SQL.
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So, sql you have the rows and the columns, as we had discussed, within the tables.
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You can have multiple tables within a database.
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In large data sets often there are indexes that have information and just a quick retrieval of the data with the columns that they include and the columns that they're sorted by clustered and non-clustered indexes.
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If you have unstructured data, how does it work with performance when you have a large data set with this?
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Or is it just magic?
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Yeah, it's always magic.
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No, no, it is stored not in a table, what you said with the columns and the rows and stuff like that.
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It is stored inside One Lake in a Delta per K file, and Delta per K file is just optimized for very fast reading for that performance.
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It is also and parquet file is also not based, what I said, on rows, but it is more based on columns, so you can very easily search, combine columns together and read your data, because if you combine multiple Parquet files and merge it to a structured data table sorry, a structured data set that's also based on a Parquet file.
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So it's all based on that particular Delta Parquet format and that's why it is reading that fast, faster.
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Yeah, yeah, so with that it sounds like then is so Fabric is more intended to be, as Chris had talked about, where you have information, a SQL survey in early days, just trying to equate it where you copy the data to a data warehouse.
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So Fabric is meant to be a destination for a lot of data, not necessarily transactional.
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So the intention of because you had mentioned that the files are meant for fast reading, so you wouldn't use it as a lake to store your data for your transaction, your day-to-day use, it would be where you would offload your data so that it could be read and queried upon.
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So that's, in essence, how it's used.
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yeah, perfect, perfect now with with fabric, um, Fabric.
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I'm trying to again trying to understand this fully, right?
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So when you're implementing Business Central Online and it kind, of people always have that question.
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It's like how do I report against it, how do I build a data warehouse?
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So should that be a natural path for organizations?
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They should always consider fabric to do some reading of reports or maybe utilizing Copilot.
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Right Now that you have this larger, more of a fabric one like database, Could you call it database?
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Wait, can you still?
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Yeah, I think you could feel it Okay.
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And utilizing all the Copilot tools.
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Is that a natural?
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Should that be a natural path for organizations when they get to Business Central Online?
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No, I think, and that's what you see also in Business Central.
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You've got some very good reporting with the NLS views, currently also with the Excel reporting, and I'm really a fan of that one, and I think if you're quite a small company, you can use the Excel reporting and there are also now some Power BI reports that consumes the APIs on it.
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That's enough for just a small customer or a small company, I think.
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If you want to more complex data, combining data from Business Central with an HR system, or even if you're using Power Platform with Dataverse on it, and if you want to combine that data, I think, then it's really interesting to go to Fabric in that case.
00:22:57.382 --> 00:23:21.432
So it's, if you have just reporting and, yeah, reporting is more, I think, about showing a list or combining two, three tables together, and that's your overview Then I think Dissental right now has the tools in it for it.
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Right now has the tools in it for it.
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But if you want to one step further, then I definitely want to recommend Marks of Fabric in it.
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Yeah, with Fabric and Business Central it's what we talked about with tools you had mentioned to make it easier to import data into the lake.
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I love calling it a lake.
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I always want to think of swimming and fishing, and that's how I look at it.
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There's a lot of data in the big lake.
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It's fish swimming around.
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Is the data we have to drop our fishing pole in to pull out the data?
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What is built in or what is set up with Business Central that allows for the easy importing of data within or exporting?
00:24:06.164 --> 00:24:15.194
However, if it goes that way into the data lake or into Fabric, into a data lake or one lake in Fabric?
00:24:15.576 --> 00:24:16.696
Indeed, indeed.
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It's sometimes confusing all those terms Indeed, all those terms, indeed.
00:24:28.441 --> 00:24:53.073
But if currently the situation is that you can only consume data from BizCenter into Fabric with the APIs that's the official statement of Microsoft in it and if you have quite a big database on it with a lot of tables and with a high volume of data, then it can be quite slow, I think, because it will affect your NSDs.
00:24:53.073 --> 00:25:08.907
And mostly when I look at our customers, they said okay, I want to have a two hour import from BizCentral into my fabric in my one day.
00:25:08.907 --> 00:25:31.031
In that case and that's not quite an interesting story because we've got one customer that does it every each two hours with the APIs and eventually they said okay, we have quite a performance drop when it is running.
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We don't know what it was running, but in the telemetry we saw okay, hey, but you are using those APIs quite heavily, so just put them off.
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And the performance went very well.
00:25:46.101 --> 00:25:59.752
And that's also what two years ago the Microsoft two guys from Microsoft has implemented BC2-ADLS, that is, a Bicentral to Azure Data Lake.
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So they're exporting data to Azure Data Lake.
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So they're exporting data from Base Central to Azure Data Lake and in deltas.
00:26:07.871 --> 00:26:18.289
So in that case it doesn't have a full export but only the deltas in it and it was extremely fast for it.
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It just exported in CSV and in this case it was Azure Data Lake.
00:26:23.348 --> 00:26:31.323
It will combine it and you can use it in Power BI and that tool.
00:26:31.442 --> 00:26:42.050
I thought, ok, when Microsoft Fabric was arrived, why don't we use the One Lake APIs just to store this central data into Microsoft Fabric?
00:26:42.050 --> 00:26:55.428
So in that case now B2A2S is also can move data very fast from business central to Fabric, in this case inside your OneLake.
00:26:55.428 --> 00:26:59.048
So in that case you can consume it.
00:26:59.048 --> 00:27:19.526
That test, just yeah, there's no source tool, but I definitely and that's a temporary tool, but I'm just betting on another one and that if that is official, then I will be crazy it is mirroring a SQL database.
00:27:19.526 --> 00:27:39.887
So in that case you very easily in Microsoft Fabric say, okay, I want this Azure SQL Server with this database, with those tables, and it is directly mirrored inside my Fabric space.
00:27:39.887 --> 00:27:50.369
So with a couple of seconds maybe one or two seconds if you change your business central data, it is there inside your Microsoft Fabric.
00:27:50.369 --> 00:27:53.667
So that will be fantastic.
00:27:55.342 --> 00:28:05.930
That does sound fantastic and it affords the opportunity to have some enhanced reporting without impacting business central, but you still have more or less real-time reporting.
00:28:05.930 --> 00:28:10.530
If the, as you had mentioned, I'm hooked on the analysis views.
00:28:10.530 --> 00:28:19.853
The analysis views, with being able to pivot and export and even save those views, is, what we say sometimes, a game changer.
00:28:19.853 --> 00:28:28.420
It gives users the ability to, once you have it, once you have a list established, and even being able to create pages off of queries.
00:28:28.420 --> 00:28:31.670
But now you can take that information a bit broader.
00:28:31.670 --> 00:28:37.786
It cuts down on the needs to have a lot of these one-dimensional I call them reports where it's always look at this information.
00:28:37.786 --> 00:28:42.722
In this view, that's the user of the application sort of control, as long as I mean.
00:28:42.722 --> 00:28:46.826
Again, it's important to understand the data, but they can control the information that they're looking at.
00:28:46.826 --> 00:28:54.891
As you were talking about this, with the data going from Business Central into Fabric, it made me think of Dataverse.
00:28:54.891 --> 00:28:59.834
Where does Dataverse or is that an outdated term now fit in all of?
00:28:59.875 --> 00:29:00.015
this?
00:29:00.015 --> 00:29:03.237
No, no, no, dataverse is not an old term.
00:29:03.237 --> 00:29:03.557
It is.
00:29:03.557 --> 00:29:12.391
Yeah, it is part of the Power Platform solution.
00:29:12.391 --> 00:29:23.446
So if you're using Power Platform, dataverse is the database of it, so that's the storage and there are also some connectors from Abyss Central to Dataverse of it.
00:29:23.446 --> 00:29:47.436
But Dataverse, what you said, is more for the power platform and also, if you are financing operations, it stores the data inside Dataverse and also with dynamic sales and stuff like that, and also with dynamic sales and stuff like that.
00:29:48.440 --> 00:29:53.316
But Dataverse is not a warehouse solution because it is quite expensive in that case.
00:29:53.316 --> 00:30:03.640
But you can also create some kind of shortcut to move your data from Dataverse inside Fabric.
00:30:03.640 --> 00:30:19.910
So in that case, what you can do, what you said, brett, with your analyst views, it is just a one-dimension view and that's really fantastic and really a game changer, I think, also for especially, the end users.
00:30:19.910 --> 00:30:33.942
For example, if you have got a PowerApp and you've got your BIScentral and both are representing inside Fabric, you can really do quite a lot of analysis on that one.
00:30:33.942 --> 00:30:50.703
So in that case, it is really fantastic just to have your data from the Power Platform combined with BizCentral and that is really fantastic with your NLS on it.
00:30:53.067 --> 00:30:58.699
So is Dataverse another unstructured database that's meant for a transactional database, or is it?
00:30:58.699 --> 00:31:04.717
I don't mean to deviate from fabric, but now you have my mind going on this.
00:31:04.717 --> 00:31:07.805
No, it is With the Eye of the Tiger song in my head.
00:31:07.805 --> 00:31:08.267
Yeah, indeed.
00:31:10.205 --> 00:31:11.351
No, no, dataverse is more.
00:31:11.351 --> 00:31:13.891
It is a structured database for it.
00:31:13.891 --> 00:31:21.752
So it's more, chris, what you said, it's the old SQL database, but then in the cloud on that one.
00:31:21.752 --> 00:31:37.974
So there you can create your columns, your tables, with a specific column type and with the schema on it and store your transactions in there.
00:31:38.765 --> 00:31:46.538
So back to Fabric with Business Central and hopefully, as you had mentioned, we'll get to the point where it could be mirrored in real time.
00:31:47.306 --> 00:31:52.025
You had mentioned that Dataverse isn't the solution for warehousing because it's expensive.
00:31:52.025 --> 00:32:03.859
I am one who doesn't follow pricing for a reason because there's no way I could ever understand Microsoft licensing and know what I ever pretend to.
00:32:03.859 --> 00:32:05.240
I gave up on that.
00:32:05.240 --> 00:32:07.933
I focus on the technical and functional aspect of it.
00:32:07.933 --> 00:32:11.748
But how costly is fabric?
00:32:11.748 --> 00:32:26.781
And then also with Business Central you can have data retention policies to minimize the cost of the database within Business Central.
00:32:26.781 --> 00:32:33.713
Is it something where, if you move the data over to Fabric, you can report on both?
00:32:33.713 --> 00:32:49.474
And if you move the data over to Fabric and then you also adjust your retention policies within Business Central to reduce the amount of data that you have within your database, what would be the cost difference for a solution like that?
00:32:49.474 --> 00:32:53.375
And then also, could you report off of both of them simultaneously?
00:32:53.375 --> 00:33:04.498
I guess you could, because if you had real-time mirroring into data like one lake of fabric, you could look at the data in one view.
00:33:05.891 --> 00:33:08.332
Yeah, indeed, and I'm also not a licensed guy.
00:33:08.332 --> 00:33:21.134
I think, indeed, if you are doing that, especially on the Microsoft, you'll get a full day job, maybe more than that one one, because there are a lot of exceptions and it's really crazy on it.
00:33:24.067 --> 00:33:27.876
Isn't it just a moment of general comment on the pricing?
00:33:27.876 --> 00:33:43.655
I thought Fabric is like it's Azure right you just pay by the hour of use with a certain storage, or something like that as well yeah, you, you pay in, indeed, for the storage and the uh uh excuse, and that's yeah.
00:33:43.696 --> 00:33:47.884
So so in that case, um, uh, chris, that is indeed right.
00:33:47.884 --> 00:34:09.144
When you have got an sq, that represents a capacity unit and if you multiply it by 24 and a couple of metrics, then you can get, for example, 170,000 seconds of consuming the things.
00:34:09.144 --> 00:34:26.114
So in that case, when you are merging or combining reports sorry, data on it, it is consuming seconds on it, and that's where the price is in that case.
00:34:26.114 --> 00:34:41.974
But what I always say because, as you agree, brad, the license guide is really great for Microsoft there is a free app that you can install it.
00:34:41.974 --> 00:34:46.197
It's called the Capacity Metrics app.
00:34:46.197 --> 00:34:54.572
It is from Microsoft and then there you can analyze how many seconds or capacity units something is using.
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