התמלול המלא של Ep. 30 - Telling Stories with Data

00:04:33.495 And then I wanted to learn more about Winter Olympics. 00:04:33.495 --> 00:04:35.767 So created a report on Winter Olympics. 00:04:35.767 --> 00:04:43.552 So I think that's how I decided that I need to specialize in Power BI, specifically storytelling in Power BI. 00:04:43.591 --> 00:04:44.612 Yeah. 00:04:44.612 --> 00:04:47.451 So I do have a question about that. 00:04:47.451 --> 00:04:53.732 So the stuff that I've seen some of the things you do, the storytelling makes less sense because like you said, it's kind of a fixed data set. 00:04:53.732 --> 00:04:56.091 And then you're trying to see what you can pull out. 00:04:56.091 --> 00:05:03.831 The thing that I always struggle with, and I think it can be done is what it like, where's the line for business data? 00:05:03.831 --> 00:05:12.764 Because the problem is like, let's say, you know, you take that Starbucks data, you can tell a story from a period of time, you can review it, you can make sure everything makes sense. 00:05:12.764 --> 00:05:20.043 But if you make a business report and you hand it off to someone, well, if sales change, that story's changed or power BI is very interactive. 00:05:20.043 --> 00:05:23.869 And so you don't have a lot of control over what they're going to like click and dig into. 00:05:23.869 --> 00:05:44.605 So for more dynamic data sets, like what, what stuff can you still do to help with great question so when I start creating reports I have two ways I do it the first is a very simple EDA like exploratory data analysis that can be done with your report, put in slicers, click stuff. 00:05:44.605 --> 00:05:49.187 You'll see everything interact with each other, cross highlight, cross filtering, drill throughs happening. 00:05:49.187 --> 00:05:53.029 And then when it comes to business purpose, the first thing is requirement gathering. 00:05:53.029 --> 00:05:57.091 I first kind of have a conversation to know why do you want this report? 00:05:57.091 --> 00:05:58.732 What are you trying to solve? 00:05:58.752 --> 00:06:07.456 Now say if they are trying to increase their sales and then I go into more data, are you looking on the marketing side or the production size? 00:06:07.456 --> 00:06:45.836 So my thought on this is it actually depends on the requirements you really need to dig deep into the data to see what type of data is available for you and then once you have your data you can get a story out of it like because of this this is happening and you know like there are the four pillars of analysis you have diagnostic prescriptive predictive so I mean just following that really helps you get it in the business side plus I always so whenever I work on projects I make sure I have page of EDA analysis as well because that helps both me and the end user understand what type of data I have in my report. 00:06:46.471 --> 00:06:48.612 Yeah, I think that makes sense. 00:06:49.432 --> 00:07:10.271 I think business intelligence is kind of interesting because I'm

sure I've said a bunch of times on this show, but, um, it's one of the most iterative IT fields that I've seen or been involved in where like a lot of times you do basic requirements gathering for something like let's say a server to run something. 00:07:10.271 --> 00:07:15.331 And generally speaking, you may have some surprises, but the requirements match. 00:07:15.346 --> 00:07:17.757 kind of what you end up with a lot of the times. 00:07:18.338 --> 00:07:21.922 That has not been my experience with Power BI reporting or reporting in general. 00:07:21.922 --> 00:07:29.348 um It is a coin toss as to whether what they said that they wanted is going to be what they actually want once you put it in front of them. 00:07:29.348 --> 00:07:41.059 And so I think a lot of the work that we do is a lot, it is kind of more, we're kind of in the midpoint between sort of classic IT and say like a graphic designer or a web designer. 00:07:41.059 --> 00:07:45.706 Cause if you're one of those, kind of folks, then you actually have to plan in change orders. 00:07:45.706 --> 00:08:01.730 And you have to assume that like you have to figure out how to fail fast with the design and the requirements gathering because otherwise it's really easy to do all this building in a cave or a bunker somewhere and then come back and then it's not what they wanted at all, even though that's what they told you to build. 00:08:02.165 --> 00:08:02.646 That's right. 00:08:02.646 --> 00:08:08.610 And one thing I like to add is when I do requirement gathering, I don't create a checklist. 00:08:08.610 --> 00:08:12.031 actually go cross out things that they do not require. 00:08:12.031 --> 00:08:16.504 Like you said, instead of me telling them, this is what required. 00:08:16.504 --> 00:08:18.916 I just cross out that they don't need this. 00:08:18.916 --> 00:08:21.677 So I think that makes it a little easier for me to. 00:08:21.958 --> 00:08:41.899 Yeah, I've, I, when I do a scope of work, a lot of times I'll not only have assumptions, but like, things out of scope or things I'm assuming that's not the case, but also like a lot number of times you're, it's not just uh a greenfield sort of project, but they have something Excel or they have something crystal reports and you're trying to migrate it. 00:08:41.899 --> 00:08:48.865 And there's been plenty of times where you're going through the business logic and you're like, how is, you're asking them or talking to them, how is this calculated? 00:08:48.865 --> 00:08:51.813 And then you find out they, no one's looked at this number. 00:08:51.884 --> 00:08:52.736 Yes. 00:08:53.187 --> 00:08:53.962 Right. 00:08:53.962 --> 00:08:54.753 something like that. 00:08:54.753 --> 00:09:05.336 um So I agree, it is a challenging field to be in because we already talked about there's a certain amount of creativity and thought that needs to go into it. 00:09:05.336 --> 00:09:16.429 But then, um you know, sometimes I compare it to like therapists for people's data because we really do have to kind of like help them talk through what they actually want and sort of help them help themselves with this kind of stuff. 00:09:16.562 --> 00:09:17.202 Right. 00:09:17.202 --> 00:09:27.293 And like I think to find a balance between creativity and analytics data also is important because you cannot be very creative or you cannot be very data oriented. 00:09:27.293 --> 00:09:31.557 To find that balance is also somewhere like a little challenging for me. 00:09:32.604 --> 00:09:33.304 Yeah. 00:09:33.304 --> 00:09:39.090 So, um, so we kind of already mentioned, um you're, you're very involved with the community. 00:09:39.090 --> 00:09:43.495 got, uh, involved with the, the data visoral championship competition. 00:09:43.495 --> 00:09:45.476 What was that path kind of look like for you? 00:09:45.476 --> 00:09:49.250 How did you get involved and how did the community help you with all of that? 00:09:49.417 --> 00:09:57.375 Yes, so about the data with Championship, I actually just accidentally stumbled upon it when I was scrolling through the fabric community. 00:09:57.375 --> 00:10:00.688 Yeah, I saw Shannon posted on LinkedIn and I was like, why not? 00:10:00.688 --> 00:10:05.443 Let's just take a shot and trust me, it's changed my life completely. 00:10:05.462 --> 00:10:15.731 And also like quick things like about the fabric community is It has helped me both on the technical side as well as on a personal level. 00:10:15.731 --> 00:10:18.192 Like, know, in fabric community, go ask questions. 00:10:18.192 --> 00:10:23.826 So from asking questions to answering questions, and then they always have these small contests. 00:10:23.826 --> 00:10:25.417 Like you could create a sticker. 00:10:25.417 --> 00:10:26.217 You're creative. 00:10:26.217 --> 00:10:28.278 Just design a sticker and submit to it. 00:10:28.278 --> 00:10:31.080 And I actually won two of the sticker contest too. 00:10:31.080 --> 00:10:34.186 So I think like, I mean, even technically. 00:10:34.186 --> 00:10:47.111 I was able to contribute and even passion like I could follow my passion too and something that I do on a regular basis is I spend at least 15 minutes a day just scrolling through the fabric community. 00:10:47.111 --> 00:11:04.110 I just see what people have asked or answered sometimes just giving a quick kudo or giving a comment makes a difference to me as well as to the other person right so I think that's how I got involved into the fabric community and like I said it really made a huge difference. 00:11:04.110 --> 00:11:29.312 for me because when I was on stage competing like those 20 minutes were very difficult for me but when I saw that there are like lots of people cheering for me and I have a lot of support like you feel seen and I think that's something uh my heart was full so like when I was competing I was so happy I already felt like a winner Yeah, I was there for the first one. 00:11:29.312 --> 00:11:35.991 I couldn't make it

for the second one because I was busy helping with the tabular editor booth, but, it was, I think it was a cool event all around. 00:11:35.991 --> 00:11:44.072 And I think it, it is something you should be really proud of yourself because if I remember correctly, there's multiple stages to kind of make it to the, to the finals and all of that. 00:11:44.072 --> 00:11:56.063 But also, um, you know, I, I don't think a ton of people put in a lot of the effort like you do with, with these report designs or their projects or that kind of stuff. 00:11:56.166 --> 00:12:08.676 I mean, again, if Reddit is any indication and it may be a skewed one, don't know, but there's a lot of the people who are posting and they're looking for feedback. 00:12:08.676 --> 00:12:18.374 kind of it's, it doesn't feel like there's a lot of time taken to kind of refine the work or think about how it's going to be used. 00:12:18.695 --> 00:12:30.244 A lot of people will add decorative elements, not necessarily ones that help with the visualization, but I'll see people like change the colors or change the backgrounds or all this kind of stuff. 00:12:30.384 --> 00:12:36.755 But I think, you know, I've seen some of the designs that you do and they feel very cohesive. 00:12:36.755 --> 00:12:40.226 They feel like you said that you're trying to think about a narrative. 00:12:40.226 --> 00:12:57.279 And I think, you can correct me if I'm wrong in this, but I think you kind of have to have like a patience and a willingness to pause and stop because again, and I'm guilty of this with like, report design, like I'm not a good designer. 00:12:57.900 --> 00:13:14.570 And generally, um, even if, even if I was doing something like, like more of a fun data set or something like that, I'm very much like, just focused on the problem in front of me and trying to make a list and all this kind of stuff and not thinking about how the pieces fit together or what the general flow is. 00:13:14.730 --> 00:13:23.928 And like, for me, like I said, I've had to come up with like all of these random rules of thumb to force myself to kind of slow down. 00:13:23.928 --> 00:13:31.051 So like what is the process for you or what does it feel like when you're working through a design? 00:13:31.823 --> 00:13:45.307 uh Yeah, to be honest, I spend more time understanding the data than actually creating the report because I think like my Power BI scales are solid, but I really need to gain the knowledge about the data and the semantic modeling. 00:13:45.307 --> 00:13:47.908 So I spend most of my time there. 00:13:47.908 --> 00:13:50.609 And then like you said, I have a story in mind. 00:13:50.609 --> 00:13:52.129 So I have a narrative. 00:13:52.129 --> 00:13:54.409 I know that the end user is looking for this. 00:13:54.409 --> 00:13:56.610 They want this question to be answered. 00:13:56.610 --> 00:14:00.527 And then I start with I do something called so what? 00:14:00.527 --> 00:14:03.908 So I see something, I see a

number and I'm like, so what? 00:14:03.908 --> 00:14:05.190 And then it's okay. 00:14:05.190 --> 00:14:06.932 This is going to make this difference. 00:14:06.932 --> 00:14:09.352 And then so what, what is this going to do? 00:14:09.352 --> 00:14:11.875 So I mean, that's how I start thinking. 00:14:11.875 --> 00:14:34.326 And I think eventually what happens is once you keep making reports, like the very first report that I made had so much data crammed into it because I was a newbie and I was like, I need to put in all the all the charts that I know, funnel chart, pie chart, all the charts were there and then slowly with practice I understood, nope, no one cares if I have 10 charts on my dashboard. 00:14:34.326 --> 00:14:37.428 I need to have four and the four charts need to tell a story. 00:14:37.428 --> 00:14:39.870 So I think it comes with practice. 00:14:40.899 --> 00:14:46.982 I mean getting a balance between the design, getting a cohesive report, getting a story out of it. 00:14:46.982 --> 00:14:49.485 At the same time, showing an analysis. 00:14:49.485 --> 00:14:51.105 It all comes with practice. 00:14:51.105 --> 00:15:00.652 Plus I would like to add on to this thing where you just mentioned people ask for feedback, but do they go back and make sure they make those corrections? 00:15:00.652 --> 00:15:01.393 We don't know. 00:15:01.393 --> 00:15:12.173 So I think Power BI reporting is more of like a feedback oriented or like an iterative process, something that I like, you might not like something that I like, my client might not like. 00:15:12.173 --> 00:15:15.250 So I have to go back, come back, back and forth, back and forth. 00:15:15.250 --> 00:15:16.523 That happens a lot. 00:15:16.687 --> 00:15:18.217 Yeah, yeah, no, it will. 00:15:18.217 --> 00:15:20.849 And it's it's so funny. 00:15:20.849 --> 00:15:27.230 um Again, I bring up right at a lot just because that's I'm I'm on there the same way that you're on the community forums. 00:15:27.230 --> 00:15:40.056 And it's funny because every like three months I see someone who's really, really frustrated that they're being asked to do things that they don't think are of the best standard, the best quality, the best aesthetics. 00:15:40.297 --> 00:15:46.048 And I've had to explain to them our work a lot of times is like being like a car mechanic. 00:15:46.344 --> 00:15:54.663 And if someone asks for tinted windows and you think tinted windows are ugly, you can explain why maybe that's not a good choice. 00:15:54.663 --> 00:16:01.504 And as long as it's, uh, you know, not illegal at the end of the day, if the customer wants that, then that's what you do. 00:16:01.624 --> 00:16:13.701 And like for this recent project I'm on did some high level, um, reporting for a school board and you know, like very high level kind of folks. 00:16:13.701 --> 00:16:15.371 And they love their radio gauges. 00:16:15.371 --> 00:16:17.152 They love them to death. 00:16:17.493 --> 00:16:23.565 I know that the human

eye is better at reading a pair of bar charts or whatever, but that's what they want. 00:16:23.565 --> 00:16:24.375 And that's what they get. 00:16:24.375 --> 00:16:32.740 Um, but yeah, I think I agree that thinking a lot about the, what is important? 00:16:32.740 --> 00:16:36.400 think, um, what can really help people? 00:16:36.400 --> 00:16:40.527 Like you said, that experience is trying to shadow people or asking people. 00:16:40.527 --> 00:16:42.048 Okay, here's your existing report. 00:16:42.048 --> 00:16:46.933 If this number is out of whack, what action do you take based off of that? 00:16:46.933 --> 00:16:52.524 um But yeah, you definitely have to learn certain pragmatism after a while for sure. 00:16:52.524 --> 00:17:01.720 Yes, and just to add, like I had a recent client who wanted me to have gradient colors in their reports and I was like, no, that's not accessible. 00:17:01.720 --> 00:17:07.214 But, you know, I had to do it because they wanted it and I had to do it even though I don't like it. 00:17:08.092 --> 00:17:10.172 Yeah. 00:17:10.633 --> 00:17:14.534 So um I've seen you. 00:17:15.555 --> 00:17:20.096 Why I don't think I've seen you speak, but I've seen you have a lot of presentations and that kind of stuff. 00:17:20.096 --> 00:17:24.288 How did you get involved with like speaking in the community and all that? 00:17:24.679 --> 00:17:54.259 Yes, so first I'll start so English is not my first language and When I moved to the US I was very scared people are going to judge me they're going to make fun of my accent and I mean there was a lot of hesitance, but once I started there is no stopping because the first very first time I delivered a speaking session was virtual and There were three to four people who connected with me on LinkedIn. 00:17:54.259 --> 00:17:56.298 They messaged me saying I did a great job. 00:17:56.298 --> 00:18:00.020 They loved my demos and they asked me when I'm presenting next. 00:18:00.020 --> 00:18:05.083 I think that one message uh encouraged me and motivated me. 00:18:05.083 --> 00:18:06.634 People do not care about my accent. 00:18:06.634 --> 00:18:10.425 It's okay if they do not understand, but they're able to see what I'm doing. 00:18:10.425 --> 00:18:13.446 And I think that that is a motivation that you need. 00:18:13.446 --> 00:18:21.029 And uh I think Kevin Chant was the one who gave me my first opportunity to talk at Data Weekender. 00:18:21.349 --> 00:18:47.548 and I think I was the only new speaker all of them were very renowned speakers and was like oops where did I get in and then I think like there has to be just one person who shows you the path and then you just keep going and even now like when I deliver a speech I am sure I stammer I sometimes forget English words because since English is not my first language I think in a different language and speak it out in English, right? 00:18:47.548 --> 00:18:54.487 But I've accepted the fact that I cannot be perfect, but for me, the main purpose

of I... 00:18:54.862 --> 00:18:59.374 main purpose of doing the speaking sessions is to share what I know. 00:18:59.374 --> 00:19:03.115 If I can create a Power BI visual in 10 minutes, how do I do it? 00:19:03.115 --> 00:19:06.076 Let me share it with everyone so that they could do it too. 00:19:06.076 --> 00:19:07.438 I don't want to gatekeep it. 00:19:07.438 --> 00:19:10.368 So for me, that's how I got into the speaking. 00:19:10.368 --> 00:19:13.951 And when I see people appreciate it, people do not care about my accent. 00:19:13.951 --> 00:19:15.662 They don't care how I speak. 00:19:15.662 --> 00:19:18.452 It's more of what's the value I'm giving them. 00:19:18.452 --> 00:19:19.743 That's what matters. 00:19:19.743 --> 00:19:21.734 I think that's what encourages me. 00:19:21.734 --> 00:19:30.321 So whenever I start my speaking sessions, I do not think anymore about my accent or that English is not my first language, I just go for it. 00:19:30.866 --> 00:19:36.882 Yeah, and I think tech is uh compared to other certain fields in the US, like fairly multicultural. 00:19:36.882 --> 00:19:42.247 there's a, have a lot of people who've immigrated here and um work in this field. 00:19:42.247 --> 00:19:44.107 And I think that's definitely a reasonable concern. 00:19:44.107 --> 00:19:51.174 uh Maybe someday I'll be able to give a presentation in Spanish, uh but uh if I ever did, it still be very difficult. 00:19:51.174 --> 00:19:55.517 So I definitely admire that you're able to do that. 00:19:55.517 --> 00:19:58.803 um Yeah, I... 00:19:58.803 --> 00:20:04.056 got cornered at a SQL Saturday after party and was convinced to present my local user group. 00:20:04.056 --> 00:20:07.567 And I think for me too, it, kind of changed the trajectory of my career. 00:20:07.567 --> 00:20:16.561 Cause one, it forces whenever you make content or you communicate something, it forces you to learn on a much deeper kind of level. 00:20:16.701 --> 00:20:23.826 But also I, I've benefited so much from having these connections, um, and even in simple stuff. 00:20:23.826 --> 00:20:31.757 So, you know, whenever I do consulting, a lot of my hourly rate is not what's ever in my head, but how well I can get an answer. 00:20:31.896 --> 00:20:41.922 And so there's been plenty of times that I'll DM someone about, Hey, I have no idea what's going on with like this fabric warehouse thing, or you know, what's going on with this performance. 00:20:41.922 --> 00:20:44.502 Um, every once in a while I make a fool of myself. 00:20:44.502 --> 00:20:56.538 Uh, I had a, was, uh, emailing some folks about this issue with fabric warehouses and the execution plan said it thought it was going to be 200 billion rows and 72 terabytes of data. 00:20:56.864 --> 00:21:00.575 And someone told me to update the stats and I was taking a look at the stats. 00:21:00.575 --> 00:21:02.207 I'm like, well, no, this looks right. 00:21:02.207 --> 00:21:03.007 The stats are there. 00:21:03.007 --> 00:21:04.167 They're updated. 00:21:04.167 --> 00:21:09.320 But then it was doing a join between a uh 10 million row table and a 1 million row table. 00:21:09.320 --> 00:21:11.051 And there was only 88 unique values. 00:21:11.051 --> 00:21:13.563 So it actually was doing a lot of work. 00:21:13.563 --> 00:21:14.653 So we got that sorted out. 00:21:14.653 --> 00:21:21.637 But, um, but yeah, I think, I think it really can change your career. 00:21:21.637 --> 00:21:35.430 And unfortunately post pandemic, user groups aren't as There are some online ones, like you said, but the user groups tend to be a very low stakes sort of way um to get involved. 00:21:35.490 --> 00:21:50.779 people are very, very patient with that and it can, even if you're new, it can be really helpful to hear someone's story because you can forget about what the pain points are or something, or a lot of times see how someone else learns. 00:21:50.779 --> 00:22:05.510 um mean, I did, uh, I did a week long workshop a year or two ago and I learned some Power BI hotkeys that I didn't know about from the students, which was a little humbling. 00:22:05.510 --> 00:22:08.304 um So, but it's always, it's always good. 00:22:08.304 --> 00:22:10.306 So um that's awesome. 00:22:10.561 --> 00:22:21.838 Yeah, and even like when I was a beginner, the way I got into the community was I just started small, like hanging out in the community, like I said, like giving kudos to people, commenting on posts. 00:22:21.838 --> 00:22:28.343 And then once I felt comfortable, then I started dipping my toes in all these little challenges or the contest that take place. 00:22:28.343 --> 00:22:29.963 So I think that helps. 00:22:31.461 --> 00:22:33.795 Yeah, no, that makes a lot of sense. 00:22:33.855 --> 00:22:37.320 I'm trying to think, was there anything else? 00:22:37.682 --> 00:22:41.490 Oh, I think one other thing. 00:22:41.490 --> 00:22:45.826 So what was your proudest moment during the championship? 00:22:46.958 --> 00:22:55.070 yeah, so during the latest, the 2026 Atlanta Championship, so when I was, so I am a very anxious person. 00:22:55.070 --> 00:22:56.611 I panic very easily. 00:22:56.611 --> 00:23:00.232 So for me, the biggest challenge on stage was staying calm. 00:23:00.232 --> 00:23:06.775 I mean, I was sure that my power-buyer skills, I can do it, but for me, like handling the anxiety was a little tough. 00:23:06.775 --> 00:23:10.276 But when I was on stage, when I heard... 00:23:10.541 --> 00:23:49.884 people cheering for me that was incredible like I told you my heart was full I also didn't win the entire like the championship I walked off the stage feeling like a winner because for me it was like I have people who cheer for me and there was this funny moment where in those 20 minutes like I had a carefully planned narrative all of that just flew out of the window when I saw like a sea of people staring at me and something that saved me was I saw that I had my little cheer squad in the front row like

the Power BI days, Washington user groups sitting for me in the first row just by looking at them and then I was back into my zone. 00:23:49.884 --> 00:23:58.930 So I think my proudest moment was to see that people recognize me, they've seen my work, they appreciate me for my efforts. 00:23:58.930 --> 00:24:02.912 That was really humbling, very happy after that. 00:24:03.223 --> 00:24:04.423 That's awesome. 00:24:04.785 --> 00:24:05.285 Cool. 00:24:05.285 --> 00:24:09.387 um So why don't we wrap up with a few questions. 00:24:09.749 --> 00:24:14.852 So what is your favorite or least favorite fabric or Power BI feature? 00:24:15.288 --> 00:24:16.712 Yes, so. 00:24:16.920 --> 00:24:22.240 My favorite thing about Microsoft Fabric is how it seamlessly works with Power BI now. 00:24:22.240 --> 00:24:27.682 Specifically now there are more, like there's an expanded data set connection options. 00:24:27.682 --> 00:24:35.805 And something that I've been recently experimenting with is the translitical task flows, although not, yeah, like just started playing around with it. 00:24:35.805 --> 00:24:42.267 Really like how it's easy for you to write back into Power, write back using Power BI and Fabric. 00:24:42.267 --> 00:24:46.087 And I think that that's something that I've been liking these days. 00:24:46.160 --> 00:24:55.444 And So coming to the challenging aspect right now for me is to keep up with how quickly the features are evolving in fabric. 00:24:55.444 --> 00:25:00.988 So being a totally power BI person getting into fabric, I'm a little overwhelmed. 00:25:00.988 --> 00:25:06.780 And like you say, like seeing people, the MVP is talk about all the fabric features. 00:25:06.780 --> 00:25:09.692 And I'm like, I do not know what this person is talking about. 00:25:09.692 --> 00:25:10.573 I have that. 00:25:10.573 --> 00:25:25.979 I feel that I think almost at least once a day, but then ah I think getting hands-on work with fabric would change my perspective but I'm still hoping for more clarity and consistency. 00:25:26.567 --> 00:25:36.567 Yeah, I, it is very hard, even as a Microsoft MVP to get a sense of where Fabric is going. 00:25:38.528 --> 00:25:46.887 Because like, sometimes I wish I had a crystal ball and I knew what Arun was thinking sometimes. 00:25:46.887 --> 00:25:53.728 Although I got to shake his hand at FabCon, so I felt very special there, because he came by all the booths and that kind of stuff. 00:25:53.728 --> 00:25:54.277 he... 00:25:54.277 --> 00:25:57.468 shook my hand as a tabula editor employee, not as Eugene Weidinger, but that's okay. 00:25:57.468 --> 00:25:58.518 Someday he'll know who I am. 00:25:58.518 --> 00:26:11.790 um No, I I wish I kind of knew the strategy because it's so hard to talk about fabric because it's like you're trying to talk about Home Depot or Lowe's or any home improvement store, right? 00:26:11.790 --> 00:26:24.517 If the goal is that you can build anything that you need and you have all these different

options, it's hard to kind of present a cohesive story and they keep coming out with stuff. 00:26:24.517 --> 00:26:28.289 And it's like, okay, there's a fabric graph database, when do I want to use it? 00:26:28.289 --> 00:26:29.941 don't I don't know. 00:26:30.536 --> 00:26:35.165 I think a lot of people feel the same frustration. 00:26:35.165 --> 00:26:56.436 My honestly, I think it's okay to not keep up with fabric as bad as that sounds, especially if you're, you know, you've got regular work with power bi, I think what I found from my personal experience is The first year or so I tried to learn it. 00:26:56.837 --> 00:27:08.061 I really could not because it was so hard for me to ground the point of it into stuff that I cared about because the whole idea of a lake house, all this data lake stuff, historically has been about big data. 00:27:08.061 --> 00:27:11.303 And when you're working with power be a lot of times it's small data. 00:27:11.303 --> 00:27:14.424 You know, the model size is usually less than a gigabyte. 00:27:14.424 --> 00:27:17.085 You're pulling data from Excel, all that kind of stuff. 00:27:17.326 --> 00:27:20.646 And it wasn't until I had to do some training that includes some fabric stuff. 00:27:20.646 --> 00:27:26.515 And until last year I actually had, you know, my first fabric thing that a lot of this started to click. 00:27:26.515 --> 00:27:34.481 But for anyone out there who's in a similar boat, I would say like, learn about parquet files and the whole Delta Lake kind of thing. 00:27:34.481 --> 00:27:40.607 Understand what a lake house is and have a peripheral awareness of some of these pieces. 00:27:40.607 --> 00:27:46.512 But I think that'll help you the point that you decide to switch, maybe learn a little bit of Python. 00:27:46.752 --> 00:27:55.790 But if you look at the number of fabric items, there's five to eight times as many as there are power BI items in the thing of stuff you can create. 00:27:55.790 --> 00:28:00.310 So I think a lot of people are feeling a similar kind of overwhelmed. 00:28:00.842 --> 00:28:02.377 Right, right, right, right. 00:28:02.377 --> 00:28:07.652 Also, one quick thing I just wanted to add was, so initially, like... 00:28:08.085 --> 00:28:18.380 being an immigrant when I moved to the US, completely new to Power BI, new to Fabric, I believed in this whole like when one door closes another opens kind of vibe. 00:28:18.380 --> 00:28:27.903 And then after moving to the US, becoming an MVP, taking part in all these contests, something that I realized that doors will not open themselves, right? 00:28:27.903 --> 00:28:29.005 You got to push them. 00:28:29.005 --> 00:28:34.728 So if you want to be a part of the community, you have to dip your toes in. 00:28:34.728 --> 00:28:37.989 If you want to learn Fabric, you have to take that first step. 00:28:37.989 --> 00:28:39.260 what matters. 00:28:40.059 --> 00:28:41.770 Yeah, I definitely agree with that. 00:28:41.770 --> 00:28:53.211 And I think fabric especially is something that ah it's like trying to learn how to ride a bike from just reading about in books, you really have to like just work with it because a lot of it's not going to be intuitive otherwise. 00:28:53.211 --> 00:28:58.195 um And, and like you said, there's a lot of different great community spots. 00:28:58.195 --> 00:29:02.138 the forums are full of people that want to help write is full of people that want to help. 00:29:02.138 --> 00:29:15.019 um We just had a whole conference with a bunch of people giving a bunch of presentations, but there's also a lot of smaller ones like, you know, there's the Atlanta SQL Saturday. 00:29:15.019 --> 00:29:17.920 Now it's gonna be called days of data, all that kind of stuff. 00:29:18.559 --> 00:29:24.839 So the last one or two questions is basically, you know, where can people find you? 00:29:24.839 --> 00:29:30.880 I know there's like 12 different social media networks and is there anything you wanna like pitch or promote or anything like that? 00:29:30.991 --> 00:29:33.858 uh Nothing much, people can follow me on LinkedIn. 00:29:33.858 --> 00:29:35.924 That's where I post most of my stuff. 00:29:35.924 --> 00:29:38.978 The speaking events, tips and tips. 00:29:38.978 --> 00:29:43.050 And I do a lot of mini series about Power BI. 00:29:43.050 --> 00:29:51.577 Like I have this thing called 31 days of KPIs in Power BI where I shared 31 different types of KPIs you could do just by using native Power BI visuals. 00:29:51.577 --> 00:29:55.160 And then something that I've been doing recently is Power BI this or that. 00:29:55.160 --> 00:30:02.497 So basically comparing two things like legends or series labels and also doing something called the visual breakdown. 00:30:02.497 --> 00:30:07.131 So I have a KPI in front of me breaking it down why it works, why it does not work. 00:30:07.131 --> 00:30:09.114 So I think LinkedIn is the place. 00:30:09.884 --> 00:30:30.009 Yeah, I do want to compliment you on, some of that because like the, the design for the this or that, and then for some of your, um, squared charts or whatever you, whatever they're called on LinkedIn, you have some basic animations in a way that's not annoying or superfluous, but helps the aesthetic overall, right? 00:30:30.009 --> 00:30:40.307 Like I'm, I'm so tired of people that just add animated like arrow diagrams that don't add any value, because it's an animation, like it ranks higher or something like that. 00:30:40.307 --> 00:30:42.609 But your stuff actually like it pops. 00:30:42.609 --> 00:30:50.695 And so I've sent multiple of your pieces of content to Gabby, my uh marketing assistant to be like, we should, we should do that. 00:30:51.277 --> 00:30:53.057 So very cool. 00:30:53.057 --> 00:30:54.148 Well, thank you for coming on. 00:30:54.148 --> 00:30:55.906 It's been a pleasure to have you Lakshmi. 00:30:55.906 --> 00:30:57.472 Thank you so much, Eugene. 00:30:58.429 --> 00:30:59.250 Okay.