Data Visualization vs. Data Analytics – Ep. 294

In this episode, the team tackles a question that quietly decides whether a Power BI project delivers value: are we analyzing data, or only visualizing it? They break down how “analytics” and “visualization” overlap, why they get muddled in buzzword-heavy conversations, and how to think about the workflow from raw data → insight → communication.

News & Announcements

• FabCon Community Conference (Microsoft Fabric Conference) — The team calls out the March 26–28 conference (with workshop days) and mentions discount code Carlo100.
• Submit an idea or topic for the podcast — Have a question you want the crew to debate? Send it in.
• PowerBI.tips Podcast — Browse the full back-catalog and listen on your platform of choice.
• Power BI Theme Generator (Tips+) — Build theme JSON to standardize colors, fonts, and styling across reports.

Main Discussion

A useful mental model from this episode: analytics creates meaning (turning data into insights you can act on), while visualization communicates meaning (so the right audience can understand it quickly). Power BI is powerful because it can do both—but it helps to be explicit about what you’re building and who it’s for.

• Analytics doesn’t require visuals: it’s the work of aggregating, calculating, and interrogating data to answer questions (often starting in tables/pivots before any chart exists).
• Visualization is a language: color, position, and shape are communication tools to highlight comparisons, distributions, and patterns.
• ‘What/when’ vs. ‘why/how’ is a real split: many reports are designed for broad consumption (status and trends), while deeper analysis is narrower and more exploratory.
• Power BI is the ‘repeatable analytics’ layer: ad-hoc exploration can start in Excel, but scale, refresh, and governance needs quickly push you toward semantic models and DAX.
• Simple visuals can hide complex work: a basic bar chart might represent weeks of modeling, metric definition, and data engineering—don’t confuse the output with the effort.
• Shared metric definitions prevent rework: if the business can’t agree on what a number means, no amount of visual polish will fix the project.
• Better visuals are a learned skill: invest in training, examples, and practice so teams get better at focusing attention on what matters.

Looking Forward

Start your next report by writing the question and metric definition, do a quick table-based analysis to confirm the logic, and then choose the simplest visual that communicates the answer to the intended audience.

Episode Transcript

0:27 good morning everyone and welcome back to the explicit measures podcast with Tommy Tommy Seth and Mike hello and welcome back good morning good morning good morning glad to be here gentlemen glad to be here here is that a Fanta no it’s actually a polar it’s like a sheltered water it’s a PO so just just some sparkling water okay after I’ve gotten back from Europe i’ I’ve absorbed some new habits it’s scarfs and sparkling water now I like my things it’s my jam have a bagette with you yeah

0:59 it’s my jam have a bagette with you yeah h next week I’ll have a mustache with some curly CU on the side of it with with a with a what a a beret B betet yeah I don’t know if it’ll go very well with my I will I will admit the the headphone things that I like to wear Seth and I Seth has no problem the hair doesn’t really get messed up by the headphones Tommy wears inner Earp pods so his hair was always stylish and looking good that’s why I do the airpods but I literally could care less about my hair and I have so little that I should

1:30 hair and I have so little that I should just probably go bald anyways but do it my I put my headphones on and the headphones push back a little bit of the hair and I’ll come up from the basement after I’ve been working for a while and everyone just starts laughing at me like your hair it’s crazy cuz the headphones like push the hair back into like a little like raised area so halfway through my head I have like a divot and then there’s like a little raised it’s like this really weird like it’s definitely headphone hair so I don’t know if there’s a thing yet but it should there should be a thing for headphone hair do you remember what haircuts are like what do you

2:00 haircuts are like what do you mean by mean by that Seth doesn’t remember I’m getting a haircut tomorrow and I’m so excited for it it’s just so needed on the sides but like man is that a thing for you still or I don’t know we should do we should do a bet here for either either someone has to grw out their beard all the way or someone’s got to shave all their hair off or both or both I’m telling you Mike Mike there there’s there are subreddits there are there there are places for like

2:30 like people poting pictures should I go bald should I go I know do it man just do it and grow out that beard you got oh man I don’t know Majestic the community loved that Majestic beard Mike well maybe maybe we’ll bring it back take a hit you maybe we’ll bring it back take a hit well see wife’s not a big fan know well see wife’s not a big fan there’s this thing called a wife and she does not like the tickly beard so much so I know I know but is what it is wow bro you you bald with that with that man beard there I get it’s funny cuz I I

3:00 beard there I get it’s funny cuz I I grow out the beard and I get lots of compliments I love the beard she’s like who’s complimenting you I’m like every other man that I met met everyone Mike you look good with a beard oh look looks good with a beard all right yeah it hides my double chin I know I know it does yes turn the corner man when I grow the beard I just get checked more often at the the airport Tommy you just look Shady in general so adding the beard adds more shade to you Italian yeah that’s the

3:31 shade to you Italian yeah that’s the Italian so real quick I got a couple announcements here and we’ll jump into our main topic so one of our introductions here is the Microsoft fabric conference is coming up on March 26th through the 28th there is pre-con workshops on the 24th 25th and a postcon workshop on the 29th if you want $100 off your coupon or your tickets go use Carlo 100 to get $100 off your tickets so we hope you enjoy the conference hopefull we’ll see you there and then Tommy you’ve got a main topic here I think Tommy’s got a beef going on here

4:02 think Tommy’s got a beef going on here with some new AI Tommy you want to give us the other news item today you give us the other news item today I I sing the Praises of AI chat GPT know I I sing the Praises of AI chat GPT llama all these things and we were all so excited for co-pilot and I don’t want to say this I hate to say this but I’m not really jazzed I’m not digging co-pilot yet I’m actually pretty underwhelmed with a lot of the features in the abilities so far I’ll give an

4:32 in the abilities so far I’ll give an example there obviously it’s in every application now and one of them would be like PowerPoint right and it’s like okay well maybe I write a little transcript for this slide doesn’t understand what that means it’s incredibly limited and the scope of what I can do in each product is right now for very very specific specific capabilities and not really allowing you if I want to say hey I want to take a look at this does this look good does it understand what that means saying I don’t understand your prompt please ask

5:02 don’t understand your prompt please ask something that I know if I’m trying to summarize my email in co-pilot and teams I was like hey what’s going on what’s my new emails it gave me three examples of junk email that is not relevant not taking anything from certain folders or from a calendar that I had to do a meeting invite and it’s like this is there’s a lot of things I’m finding that are useless and not what I was expecting it to be I wasn’t expecting do everything for me but my ability to interact with each

5:34 ability to interact with each application especially PowerPoint it’s just feeling like it’s very limited limited scope right now and I’m I’m a little disappointed sad about sad about that I will say this I think I’m getting confused on what’s co-pilot and what’s not not co-pilot and the reason I’m saying this is is because the The Branding of things that are AI are called co-pilots so for example i’ I’ve been recently my family knows I’m recently obsessed with

6:05 family knows I’m recently obsessed with Chuck Norse jokes so I keep asking co-pilot give me random new Chuck Norris jokes now I think I’ve hit a point in time where I keep getting the same jokes over and over again that’s just not really generating anything new but if I ask that into like the co-pilot app versus like the co-pilot window on the side of Windows Explorer versus if I ask it some other like sometimes get like we don’t like to make jokes that we’re an AI to help assist you like I’m like oh now do you like okay sassy AI like just

6:38 now do you like okay sassy AI like just tell me the joke already so like I’m I’m so in that respect like I feel like I’m I feel like there’s a lot of different things that are AI but they’re all different flavors like for example you go over to Microsoft designer and you can get Microsoft designer to generate images off of some text awesome I use that feature a lot but but if I go over to the co-pilot inside like the browser it won’t do it and it says like I’ll make you an image and it just gets stuck halfway through and you’re like are you thinking is it going to

7:08 like are you thinking is it going to get completed I don’t know and then there’s co-pilot in like teams and that seems to be yet another slightly different experience and so I have a hard time understanding right now in each program what should co-pilot be doing and I feel like Tommy this is this is where I think this is what we haven’t gotten dialed in yet there needs to be like something called prompt master so they have this co-pilot Labs yes I saw that yeah but you can’t create

7:38 yes I saw that yeah but you can’t create your own you can only save prompts that have already Microsoft’s already created bogus like that’s not that’s not what we want here I want to make I want to be able to have my library of prompts but I need to know like what prompts work well in word what prompts work well in like I do like the Outlook thing Outlook has done a couple times where I’ve had to summarize this email and it reads through an email thread and gives me some summary points it’s getting better it definitely does I will say this the co-pilot that’s running on top of videos and transcripts that are inside meetings

8:09 and transcripts that are inside meetings that’s working pretty good that’s cool but that’s been out like it’s not the generative side of chat TP generative language because again it’s more like AI things that have already been available in like PowerPoint such as the designer for example the prompts that are available to me add an image okay like or organize my slides I’m like I’ve never really wanted that like that’s never I’ve never had that like oh I wish I had an AI to organize the slides and my slides are so disorganized I don’t

8:39 my slides are so disorganized I don’t understand it at all I’ve done this step by step here already and when I and I’ve tried each of these and each time like oh no no no no like that’s horrendous or it’s you basically can hear in the background like I am a robot and for like the some of the drafts so co-pilot should and I’m not saying it should be exactly like chat gbt or those other tooling but I feel like they using a different system on the back end and that was not the expectation in terms of being able to customize but even what

9:10 being able to customize but even what would you be trying to do in each tool and I think that’s the problem I have with all technology is whenever I’m going to buy a tool or use something powerbi like really what are you trying to do and I think that’s why I’ve latched on to powerbi co-pilot right now I think it’s still a very beta version version I I have two different thoughts one is as you guys are talking Mike I think yours is resonating well with me as far as the confusion part right like yeah

9:41 as the confusion part right like yeah calling using calling everything co-pilot at least from an end user perspective assumes that co-pilot depending on what I’m paying for yeah I’m enabling other features of co-pilot so that thing should work or behave similar Lally wherever I am yes and that’s just not the case Right Tires on all the things but it’s just not the case so is it the same Technologies and people are and the different teams are leveraging it differently and they have

10:11 leveraging it differently and they have different prompts and like yes it’s disconnected it’s DET jointed I I’m I’m guessing that eventually it’s supposed to tie in together I I don’t know or it’s going to remain like one of these not so great marketing pushes where you get a co-pilot and you get a co-pilot and you get a co-pilot but what we’re talking about is co-pilot for Microsoft 365 or co-pilot for sales or co-pilot for service or like yeah okay like can we now we’re we can’t really

10:42 like can we now we’re we can’t really use acronyms because cop sales would be the same as co-pilot for service so it’s Coos something something something something so I I I feel you there on on the positive side unlike Tommy a lot of my job lately is turning into like communication it’s Communication in organization and as you consolidate and summarize thoughts PowerPoint is that

11:13 summarize thoughts PowerPoint is that thing however I’m a bullet list guy right like I I very typ well very typically structure out what my agenda is going to be my how I want to articulate something whatever whatever so I have a framework

11:32 whatever whatever so I have a framework to go build my slides MH in my testing and in so what what I’ve done is take full full documents in like word docs that have accompanied presentations before now mind you I would use an llm to give me a framework fill out and and basically write the full document yeah and then go spend all the time to generate the PowerPoint slides it’s very timec

12:04 PowerPoint slides it’s very timec consuming all of that is but like the llms help with at least at least you and not using copilot but I also tested that in word but like I have a framework boom now I have to go present create a presentation and it’s very long verbose I have to create all the stuff so in my tests of taking like that full document that was very well structured and going into PowerPoint and saying here’s my here’s my word doc create a

12:36 here’s my here’s my word doc create a presentation it did a hell of a job was it perfect no but when I looked at it I was like oh my God you just saved me hours hours of my time just framing out these things in like a structured way that I can fill out embellish tweak I didn’t have any like I had some issues initially trying to get a visualization because I wasn’t using the right prompt but afterwards I didn’t

13:08 right prompt but afterwards I didn’t have a problem if I was like Hey throw a visual in here that makes sense with you visual in here that makes sense with what the context of this is and know what the context of this is and every single one was different and great so all these things are are huge Time Savers as it relates to taking written word and just dumping it into a PowerPoint that gives me a structure that I can work with the other thing I did test that it let me finish Tommy you want to whatso I had a cough the other thing the other thing I like that I did test was taking the master templates

13:39 test was taking the master templates right and there’s a there’s a like a process the thing I didn’t like about it was it automatically started overwriting my master template file as opposed to just assuming that I’m Gonna Save that off right so there’s a disconnect there yeah because I have to save it save as and then remove all the slides out of my master like that thing but it’s still used used all of the theme it used my master template and I like would require some tweaks as far as like what fonts or sub type of things

14:09 as like what fonts or sub type of things it used but it’s the content of creating all that all that that like I said ours alone just made made it worth it right from an implementation and creation standpoint so going from that word doc to PowerPoint huge huge I I think is one of the best features I’m going to get a lot of use out of and then secondarily one that I haven’t explored like really deeply was but in the tests I’ve I’ve

14:41 deeply was but in the tests I’ve I’ve had so far been pretty impressed with same type of thing right like I I need a framework for building a a proposal I need a framework for a business case I need a framework for a job role all these things like in word doc just like boom give me the structure and I can fill it out fill it in whatever the case may be so when I think about and we’ve talked about this a lot before when I think about Ai and the places that it

15:12 think about Ai and the places that it can like easily plug in it’s the mundane stuff that kills me and these are mundane tasks they’re like I need to communicate something I’ve got to put the these slides together I’ve got you the these slides together I’ve got framework I’ve got to write out all know framework I’ve got to write out all these this stuff if you’re hours or days out of my a day out of my time every single time I have to do this like you’re you’re winning and so far I’m it’s it is it is in a place

15:42 far I’m it’s it is it is in a place where I’m already getting value so I would say like from that perspective I think in those cases whoever built those functionalities it’s good I think that’s a important distinction too because I think Microsoft’s assuming everyone who’s using co-pilot doesn’t know what an llm is an llm is and right and I think I for me I’m like I just asked show me some key slides my next thought because I’m used to this and other models is why did you choose those slides because I want to say like why are those important doesn’t

16:13 why are those important doesn’t understand that but to your point set like those mundane tasks it’s simply building on that it’s not everything else so to speak it’s and that’s a really good point in distinction right what what we’re describing are two different things is it helping you build something from nothing where other tools are you’re saying not really pretty pretty much falling over its face is it can it easily take thing like recommend structure take that and

16:45 like recommend structure take that and then do something with it and I found yes it can do that yeah so so yeah two different use cases for sure yeah but I I get what you’re saying like it is pretty snazzy when you go into other some of the other tools and it’s just a matter of how you refine a prompt that produces some pretty amazing outputs you’re picking up what I’m putting down all right yeah yeah sure I think I’m with you on this one a little bit as well because it’s it’s more around I see what other tools are doing and now there’s a comparison that’s being made

17:16 there’s a comparison that’s being made whether you like it or not it’s it’s there like it’s I can see like the ease of useing some of these other tools so there’s there’s more of a a need for Microsoft to like okay you’re you’re going to play ball with the big guys yeah the companies that are making this you got to you got to play ball like it’s it’s time to step up so I I think but we’re also seeing the very first round of what this is looking like initially day one so I I have to imagine they’re going to continue all these teams are going to continue improving this one I I also feel like there’s another momentum thing here too as well around like Microsoft made co-pilot and

17:49 around like Microsoft made co-pilot and there’s AI is huge like it’s the buzz word right now so I have to imagine there’s some layer of like pushing from leadership down into these teams to make sure like every team needs to have a co-pilot somewhere in the program and some of it will be dialed and some of it won’t be like some of it will be like really refined and some of it won’t because it depends on like it maybe some teams are throwing a lot of people at maybe some teams are only throwing a couple people or one person like that’s their whole job is just to get some kind their whole job is just to get some co-pilot thing working so there may of co-pilot thing working so there may be some limitations there that we’re not

18:19 be some limitations there that we’re not quite seeing from the outset and maybe what we’re seeing is that not unified experience something you brought up in your comment earlier Seth that I thought was really relevant here was now that everything is branded with co-pilot everywhere across the entire ecosystem I feel like there’s now this expectation that it is knowledgeable of all the other conversations I’m having across all the co-pilots and I and I and I think this is another thing that’s a disconnect here right it doesn’t have context to like if I’m

18:49 doesn’t have context to like if I’m talking to it in teams or if I’m talking to it in word or I’m talking to it in Outlook I’m not sure it’s getting the context of those other conversations and there may be some need there like I really wanted to know like what was going on in these other areas or not not some need I think this this is this drives to the point that it better yeah at least in my if you’re G to take over the ecosystem of AI in your tool sets and not have third-party services which are very easy to plug in

19:20 services which are very easy to plug in in your Azure ecosystem right yep take take the stance like we’re already pointing out you are you you are being compared to those Services yes right and the differentiator and hopefully like I said this isn’t an area I know a lot about hopefully it is like as as it relates to Microsoft’s implementation right but if you want to talk about like building something that’s going to lock in your customers that they’re way willing to pay for it is this type of

19:50 willing to pay for it is this type of stuff that Tommy’s talking about that helps generate content but also to your point that works across the ecosystem so it’s not not a matter of like co- does co-pilot understand you in CRM or teams or wherever yes of course it’s contextually aware the only thing it’s not going to do or the only reason it wouldn’t be is if you’re not paying for that other service right so it’s it’s a feature enablement as opposed to where we’re at right now which is just what

20:20 we’re at right now which is just what seems like a very disjointed experience in each one of these tools as it get gets rolled out yeah but yeah I gets rolled out yeah but yeah % to your point if if organization mean % to your point if if organization I I would I I would say I would be shocked if organizations aren’t aren’t heavy pushing right like AI to be implemented in some way shape or form in their their organization 100% which is interesting right like as I say that because if we’ve we’ve talked

20:51 say that because if we’ve we’ve talked about like right away when AI was coming out there’s the hype cycle right like whatever trains there are right there’s this giant push the trough of disillusionment and then like normally like a whole bunch of organizations like roll on years later a AI is like not that it seems to me at least in my circles that everybody’s jumping on this bandwagon it’s like and and that is very indicative I think of just how

21:22 just how transformational this this one is compared to the other Technologies we’ve seen seen that that have been like disruptive or hey if you don’t do this thing whatever like AI is crazy man right so it is it is nuts man it’ll be fun it’s it’s gonna be a fun ride wherever it takes us I think think so yeah so this that’s my impression so far see where see where it takes us so anyways I I I I like what Copa is doing

21:53 anyways I I I I like what Copa is doing I think set to your point if you can make it saave off hours of my time I will use it more if it can tell me funny jokes about Chuck Norris I will use it more if it can one thing I will say that it does very well all of our thumbnails a lot of things that we do in the podcast have been generated by AI based things so image creation things that are interesting to look at that are visually stimul it’s getting that down pretty good right now and there’s a lot of good AIS out there that are doing good jobs with that so I like the Adobe one that I’m using now for that one there’s Leonardo there’s other

22:25 there’s Leonardo there’s other ones out there as well but I think some of that creative side of things it’s just good to have a starting point and to your point set like I think we’re going to get to a point where we can just start ripping out bullet points or an outline and say from this outline makes six slides and then it can get started and then I can just spend a little bit time cleaning it up and call it done because honestly I think honestly I think it’s a waste of time to make it look pretty like someone else should just figure that out and just just happen it just just had designer then that’s already a great feature I’m I’m not going to spend a lot of time on it honestly I’m going to focus I want to focus my time on like thinking about the

22:56 focus my time on like thinking about the bullet points the the thoughts the training like the steps through the procedure I want something else to take

23:01 procedure I want something else to take care of the rest of the other pieces for me so we’ll see how that goes anyways really good topic there around the co-pilot things so Tommy let’s jump into our main topic for today oh yeah oh yeah so AI well we top snap to a slim gy so no article today but that’s fine this is all in our brains guys this is all in our mind it is oh boy I think

23:31 all in our mind it is oh boy I think this comes from a place because again the buzzwords that I always hear buzzwords are man they’re they’re really bugging me they’re killing me how many buzzwords are out out there we’re hearing a lot data analytics actual insights and data visualization and I keep looking at powerbi and I’ve been doing a ton of dashboard in days lately okay and building those out and just showcasing the advanced slides I’ve been doing a few a few pl300 exam trainings as well and I’m going through the slides and I’m teaching the people

24:01 the slides and I’m teaching the people this and I’m going through the visual side of it and the content talking about the the analytics and I’m having this core question around what is the real difference between our normal powerbi report that really is generally basic visualizations we’re going to have a bar chart line chart maybe the drill through feature and really true data analytics within powerbi and we’re not talking data science here we’re not talking

24:31 data science here we’re not talking machine learning or cognitive training we’re simply talking the realm of pure analytics back in the day what you might have done at Excel and I think like how do we actually make sure that we’re we’re providing through a simplified core user interface that is powerbi analytics to the users while at the same time we’re not sacrificing any of their from visuals because yeah not every visual is analytics and I think that’s really the core of my question there or the hot

25:04 take there’s a lot of there’s a lot to unpack there so let’s maybe distill this down to like one let’s start talking the topics here so I think starting off here at the beginning let’s let’s maybe kind at the beginning let’s let’s maybe sit on data visualization and then of sit on data visualization and then maybe data analysis right let’s maybe I I think I have some thoughts around that so my initial thought here is what what is the main key difference between data visualization and data analysis I think data analysis doesn’t necessarily have to render itself into a visual I think if you think about the data analysis you’re trying to do if

25:35 data analysis you’re trying to do if you’re trying to some Drive something to action a language you can speak to somebody with is the visuals that you represent so visuals are a language a a method of communicating to someone else comparisons distributions those kinds of patterns and you’re conveying through images a message right color highlights these things are red these things are blue red things maybe demand more attention for me to look at them because they are highlighting something

26:05 because they are highlighting something that I want you to point your attention to so when I when I think about data visualizations I’m thinking this is more of a graphical language of how we communicate data but then when I move over to data analysis data analysis feels a lot more like running through numbers and statistics and producing tables of data or doing analysis of again I use the like the example of let’s just imagine I have a 100 million row fact table no one person can go

26:35 row fact table no one person can go through 100 million rows and figure out which rows of that table are important to them what you have to do is you have to aggregate you have to roll up you have to figure out where are the sales down for my region where is where can I where are we underperforming based on prior years so that to me is going through the data and analyzing it to produce and I’m going to call call this for a lack of better term the insights the insights that are this year we were the kpi I’m trying to go for is this year’s sales versus last year sales

27:06 this year’s sales versus last year sales by region that’s a key metric that we care about and we want to identify the regions that are substantially below where they should be or where we project them to be so those things to me that is data analysis data analysis can be represented as a visual but doesn’t have to be it could be in other forms too so that’s I just wanted to maybe like cover off on that first part of how I view that is your view different Seth around data visualization versus data analysis or where they would differ or how they are similar no I I

27:37 how they are similar no I I think just drawing on the raw definitions of what these things are align with your explanation right data analytics is the taking raw data and creating meaning behind it right so we we do that in many different tools I think we talk about the Technologies a lot right like the different parts and pieces of ingesting data and transforming it flattening it putting it in a position where we can start to infer right things that we know about

28:10 infer right things that we know about the business on top of the data and drive towards to your point insights y we’ve been doing this for a long time Excel is a great place to do that because it allows you to even prior to powerbi connect multiple different data sources merge like throw things together Ram it together in power power pivots Etc but there are limitations like you instantly will hit a point at some point in time where either you’re going to have to start

28:40 either you’re going to have to start coding in Excel or you want a you want better summaries you want to start creating additional calculations on top of stuff and I think that’s where the to me the tradeoff moves into more powerbi Centric Solutions where we’re still doing that analysis except it’s just ad hoc I’m just throwing some stuff together where data visualization enters into the picture is now that we have meaning behind that

29:13 is now that we have meaning behind that data there are many different ways we can tell that story or we need to to engage with a certain audience and show them or give them the best rep presentations of that in visual form that will help them digest it as quickly as possible and that’s the whole area of data visualization and there are some fantastic people we’ve talked about on the podcast before that have spent their careers diving into the

29:45 have spent their careers diving into the reasons why it’s worthwhile to spend time and understanding hey there are some really good practices you can use to create visual how like representations of meaningful data to people and ultimately it’s to drive and make sure that they’re easily digesting digesting it where the conversation I think es and flows in different directions is is you flows in different directions is is how complex like what are what are know how complex like what are what are what are the different types of

30:15 what are the different types of reporting needs that people have what should we be doing with powerbi and the data in in the platforms for the audiences etc etc but like on in a nutshell that one is about taking just raw data that we collect and making making it useful for the business and then the other is how we best communicate out the business so people don’t have to re like do the same analysis over and over and over again

30:45 analysis over and over and over again we’re sharing we’re sharing that with other people and we’re also simplifying a lot of the complexity by building the underlying complexity into simple form for fit for purpose kind form for fit for purpose reporting and I think we all agree of reporting and I think we all agree because really there we’re defining there are two lanes here that come with both their pros and cons or with their perks whereas the data viz is more the what and the when it’s a little more Leisure it’s more collaborative and it’s

31:16 Leisure it’s more collaborative and it’s probably more sharable your data analytics is that why and the how but it’s more confined and more strict to me because again you are like you said you’re trying to answer usually specific question question whether it be through raw data it requires the user to have a a common knowledge of what those numbers are trying to convey whereas from the data visual side that’s probably your kpi we want to see the trend you’re just simply communicating what the numbers are not trying to tell why

31:46 the numbers are not trying to tell why you are what you are at because data Vis has a probably more broader audience so to me I see that there’s two very distinct Lanes between them there’s some overlap but clearly based on what we’re saying here that we’re we’re almost I don’t say dealing with different tooling but the way we’re communicating this and the interface itself is going to be different what missing the two lanes sure what are the distinction you’re making between the two and why they’re so different so I’m saying data

32:18 they’re so different so I’m saying data Vis is the the what and the when what’s going on when did it happen some simple trending the data analytics is the why and the how of Any Given number I don’t see that as much in the data Vis side of it because that’s a lot more exploratory that’s a lot more into the details the widgets if we change this by a certain rate what would occur compared to a common Trend like where is our Trend or are we meeting a goal I

32:48 our Trend or are we meeting a goal I don’t think I would have I don’t think I would have made that initial analogy but I think I think parts of that stick I wouldn’t I wouldn’t 100% say like 100% the time it’s always those two ways but I feel like that’s pretty good generalization of like sometimes the data analysis provides more of the reasoning behind why the numbers are showing something and and again I think if you’re looking at a single visual you’re probably not going to get the whole story out of a single

33:18 to get the whole story out of a single visual right so I feel like what you’re saying is like the data analysis is potentially like is like a super set of like data visual ization so data analysis would incorporate multiple visuals Pages tables like it’s more encompassing that is really aiming to drill towards a specific outcome or action or do some analysis yeah there’s a big difference between what is our cost per click and how can we improve our cost

33:48 click and how can we improve our cost per click thinking I can see the thinking faces on the think the thinking fa is occurring it’s not it’s not I’m just trying like I wouldn’t I necessarily wouldn’t describe it as two lanes because Lanes to me are separations that don’t ever cross over and to me it’s more of an evolution of of the progress by which we typically make or the stages of how we interact with data right like

34:18 of how we interact with data right like data is all over the place we try to bring it together we start to apply business rules to make sure that it’s fit for purpose and it matches the rest of the applications right great now we have the framework by which we can start

34:30 have the framework by which we can start to analyze to your point Tommy it’s like like the why and how like what is happening like we need to look at the some information that’s going to drive some decision making and I think that’s where I agree with you the discovery the insights that we’re pulling together initially from the raw data I think produce the quick wins quick answers and it will consistently do that where I

35:00 it will consistently do that where I think it think it evolves more into what we’re what we’re terming is visualization but I would also throw into the data visualization part of that a lot of the modeling and Dax portions because those are those are specific activities we’re taking on to produce outputs in visualizations right much much of the time or aggregating data in ways that we can work with it

35:32 data in ways that we can work with it better faster right and that’s where I think we we move out of the quicker conversations but it’s like I have this to your point what what was the example you just used I per click I have click how do we make it better right what is our cost per click well moving on to how do we make it better in May involve multiple different other inputs us to analyze across the

36:03 other inputs us to analyze across the Spectrum us to create a whole bunch of calculated things that are going to lead us to a direction like and ultimately this is where it drives into like what questions are we trying to answer and I think that’s where the visualization part of this becomes much more refined in conversation and or what we want those outputs to look like because they’re going to be reoccurring like we’re going to come back to this all the

36:33 we’re going to come back to this all the time because as the data changes underneath these visualizations help us understand what is changing as opposed to data and analytics is like to me it’s like it’s the first foras that lead to more refined conversations and in ways we want to look at things but they also take more time to develop right and I guess that’s to to me it’s just this Evolution and natural progression of how these two areas work together well and how I I view them as opposed to

37:04 how I I view them as opposed to two separate things what you just said I think is the key for me Seth I’m having this aha moment because I think I was looking at this the wrong way because the measurements itself is truly the heart and soul of what makes something analytical or just something pure honestly data VI this may be more of a hot take saying but in general I would agree on this more than not it would almost be impossible to do data Linux off base me measures or metrics if I

37:35 off base me measures or metrics if I have total sales no matter what features available in powerbi it’s really hard just off of that to do in a sense that genuine analytics everything’s going to be more communication no matter what your dimensions are whereas again change that up say what is our what is our expected sales what is our again some Ratio or something off of that base measure that’s when all of a sudden the

38:05 that’s when all of a sudden the analytics kicks into gear I guess I’m I’m slightly confused in in how so let’s say you had a power sure let’s say a powerbi report there’s two measures sales and cost that’s all you have now you have to build an analytical report you have whatever your why do you keep saying analytical report you’re you’re building this for someone to make ingrained or integrated

38:35 someone to make ingrained or integrated decision so they’re not just going to be high level show me my sales over the last 12 months but where can we get better better sales yeah but iess I feel like you’re being really picky about like what your your your scenario here is I feel like I’ll broaden I’ll Broad in I’m just saying like I feel like some some companies are like okay I just want to see my I want to see my sales like I think I think there’s value in saying just show me my sales over time and then I’m going to set a goal of 10 million in sales and I’m going to see

39:06 million in sales and I’m going to see how close I get to that number by the end of the year like that that could be like this that could be like the simplest part of the KP that we’re talking about but what what you’re talking about Tommy is like you’re talking about like deeper integrated more layered versions of like okay I’m selling 10 products which one should I focus most of my attention on which one which are we which one could we have the most Prof from like those are other questions that I think are all still just general data analytics but can be represented as visuals so I don’t I don’t really see the distinction like so separately I just see it as part

39:37 so separately I just see it as part of like the conversation around okay it’s it’s it’s more about what is your end goal what is your desire at the end of the game like what is that action you want to take away from and and we’ll agree to disagree here because I I’m I’m going to stand on the point that yeah you’re 12 month and show me the Target is that really data analytics again I’ll put that on the parking lot but I how it not it might be it might be simple in nature but it’s data analytics even if it’s it’s simple I don’t think you can argue with that I think to me that’s more just data

40:09 that I think to me that’s more just data visualization that’s just the numbers on the board I I think I think this is cyclical to me right when I say Evolution like the the simple case I I laid out is I have raw data I make meaningful insights using whatever tooling right I just I I can do pivots I can summarize I can do aggregations but there’s a level at which that becomes harder and I’m going to choose a tool like powerbi to add to your point the other metrics I want because I’m I’m

40:40 other metrics I want because I’m I’m being led in an area that it requires more work and I think that’s where data visualization comes in because the more work that’s being done you’re trying to summarize and produce those outputs in a way that’s cohesive to yourself or an end user but I that’s like that’s one scenario the other is you’ve already done that now we want to go even deeper right and that is I think

41:11 go even deeper right and that is I think where you may not know the the output of those questions but you have deemed it necessary to do the like want to get to the next levels of insight where you’re still going through the same process of well maybe as I’m as I’m talking through this like you’re still driving but now it becomes I think more more refined because you don’t know what the outputs are going to be but we’re very familiar with the Insight so are you are you getting value out of the end product I

41:44 getting value out of the end product I think that is that starts to become very dependent on the types of visualizations that you choose and how you produce the outputs outputs because typically there’s a lot more going on that needs to be as simplified as possible in a visual format yeah and I’m not arguing that you should only have analytics I’ll simplify the analogy here me looking up the score of the Super Bowl is data visualization that’s not data analytics it’s simply numbers

42:14 not data analytics it’s simply numbers in a table looking at me the points per quarter that’s just data viz my friend there’s no analytics there and I like what you said Seth because you’re right I think there’s that evolution and I’m not advocating to not have data Vis that you can only have data analytics my case I’m trying to make is I think there needs to be an important Distinction on just outputting in numbers to Showcase like a box score in baseball which is not analytics that’s just the numbers which sometimes to me

42:45 just the numbers which sometimes to me is no different from sales by month which is simply the number that’s our scorecard I think I see your point yeah I think I get I get your point I think I think you have to consider there’s like this analytics maturity curve that goes along with this right so part of what you’re talking about is you part of what you’re talking about is the basic level of this is just know the basic level of this is just looking historically what did I just see in the rearview mirror that’s that’s one level of analytics but that’s a very base level yeah it’s your RBI it’s your

43:17 base level yeah it’s your RBI it’s your home runs right whatever that number is that’s a factual roll up of that number and I can roll it up by like different groupings like how much we pay by salary or I can roll by what year they were born or what’s what you were born or what’s what team they’re from right that’s just know team they’re from right that’s just to me it’s still analytics it’s just very basic but I think when you start combining those metrics together and you start looking for Trends and patterns and like connecting the things and then you start incorporating things like statistics and doing a lot of other things on top of that we’re

43:48 things on top of that we’re more likely to get home runs or hits when we bat a certain way or if we train a certain way like so I think what you’re speaking to is is further up that maturity curve you start going from I’m not going to look historically which again is very basic we start thinking about what should we do what would be the prediction if we take a certain action and I think ultimately we want to get every organization into like the prescriptive like what should I do right that’s where the analytics tell us what is the next step again I’m thinking Marketing sales things Tommy because

44:19 Marketing sales things Tommy because like you do this a lot right if I can spend $100 on LinkedIn YouTube or Twitter for advertising and one of those platforms produce more engagement that we Define as what we want or more sales well you’re going to likely continue to invest more in that platform because it’s driving the outcome that you want right if we can predict that with our data then we we know if we do these actions spend this level of money on marketing we’ll get this return on our

44:50 marketing we’ll get this return on our investment and I agree completely and I think what bothers me and I think what fires me up here is because we do all the basic people think bi stands for basic intelligence not business intelligence here and what else we’re capable of doing or what the tooling is capable of doing what we should be asking yeah I like I like where you went with some of this because I think I would still call it the same family right but some it’s like a family

45:20 right but some it’s like a family there’s there’s going to be kids that are younger in age and there’s going to be like adults that are more mature in age and like you can look at like you age and like you can look at like how the analytics play out in know how the analytics play out in companies and some companies are going to be very young in their analytical culture other companies might have a bit more mature analytical culture they’re where they’re focusing more on statistics repeatable results but I think a lot of this you have you can’t get to those higher levels of analytics maturity without covering those basic platforms first you can’t you can’t get Beyond historical reporting unless you

45:50 Beyond historical reporting unless you have it first you have to have some good historical reporting first before you can start doing predictive and suggest in what what you should do with your business so how do to your point Seth or

46:00 business so how do to your point Seth or to your reference how do we then evolve do the basic visual elements in powerbi serve the needs already from both Visual and analytical if I just see bar charts and I’m simplifying everything in a good way again and still absolutely important how is that next step then taken if I just see a bar chart I can click on it I can see trending how do we get the organiz ation or the teams where to ask other questions or to provide the really that

46:31 questions or to provide the really that more analytical deep Dives I okay so let me let me try to answer your your question question the if data an analytics is supposed to be driving meaning out of data visual data visualization is choosing a different type of VIs ual to aggregate data together to communicate that effectively much more so than a table of

47:01 effectively much more so than a table of information or more so than what I can get out of a pivot table because it requires more work but I’m I’m still producing that insight as as easy as possible I I think the principles stay the same even though the conversations get harder it what what by that is like we can get into very hairy places with a lot of statistical analysis we can do a

47:32 lot of statistical analysis we can do a lot of crazy things with calculations and God knows what going on in a model the complexity is how do you convey that to the end user in a way that they can easily digest it and I think that’s where the elevation of this conversation gets harder but we’re doing the same thing that we would be doing in the easy scenarios data visualization and the reason we use visuals is because it’s easier to consume the information and then get the insights

48:03 information and then get the insights from it so like I’m I’m I’m hearing what’s being said yeah kind I’m kind I’m following but it’s the visualization part is absolutely important it just so happens that a lot of the visuals we use that are part of people’s lexicons are because we Group by something it’s because we use a trend over time and that’s a line chart right the grouping is a bar chart whether it’s horizontal

48:33 is a bar chart whether it’s horizontal or vertical like all of these things in very like simple terms allow us to see things up and down right whether it’s by a group whether it’s over time like and a lot of the questions that we have about our business are either current state give me red or green a and or let me see how something is moving over time so do we need to move into the 500 other types of visualization well

49:03 500 other types of visualization well obviously not yeah does that mean that because we’re producing something that lets an audience easily digest the information that it was easy for us to create it no and I think that’s the fallacy is like just because you see a bar chart doesn’t mean it didn’t take somebody a month to generate the data required for us to show you that simple bar chart right like if Mike runs

49:33 bar chart right like if Mike runs everything through six statistical models and the output is that bar chart yeah just because it’s a bar chart doesn’t mean that it was easy to put that information together if it’s easy for you to consume it and make a decision off of it then it’s doing what it it should but that’s the hard part just like like what is there’s there’s an analogy and and tons of stuff in here right like it’s the guy with a hammer that knows where to click that’s why you pay him all the money right because he’s

50:04 pay him all the money right because he’s been doing it for 40 years and what he can produce for you is the expected output that you want just because it looks simple doesn’t mean that it is and I think I I don’t know if that’s a mix welcome to every Excel file I’ve ever looked at it looks simple but it isn’t really right a mix in here of like some of we talking about I’ve added like 100 macros and a million a million named cell references and all these you named cell references and all these complex formulas you’re like holy know complex formulas you’re like holy smokes this is a database you just built an Excel like this is way too complex please don’t touch C4 please don’t touch

50:34 please don’t touch C4 please don’t touch the4 right I I sorted I sorted the information you shouldn’t have done that the last the last three columns were the Lynch pin for everything else to work and you should have just taken a through z no I had a v lookup no more X lookups yeah yeah but I don’t know if I’m answer you’re spot on my friend so I think I want to ask answer your question to another maybe another flavor another angle from this Tommy like so I think your question was like how do you get

51:04 your question was like how do you get the data culture to start moving in a direction that we think we start thinking more together as a team analytically MH I think you need to provide in some cases it’s a little bit of mix of multiple things here one of it is just is just training like sometimes I think we try to take on to ourselves that we are like on an island by ourselves trying to figure everything out by ourselves there’s a lot of other really smart people who probably have figured out most of your business problems somewhere else in a different company this is one of the areas why I love Consulting

51:35 of the areas why I love Consulting because in Consulting I can see across Industries the same problem occurring over and over again so like people Tom talk me well you probably have never seen this before I’m like well actually I have not in your industry but I saw the exact same problem over here and I can take those connections and bring them together and say okay I have very disperate experiences that are all saying the same thing so one thing here is I think you need to I think we need to be more open-minded around exploring Solutions holistically as a company

52:08 Solutions holistically as a company another thing I think here around you another thing I think here around the needs of training is you need know the needs of training is you need to give people space to be able to train themselves the argument or the a data culture or a culture around I have no time to learn something new because I’m so busy I think is a detriment to the company and that’s it that is a that is a pure people and management piece that’s happening inside the organization you’ve given people so much work you’re not letting them spend time to actually go learn power query take a class on some data engineering take a class on

52:38 some data engineering take a class on some data visualizations like expand people’s minds by giving them some space to be creative in how they get to their Solutions I think what that affords you is if you pay for training if you pay for something to come in and talk to you about this in your company one it gets everyone thinking the same way to some degree you you can bring in this outside perspective that can give people more insight and I I gotta be honest Delta Associates was the company that I used that I got pushed through for training and I thought I was

53:08 through for training and I thought I was good in Excel until these guys came in and showed me like a whole new way of thinking about things and it really helped me focus on yes we may have lots of sales in these different products but which product is actually most important to us as a company and and I think a lot of people can to your point earlier Seth right you can get it really around the world here and do a ton of statistics and data and numbers and Analysis but at the end of the day does it really point you to the most important thing you need in your data

53:38 important thing you need in your data and I think that’s a learned skill I think it’s a learn skill to figure out from all this information where do I focus my attention that’s hard so I would put around give space to people provide some training from external sources encourage them to read books maybe even start like a book club go find some great visualization books and read them together as a company and say we’re going to buy these books for everyone at lunch come down and we’ll talk about what we’ve been reading has anyone found anything interesting or what are you doing does

54:09 interesting or what are you doing does this apply to your day job stuff like giving some space for that I think would really help and then maybe my last Point here is to your point Tommy like how do we push people Beyond just the report and I think you’re right I think when people talk about powerbi they talk about powerbi report page it’s way more than that now especially now with fabric so I do think again having space for people to explore what is a page report how do I connect a pivot table in Excel to a data model and use data from there and then maybe on

54:39 use data from there and then maybe on those more advanced users starting to expose them to spark notebooks and how does a notebook work and how can I access data from a lake I think those are the skills that are going to be most valuable to your company because it’s really going to allow the company to use real Enterprise tools to build the nextg solutions that they need for their business and I think that’s the real Lynch pin for me like I’m seeing data engineering become a commodity anyone can do it now and Microsoft wants that to to happen you both have said things that

55:10 happen you both have said things that are really connected W with me and one thing I’m hearing from both of you in an indirect way is there’s a lot of Reliance to on what the business is willing to measure and what by that is if you’re just looking at your sales over time or that’s the your team sales or like the number of calls taken right that from a very basic level if that’s it then that’s fine we’ll be L kpi but I think part of the training Mike is not just how to use powerbi or

55:40 Mike is not just how to use powerbi or connect to your data but how and what are you measuring for example if I want to push my teams like well I don’t want to just look I want more calls but I want to make sure that we’re more available to calls okay let make let’s make that a goal for us this quarter okay that all becomes a different way not only from the visual side but also the Dax measurement not only more actionable but it becomes something that now is tied to your whatever your foundational metric is of number recalls

56:12 foundational metric is of number recalls but you’re looking at it a different way so what we’re actually measuring and how we’re actually measuring it comes from the business yes because I’m not gonna push them say oh by the way everyone’s only available 60% of the time even though you wanted a call center report to look at number of calls unless that’s important to them it this goes back to our earlier conversation around the the implementation side of things like like yeah yeah to me this I think really makes you sit back and sit sit back on

56:42 makes you sit back and sit sit back on your ideas and say what am I really trying to measure right what is we say we can we can say very koi terms like I want better engagement on my website what does that mean how do we quantify that what numbers can we put behind that does that mean we have to throw a survey on it and say are people happy or sad about the experience they’re receiving do like I even see like I was in an airport recently and I don’t do you guys do so when you’re in the in the airport you’re walking out of the bathroom

57:12 you’re walking out of the bathroom there’s sometimes those little smiley faces like a red yellow green on the airport do you ever spend time to provide feedback through that back to the airport or whoever is running the bathroom have you have you seen those take look at the status of the bathroom first to see if it’s actually working or not before I click on it well I

57:31 not before I click on it well I look at them and and it may be totally anoculus it may be totally anoculus about what’s going on there Ian it could be just like a human experiment on me and I don’t even know right it could be something that’s like I’m a placebo effect like I had a better experience in the bathroom because I was able to click the green face as opposed to like the red face or maybe I felt better about the experience by clicking the red face and the data goes nowhere I don’t know but my opinion here is like I think that’s a really interesting feedback item people can passively go through and if they had a bad experience that something was out something didn’t work

58:01 something was out something didn’t work they could either click the smiley face or the the frowny face and that would at least give the people managing the facility some indication around we should send people to this area of our building something’s not working over there to your point Mike if the business or the airport was not willing to measure that or actually have that as one of their metrics that a that’s not happening and that goes to your I think the open-mindedness side yeah don’t look at just sales yes that’s important that’s obviously what we’re all aiming for yeah but be open to

58:32 all aiming for yeah but be open to another way to look at this and that’s exactly what I see and I think I think this is the idea of like what do what do we what is our ultimate end goal of what we’re trying to accomplish here are we trying to accomplish satisfaction when people are using our facilities well how can we measure that in a non-intrusive way or setting people down and having them do surveys because you that also skew some of the numbers as well so I think these less intrusive areas allow you to have the ability to detect things and again now with like

59:03 detect things and again now with like all the things we can do with AI and video this is where the the volumes of data is going to be increasingly important and it’s going to be more impactful for your business is now you can just sit a camera feed down a hallway and you can literally detect who what type of people are walking down the hallway and you can even say are they happy are they sad are they mad like can get emotions off them via the cameras like so the amount of like what we want to measure about whatever the situation is using my building what we

59:34 situation is using my building what we have to be more intelligent about what is the end goal what are we trying to accomplish here and then from there we can start walking back and say are we even collecting the right data do we need to have different methods to collect what we think is valuable because I think a lot of times we want these great goals but we don’t even have the methods to collect it initially I I can Mike I I’m envisioning the president of the airport and a board meeting going we need to improve the experience at our airport we need to people have a better time what do you think someone goes bathrooms what it’s like well everyone hates a bad

60:06 it’s like well everyone hates a bad dirty bathrooms like so what what do you want to do we’ll do a feedback survey how do we how do we know which B like which one of the bathrooms we don’t have enough staff to keep every all the time which one’s which one’s the worst one is it more real time than you think where it’s like red red red red sense Seth over there clean the toilet you Seth over there clean the toilet yeah data culture everyone has to know yeah data culture everyone has to be open to those conversations and open to measuring that but again it goes back

60:38 to measuring that but again it goes back to leadership saying what do we care about what are we really trying to measure yeah I’m I I hope this doesn’t deail on my final thought but when when we’re talking about conceptual models and Reporting and this cycle where you and Reporting and this cycle where sometimes these are quick insights know sometimes these are quick insights and then they’re not and then we’re answering more questions and then things evolve more and more I’m getting enamored with this idea of the conceptual model being one of the most important parts in engaging with the

61:09 important parts in engaging with the business because it would allow us to solve the short and long-term problems and get us out of a cycle of people thinking one report is the thing as opposed to it being an evolving solution right it because yeah then it’s the framework it’s the place I can go back to with all the conversations what are we learning how are we improving what is the fastest way we can consume and make decisions and then it’s like we have that place where we can say

61:41 like we have that place where we can say here’s the problem this is the solution we have okay what’s next what’s the next solution then two months later you come back where where were we why why were we doing what we were doing great that that’s not relevant anymore let’s shift gears and if all that’s in the same place I I think that is going to create almost more business value than the products that are developed because in some way sh perform unless those become like the daytoday

62:12 unless those become like the daytoday reports right if it’s a day-to-day report those are the ones that are like a part of the business all the time but a lot of the reports fall into this realm of like six months later why why still supporting this or or hey this report is doing this why did we decide to do that and it’s a good point documentation I think it’s part of this cycle that data analytics is taking raw data that means nothing and making B

62:43 data that means nothing and making B creating business value and visualization is simplifying that for the the conversation and if we don’t have the context of all of that work we start stop we start stop we start stop right or we create ourselves challenges and like I’m just I think it’s this piece in here where for some reason I keep coming back to boy that having a conceptual model really evolves I think this trade or not trade but like

63:15 I think this trade or not trade but like this transition where we’re going from raw to something more meaningful to something enhanced to something that’s Dy ding bigger and better things for the organization and I think ultimately these two concepts they work and play well together but that’s where I land with this conversation that’s really a lot of good thoughts thoughts there that that conceptual model I think is very is very important a number of projects I’ve

63:46 important a number of projects I’ve been on with had a lot of data we just needed a good job sitting down and talking about how does your business run tell me the Big Blocks that you care about people products yeah these things and when you can start articulating those higher level goals because there’s usually a lot of like dirty data and weird stuff at the bottom you got to like reshape and figure it out I really like that I think that’s a really good point Tommy any final thoughts as we wrap today I think we all need

64:16 wrap today I think we all need to do a better job and not just the three of us but when we go in to say what is powerbi and what is business intelligence to have that conversation is we’re no longer trying to tell you what the score is we’re going to tell you how to win more baseball games and being opened to a different way of looking at that we’re not just looking at the final score we’re going to show you the number of hits let’s talk about that and that’s going into before we’re even showcasing the report and we’re showcasing the visuals and all the other neat bells and

64:47 visuals and all the other neat bells and whistles it is that to your point that conceptual side of it of why are we incorporating business business intelligence or basic intelligence or data visualization in any former capacity and you’re right it starts with what we’re measuring I’m gonna always go back to this is know what you’re measuring and how you’re measuring it and that’s where all this begins and will ultimately end yeah I think you’re gonna get your best wins there I would say from this

65:17 best wins there I would say from this conversation here I I think I feel I think I feel like data analytics is a super set of data visualization you use data visualizations inside your data analytics I would like to think that the data analytics can span further than just reporting and I think I think opening our mind up to Beyond just the report it’s it’s a pagein report it’s a notebook it’s tables that are sitting in a lake house it’s even getting to the to the data science things things of the world right you’re

65:47 things things of the world right you’re going to peel off parts of your data and do special things to it and you’re going to need to store it somewhere so this is why man I’m just so excited for for what Fabric’s doing because I feel like this is something I’ve been working on for like six years with companies to help them build and mature and and and now it’s coming into my my other fun area of powerbi like this is so sweet because it’s it’s now a merge of like these really cool tools and Technologies I think we’re really on a point mean I think we’re really on a point here where a lot of companies have promised to deliver this entire ecosystem I feel like Microsoft is making really good strides to do this in

66:18 making really good strides to do this in a cost-effective and easy to consume way for companies or or for the business to consume so I’m really excited about this and see where this is going to go all right Seth last I last point oh okay he already did his he started he started last Point Seth actually looked at the clock because I just looked at the clock I was like oh my gosh we’re already an hour so with this one this episode’s a little bit long apologize for being a little bit lengthy but we had a lot of words apparently to say so with that we

66:48 words apparently to say so with that we really appreciate your ears we know this was a long hour and six minutes for you to listen to us we hopefully you you got your runin your your jog maybe Tommy can can can say hello to you on his Pelton from his basement when you’re you’re doing your workout just a bike just a bike maybe you should put an iPad in front of it then you can you can say hi to all of our fans you you can say hi to all of our fans power B P Pedal Power on powerbi know power B P Pedal Power on powerbi maybe Tommy will start a new podcast here pretty soon powerbi pedaling with podcasters yes exactly so with that we

67:21 podcasters yes exactly so with that we just want to say thank you so much if you like this convers if you’d like thinking about data and analytics or if you have other thoughts around this please let us know in the comments we do watch and read those Tommy will probably respond to them before anyone else does because he’s watching them more than everyone else is but we really like your feedback and we appreciate the comments Tommy where else can you find the podcast you can find us in apple Spotify or wherever get your podcast make sure to subscribe and leave a rating helps us out a ton or share with five people send out a link you never know what can happen do you have a question an idea or a topic that you

67:52 question an idea or a topic that you want us to talk about in a future episodes stop it Jo head over to power. tipsthe podcast leave your name and a great question join us live every Tuesday and Thursday A. M Central and join the conversation all powerbi tips social media channels Tommy has a big poster in his in his basement that has all those words on it so that he doesn’t forget how to say it every single week I couldn’t stare it Seth or I was gonna lose it so I love I love the fact that just me smiling throws you off so much it’s so rare it’s so rare

68:25 so much it’s so rare it’s so rare amazing well with that we’ll end this with a smile from Seth thank you all very much and we appreciate your time see you next

69:00 [Music] out

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