Future of Data Visualization – Ep. 319

This episode looks at the future of data visualization: what’s changing (AI, interaction patterns) and what isn’t (clear definitions, good modeling, and performance).

News & Announcements

• The Evolution and Future of Interactive Data Visualization (Part 1) | Nightingale — Interactive data in the pre-Web era Interactive data visualization is an essential component in the current state of our web.
• PowerBI.tips Podcast — Subscribe and listen to the Explicit Measures podcast episodes and related content.
• Power BI Theme Generator — Create and download Power BI report themes using the PowerBI.tips theme generator.

Main Discussion

The conversation zooms out from product features to talk about how visualization is evolving—and what teams should focus on so their reports stay useful.

Key points from the conversation:

• AI and new experiences: how Copilot-style tools and natural-language interaction may change how people explore data.
• Storytelling over dashboards: visuals need to support decisions, not just display numbers.
• Consistency and reuse: why standards (themes, patterns, templates) matter more as organizations scale reporting.
• Performance and simplicity: a “cool” visual isn’t helpful if it’s slow, confusing, or hard to maintain.
• Accessibility and clarity: good visualization is still about communicating clearly to the widest audience.

Looking Forward

If you’re modernizing your visuals, start by standardizing themes and report patterns—then experiment with new interaction/AI features in a pilot before rolling them out broadly.

Episode Transcript

0:21 [Music] out out [Music] welcome back to the explicit measures podcast with Tommy Seth and Mike hello everyone and welcome back to the hello happy Tuesday sure that’s the right one is that the right one are we a little not confident here

0:52 confident here Thursday not at all confident at all okay that didn’t sound like the normal enthusiasm that we have that was I think not that was that was basically a me looking over to see if I was going to get your reaction of like am I going to miss it and going yep I’m gonna miss it and just saying it wow you’re doing the mask in your head okay miss it what episode is this one gonna be can we start with that Tu I don’t know if we can have the same conversation with that least enthusiasm happy Tuesday

1:22 with that least enthusiasm happy Tuesday oh I could manage manage okay this is going to be a fun episode I can that already oh man I want to argue with everything Seth says we’re going to get I’m I’m just I’m just going to say Tommy that’s probably not a button you want to push this morning oh just just gonna say that what but you can having said that maybe it will be fun listen I don’t call danger danger calls me okay so yeah well she’s she’s not very nice to You Tommy I

1:53 not very nice to You Tommy I know I like taking my my my my stripes I don’t know if your wife knows about danger that’s that’s oh move on new topic new topic she doesn’t listen right no one does actually they only only that’s the funny thing most of our family members only listen to the first couple minutes had we said this like 15 minutes in the episode I’m pretty sure no one would have heard it but the the beginning of the episode yes they may have I should do my then introductory since when I when I’m pretty busy I

2:25 since when I when I’m pretty busy I don’t do a great job of calling my family so hi Mom hi Elena hello that’s cheating dude that’s totally cheating this counts I’ll call you next week I’ll call you every Tuesday and Thursday at amm join in join in good to see you online Tommy that’s very manipulative you don’t you don’t call your family and you use them to get more views it’s smart I don’t tell them the listen it helps if it helps us if it helps it helps we’ll go up to four users

2:57 helps it helps we’ll go up to four users total they don’t bring users to the to the podcast yeah so not yet not not yet not yet all right jumping in today I don’t really have any major announcements there’s not a whole bunch of things coming out from the Microsoft news or blog or announcements it seems a little bit quiet right now so I think we’re going to skip right into our main topic for today so the main topic today is an article Tomy has found I think this will just create some interesting discussion the name of the article is the evolution and future of interactive data visualization and it’s

3:27 interactive data visualization and it’s coming at a two-part Series so we’ll have to read through part one in part two it’s night Andale devs the author is clever Frankie I think is how he would say his name I go with itank that’s what’s listed on I would agree with you okay just making I just confirming looking for some verbal cues here from Tommy as we look at the video here making sure that yes this is in fact clever Frankie I wasn’t expecting clever Frankie but yeah that’s okay shocker

3:57 Frankie but yeah that’s okay shocker there we go but jump Us in Tommy give us a an intro of like the article what’s it trying to convey here it’s just talking about this is a little bit more historical of where visual data has come from and how we see this portrait on computers yeah even though we say we’re all we’re veterans in the space for data Vis powerbi which nine years is nothing you powerbi which nine years is nothing nothing to sneeze at or data Vis know nothing to sneeze at or data Vis has been around for a long time and even the collection of data and then trying to communicate with it the article goes

4:29 to communicate with it the article goes in I think and the part one at least is really focusing on how technology and people and the ability not just on the RAM and the computer speed to show visualizations but more importantly the ability to share and consume that information has changed the way we one interact with data and two visualize it so we’re we’re starting right from the beginning in terms of whether data was our first thing we collected but talks about all the different ways and moving forward I think more

4:59 and moving forward I think more importantly when we look at where we are at today in 2024 with the amazing technology we have the amazing ability to collect data what’s causing that as more people adapt and I think probably evolve to being better Adept to looking at data and then where do we go from here and also then I thought yeah so I have two questions one is you said part one so this is H part one of how many articles two

5:30 many articles two two all right I thought you were going to drop like this is seven 17 articles now going to be like our seven part series a little better so and and the the second part is how far back in the way back machine are we going yeah we’re we’re not GNA necessarily I think focus our time but we got of start here 1657 so can’t can’t wait to hear this yeah again I’m not going to necessarily choose to focus my time really we

6:01 choose to focus my time really we just talk about interactive data in the pre web era that’s part one that’s pre-1994 and I love some of these maps on data visualization looking at weather statistical data in the Boston area again in the article Contour conform it Trend surface these the giant pixels on a screen I do remember this from at least High School of data Vis and the ability to actually consume data was a very I don’t want to say glitchy but it

6:32 very I don’t want to say glitchy but it was a stagnant approach it wasn’t necessarily something interactive to what we’re used to today so I I like where we’re going on this one but I’m GNA just pick on some of the article pieces here I want to just pick apart some sections here right so the article kind sections here right so the article starts at like of starts at like 1657 right it’s data collected from that period of time there’re visualizing data for global temperatures and showing a graph of the stuff so I think I think think there are a number of key sections that are pointed

7:02 of key sections that are pointed out here right so there is data that comes out pre of the internet and the web and then there’s data that comes out after the internet has been invented so I feel like this is a a relevant point because how did you distribute information before the internet it was all in print it’s all in paper form so unless you had Advanced ways of printing things visuals in I don’t even know what’s in newspapers back that that old I don’t know like I don’t know how you would visualize that stuff but like that would be the only medium someone would draw an image put it in a newspaper and

7:32 draw an image put it in a newspaper and that was the image that we used to to graphically show the information now moving forward from that post internet invention I think that’s where a lot of this stuff starts accelerating faster and I’m going to say this again because I said a lot in the podcast it feels like a lot of data has been commoditized it’s becoming a commodity so it starts with okay you have to have a computer you have to have the right software and so the article talks about like all right we now get computers that can do

8:03 right we now get computers that can do some very basic maths on things and start drawing things on a screen for you and then it gets to a point of okay now we’re having computers that are actually personal computers and so now for, dollar you can have this laptop thing or this big brick of a machine on your desk and do things at home like that’s a new era and then it it gets adopted by business business starts utilizing it and people now start finding the value like Loc like Loc like inside their homes and and then it

8:33 like inside their homes and and then it goes from there to like okay well the computers exist what about the software the software doesn’t exist yet and this is where I this is where I think I’d like to pick up the article honestly I’m skip I want to skip all that old stuff okay some of these come on man some of these images are pretty crazy like touch screens in 1972 or what was a touchcreen the yeah the brick of a house behind the screen screen talk about but true well there’s there’s an important divide and I want to focus

9:04 an important divide and I want to focus on the digital space too but just real quick on that pre era and then we’ll we’ll we’ll go into the future or into the past I guess but there’s a lot of important aspects that we’ve learned from the pre-digital era or the pre- internet era that we’ve done on this podcast and about the one of the big things back in the day was also the lack of resources not just data but also ink I think in benetti did one of our we

9:31 I think in benetti did one of our we did one of his articles and he talked about the data to Ink ratio something that now is totally applied in one my training but also in my idea of as we build and that idea was you only have so much ink on a newspaper or you have only have so much n ink to use on paper use it wisely if you have two x X and Y AIS with titles and you already have a title well you’re wasting a lot of ink that the company’s using to spend and there’s a lot of principles here even back in the day that are still pretty heavily

10:02 the day that are still pretty heavily applied now or should be applied now even though we have all the resources and all the software and all the internet possible I think you’re you’re talking about the the theory or the data ink ratio as described like Edward tuft yes that’s right Edward tuft so Edward tuft was the the idea of that the originator of that and I I liked how he simplified a complex problem and said imagine the cost to make ink was extremely expensive and this is what I

10:33 extremely expensive and this is what I extremely expensive and this is what by like talking about mean by like talking about visualizations and things have been commoditized because today like you can have color all over the place you can have like it doesn’t cost you anymore TimeWise to render a report that has a lot of stuff or not a lot of stuff other than the fact that it’s a lot of time to build it right so now now I think our time is measured not in in data to Ink ratio but more of like developer time to Value ratio right does it do I want to do all that extra styling to make it super fancy but I like this I like this concept and I I’ll

11:04 like this I like this concept and I I’ll just make my point here I move on mhm I like how you took it to this the extreme like okay imagine Inc is no longer 10 cents of black and white copy let’s turn it all the way up to, 000 like let’s make it really expensive for us to put ink onto paper okay knowing that information do you make different decisions and I think you do yeah it’s funny it’s like the lack of limited resources almost output best practices that we use today oo that’s

11:34 practices that we use today oo that’s pretty that’s pretty impactful I like that limited resources outputs like you have to really think about what you want to produce right I like that now there probably a better way to say this and I may make a t-shirt out of this but I like where that’s going but you look at all these visuals here and the the start of digital information again the number one probably concern if you were to ask the people working on this is like what’s your biggest problem what’s your barrier to entry to get this started they’re going to say probably our ability to compute so we have to be very

12:05 ability to compute so we have to be very conscious and very calculated on what we’re going to render and then it’s probably that ability on what data we actually have access to so there’s a lot of calculation that again we don’t even have to think about now just because you’re not thinking about it doesn’t mean that there’s not a cost right like and that’s where that’s where things can Accel rate and I like I I do like your point about the the cost of things driving more intentional

12:35 of things driving more intentional action action and to to some degree as visualization has changed or our ability to visualize things in tooling very quickly so has I I think been lost along the way here because it’s so commoditized the value behind visualization right so it’s ironic from the standpoint that you would never see or couldn’t see things

13:06 would never see or couldn’t see things because in order to aggregate or put together a visual you would need massive compute power right which just didn’t exist like even you think even when I started in databases right like if I think about some of the queries that I run against my big data like I wouldn’t have been able to aggregate the data 15 years ago and now we easily can not only aggregate but I can just like I can just throw it into a a visual without much thought whereas po

13:37 visual without much thought whereas po pre those days where it’s like hey this is going to cost us $2, 000 to come up with the analysis and everything you’re very diligent about all of the steps because you get one shot at the processing right and in some degree it’s like yeah I’m talking data but even in visualization I wonder to some degree Tommy if if there isn’t as much Focus or intent behind what we’re throwing up throwing up on a page for people to digest and that’s where to me there there’s an

14:09 that’s where to me there there’s an interesting conversation Point well I think that was my problem and that was that Segways nicely into a question I was going to have is the other side of this coin is also all the visualizations you’re seeing in the beginning here this was not someone who was dragging and dropping with the mouse there was a very specified skill language or tooling that was involved yeah and like I said I will be the guinea pig here in 2015 you gave me powerbi and no skill in data visualization and no training in data

14:40 visualization and no training in data visualization and I apologize to all my first clients and all my my first consumers of my reports because it was very much what you said a throw up of the visuals because you gave me access to all the data and more or less all the tooling with no skill so you’re dealing with back in the day something with limited resources but very funneled skills and we basically have flipped that on its head in today’s

15:14 world I do like that and I think again I’ll go back to like this whole concept of like it’s becoming a commodity at this point I really do think like things are becoming easier it’s it’s becoming less effort and I think I like your point there Seth because when you had to plan things out when it was harder to do you had to be much more measured about what you were producing right I think this I think this Spurs two behaviors one Behavior it Spurs is the ability to crank out a lot more reports quickly which means I can try more things at

15:46 which means I can try more things at once but that means now I have potentially a lot more waste that I’m going to try in the time it would take me to build one thing I could build 10 and how do I evaluate which of the 10 is the best solution or two of the 10 is the best solution so I think that the behavior is I’m going to now produce a lot more there’s going to be a lot more stuff and so the second Behavior I think here is you you tend to collect a lot more things and so you’re now becoming like this accumulator of a bunch of reports

16:16 this accumulator of a bunch of reports that may have certain amounts of value I see it in my tenant right now like there a whole bunch of stuff that’s created that I haven’t touched in a while I throw it out there it’s almost nothing okay fine it’s in the tenant I don’t ever go back and clean it up there’s nothing like there’s nothing like an auto scrub there’s not like get rid of it stuff it just sits there so what what’s what’s more interesting to me the more I think about this is if if previously in entire like people spent an enor amount of time to build a

16:48 an enor amount of time to build a visualization and we’ve come so far to the it like that requires a lot of expertise and we all know like we’ve read several books and there’s a lot of ideas and theories out there of like good visualization good picking the best practices doing all the it is a a role studied role within uiux Etc sure and we’ve like visualization has gotten so commoditized within these products

17:18 so commoditized within these products that we’re okay just saying self-service is a thing now mind you like it is for the standard things everybody knows what a bar chart is everybody knows what a chart is everybody knows like what a pie chart is unfortunately but like you throw in there like everybody’s just throwing stuff against the ball and sometimes you’re not choosing the right things or you you have to have conversations about look and feel and like there’s a reason there’s intentionality behind this but

17:49 there’s intentionality behind this but the meaning almost gets lost a little bit and like the expectation that everybody can just vomit out the same stuff is a a false one right like if you if you still want good insights and good like good reporting and good visualization it requires people that know and know and understand a lot of the the technology structures and theories behind how you build these things

18:21 behind how you build these things effectively that goes to a great point that you said earlier about there’s a li there’s still a limited resource you’re just not aware of it anymore just because you have the entire canvas and you could put 20 visuals on there and it’s not going to break doesn’t mean that you’re running into problems because you’re running into the cognitive load I want to pose a scenario or quick if you were a data Zar and you working on a project and I gave you limited resources very limited resources what the computer could render and how many colors or visuals that you could do

18:52 many colors or visuals that you could do would you have more confidence in the quality of that than if I just gave you all the bells and whistles now you’re talking about like a version two of parb desktop versus

19:04 version two of parb desktop versus version whatever we’re on now n years later five right let’s say vers five thing when it was powerbi designer so you’re giving me powerbi designer in one hand you’re giving me powerbi desktop in the other hand right right I’m giving you prob service or something yeah with visual C so can add exactly because to me that’s where that’s where my head goes is I feel like if I was limited where there were barriers I feel like I would output at least initially a better looking or more effective report based on where this

19:35 effective report based on where this conversation’s going I don’t know I think I think giv me more I I think better looking is a very subjective term to use here because I think you could very much compare like okay there are greatl looking let’s call them sample dashboards on the internet you go around you look at like novie Pro is one of the websit has a lot of good examples of like incredible powerbi built reports that look nothing like a report so I would call them amazing

20:06 report so I would call them amazing looking reports I think you have to really Define to your question what is the objective you’re trying to accomplish are you trying to convey information to make a decision or you’re just trying to make a stunning visually good-look report that interacts with great uiux right I think my argument here is if you’re just trying to convey information you have to concisely think about what information you’re trying to convey is and design for that whether that’s just a couple kpi cards you can run your I think I was watching a

20:37 run your I think I was watching a YouTube video saying how do how could I have a better report run or how could I run my what are what are my five metrics so if I’m running a business and I was on a beach Island somewhere there’s five numbers I should need to know if my business is healthy or not or if I need to make changes or not what are those five numbers so if you if you keep distilling down lesson and less and less I think you can get down to like these are the critical things we care about to make our numbers better and I think this is actually speaks to the example that Microsoft gave when they

21:07 example that Microsoft gave when they talked about their kpi and their metrics they have a I think on their adoption road map they have a little section on the right hand side that talks a little bit more in depth about what Microsoft did with their internal kpis what they’re doing with their internal metrics and they had like 150 metrics or kpis they’re using to measure everything they’re like that’s too many we can’t make them all good let’s is there something we can do just just still that down I think they got it down to 45 or 35 35 key metrics that said if we win on these we can tie those metrics to

21:38 these we can tie those metrics to success in selling sales and software and all these other things so I think that’s important to really cut out the noise and go down for simple and make action that way but that speaks more to like what’s the point of the report yeah pretty or not that’s different yeah I wouldn’t I wouldn’t necessarily say that like limiting my resources is going to help me effectively do a better job what I what I think it’s pushing forward in my mind is

22:08 my mind is is like the expectations setting is different right like back in back when we’re looking at hey I it’s going to take a really long time or a ton of compute or Inc to produce a visual the value was the single visual because it it gave insights that were other really hard to see or completely unknown and nowadays like what is What is the value and how how do you quantify

22:38 is the value and how how do you quantify it compared to like or different like how do how do you quantify value versus different like the fast path throwing something on throwing something on a page and and I I think to me that that drives towards the levels of the type of reporting reporting right you sometime sometimes or I should say like the value here is there is self-service the value is people can do analysis and they can they can look at

23:09 analysis and they can they can look at aggregations there’s a ton of answers people can find by just you utilizing the basics of powerbi right like power query I can create some buckets I can filter out data and then throw it into a report page and create a visual and look at the visual and get insights I never would have just seen innately huge value in there but the minute you get towards where that large effort of value was the single visual I do think there’s that

23:41 single visual I do think there’s that delineation between okay now we have a senior leadership report or an executive leadership dashboard and Report where you’re really tying things out and it is a comprehensive report where you’re showing multiple different types of visualization or the best presentation for these types of metrics that allow people to consume them quickly and that that does require that you spend that extra time there and maybe that’s where the the F my

24:11 maybe that’s where the the F my focus should be as opposed to just cart blanch saying like hey like every everything’s vomit out there but it’s not there’s a ton more value that we can get because we have all these capabilities on the lower and lower levels meaning people are making more informed decisions or making bigger mistakes because they can see more data and visualize and you’re wrong and Mike this may actually be going to where you wanted to go to in later in the article where one of the relative still relatively new shifts in data visualization we’re so accustomed to it

24:42 visualization we’re so accustomed to it now because that’s obviously what we’re supposed to do is the ability to share it and the ability to have an audience like we’re talking about the audience here you’re talking about the value that’s based on the people viewing it and we’re talking about executive dashboards this is still pretty relative ly new maybe 25 years old the ability to easily share data visualization that’s one of the Artic parts of the Articles talks about everything was really still restricted to the physical world it was printed or

25:12 to the physical world it was printed or stored in a drive that we’ carried to another computer we take this for granted now because powerbi is obviously meant the full intention of the whole tooling is the ability to consume that across an organization yeah you you say that but I haven’t encountered organizations no no I have encountered organizations that still stay PBX files onto SharePoint drives and then have other people go access said reports from so like this is why I use the word intent but agreed but like this is this

25:44 intent but agreed but like this is this is where I think what we’re seeing now is like one one part I see this is like Lego bricks right one part of the technology had to be like the computers had to be strong enough and had enough memory to capture the data right two we need to have software that’s better to use and the Artic talks about like using bical I never used it using mat lab I did use that but back in college for more engineering things Lotus 123 like another Excel like program and so what you find here is there’s like all these different

26:14 is there’s like all these different programs the software starts increasing in capability which adds again it’s to me this is how I see it it becomes more of a commodity right everyone can get mat lab everyone can get Lotus 123 and we’re starting to continue to see the barrier drop for who can get access to these programs to start doing visual based things and then with the software comes like the proliferation of devices right now it’s a laptop is super cheap to go get everyone’s got one now

26:46 to go get everyone’s got one now everything’s on a mobile phone right so if your company doesn’t have some sort if your company doesn’t have some mobile option or mobile web version of mobile option or mobile web version of a of your company software like they aren’t going to use it as easy they’re it’s it’s a lot more focused on like mobile experiences and I can buy these devices that are full computers that sit in my hand that’s incredible we never had that before and so I think what’s happening again is the technology is getting cheaper and cheaper cheaper becoming more commoditized with that we’re generating more and more data data is becoming a commodity and now we’re having the tooling that supports it all

27:17 having the tooling that supports it all become more like a commodity and another argument I’ll I’ll use to render against that is harbi desktop came out and I think this was a genius move by Microsoft it was free where all the other heavier visualization tools even Excel if you call it a visualization tool comes with a license you have to pay for it and I think the threshold here was Microsoft’s going to make the tool free but you pay for the share that’s that’s the difference here and I think to me that was a very wise move because it let

27:47 was a very wise move because it let everyone explore the tool this brand new thing that they’ve never been experiencing before they were able to get comfortable with that first find that this could be really interesting and valuable and then move into how do I share with my team how do I distribute it can I ask you about the commodity this is something I think we all agree on on data is a commodity now and something that’s been touched on a lot in our our previous conversations in what way as data as a commodity or technology as a commodity

28:18 commodity or technology as a commodity have we as business intelligence MVPs or Pros have to clean up after because data is a commodity obviously I think I think we’d all consider it a net positive right we’d all say it’s a good thing that data has more access to more

28:34 thing that data has more access to more people but there are ABS ways where it’s hurt right there’s ways that it’s like we have to really put some Band-Aids on or really have to go back where were you see the biggest cause for data being a commodity that Pros have to come in or have to be aware it’s not 100% commodity or or positive I think something I think someone scarred you along along along you don’t have scars man well I along you don’t have scars man well right I feel I feel like we bring

29:05 mean right I feel I feel like we bring up this a lot with Tommy he’s like you up this a lot with Tommy he’s like how do we how do we throw people at know how do we how do we throw people at this problem for data qual like I get it I don’t know if you can always have 100% clean quality all the time data and yeah it’s going to be commodity I think this I think this comes with the territory right with more data you get more junk like you’re not going to be able to increase the volume of data without getting some level of additional junk thrown in there with everything else so my my answer to your question is I think it’s a I think it’s less

29:36 is I think it’s a I think it’s less about the data and the quality and the cleansiness of the data I think it’s more about who’s responsible for making sure the data is of good quality for the organization to use and I’m going to keep leaning on like I really like this story of like who’s responsible what’s the data stewardship story that goes with the information cuz I think that who cares how much data you have you have a little bit you have a lot of bit but if it’s wrong in a little form or it’s long if it’s wrong in a big form someone needs to own is this stuff

30:08 someone needs to own is this stuff valuable to our organization how do we make sure it stays clean how do we put controls around it so we know that when it gets out of out of shape it’s out of quality when do we stop what we’re doing to build new products to go Focus back on the quality of the data or higher like to your point Tommy right I can probably run my business on 10% bad data and still do just fine maybe even higher if you have other companies that are doing things differently your process is weak maybe you have a lot more dirty data but what do you do to solve that problem you

30:40 do you do to solve that problem you throw people at it and so someone’s taking ownership someone’s getting thrown on the problem fixing the data making sure it’s clean so what is that threshold between how much junk data can I tolerate before I have to start cleaning it different Industries are going to handle different levels of this this man I I’m going to lean into to what Tommy is saying so like the the commodity part and I don’t really there’s an aspect that I agree with you Mike but there’s the other aspect that I

31:10 Mike but there’s the other aspect that I don’t okay because the commoditization of data and or systems that allow business to use them it is is a problem like name anybody can name any of the it’s been a long day such a short day I’m just getting up all nighter nighter like pick a CRM y right a

31:43 nighter like pick a CRM y right a perfect example of the commoditization of data and or platforms is throwing business people who have no idea how to architect systems of data into crms and the result is the crms that we get to deal with right like that is a commoditization of simplifying data work to the point where anybody can do it and the problem and we’ve seen it not Mike you’ve seen it right it’s just how bad is the implementation so much so that you’re right you do have to throw people

32:15 you’re right you do have to throw people it at it eventually a lot of people and people that actually know what they’re doing related to Building Systems of data architectures in a CRM so I do think there’s a problem that is rampant and and yes ultimately there’s an owner but even if the CRM gets launched with somebody who has no idea how how to build it the infrastructure underpinning these applications they’re the owner but they’re building something that’s

32:45 they’re building something that’s defective for the organization I think where but unknowingly yeah right So eventually eventually as an organization evolves you figure out talk now we’re talking data stewardship now we’re talking cleanup now we’re talking like all of the things that evolve and that’s where I do agree with you like yes structure all of the fixing of the things has to be done but that’s after the fact so like it’s become so easy that anybody can do it

33:16 become so easy that anybody can do it and in some way shape or form like you and in some way shape or form like even on the visual level a lot of know even on the visual level a lot of just because somebody can do it doesn’t mean that they’re doing it with intentional intentionality or an understanding of how something should work I don’t know if we even answered your question at all I think we just I think we just disced is it the commity I said yeah I think it is okay first off I love that we’re talking about data visual the history of data VI and we’re talking about people and this customization because I think this is dead on point are you kidding this is

33:46 dead on point are you kidding this is okay just making sure I didn’t I just it was saying things and maybe it wasn’t we’re always it’s always giberish it’s just how we interpret it but no well let me Focus first what Seth said because I think think this is the underlying tone that we’re talking about here the CRM systems as soon as you said that I just remember some implementation it’s like it’s all fully custom you can do anything you want in this custom tooling if you want to make this field or this and that’s usually what led to problems and I think about opening up powerbi you can

34:16 about opening up powerbi you can customize everything the it’s a white space I can customize how big the space is and a lot of times to me like to if I were to answer the question that commodity is we we don’t build I think solid enough roads right we’re we want people to drive I want people to be able to navigate and take their own directions but a lot of times these are very gravel roads and because I can customize the page there’s I can Cho you like you said I can do 15 colors on a bar chart No One’s Gonna Give me an error right there’s not going

34:47 Give me an error right there’s not going to be a popup that says this is a terrible design would you like to reconsider it just goes out into the nether Spear and either stays there forever or some whatever maybe there’s an evolution there but this customization is part of that that commoditization anything just like the data that we can get in and do anything with with whenever we want with powerbi with any technology really but focus on the data viz I have the ability and more importantly any user does and this goes

35:18 importantly any user does and this goes to your point Mike on the people side anyone has that ability and the ownership with maybe not the perm I don’t to say permissions but maybe not the cert I don’t certification but that they have the ownership but they may not have the credentials is maybe what I’m trying to say they either have the ownership of the data or to build it because everything’s fully custom to me the biggest guardrail or the biggest barrier that we see as we try to move

35:48 barrier that we see as we try to move forward with data visualization is this lack of true roads of exits of the highway that’s being built because that constantly pushes people back I will always push on the trust issue I will always push on people’s misinterpretation of data because I’ve lived it I’ve seen other clients live it where we have a thousand reports we never set out the guard rails for how we’re going to build these reports of a standard and that’s too much of a

36:18 standard and that’s too much of a cognitive load and people just follow their own behavior to something of the leas path resistance so to me every step we try to take forward with technology and commod ation if we’re not aware of the guard of building guard rails we’re going to take a step back I I’m going to use two two wow a lot of good things that unpack there okay my my first unpacking thought here is to your point around Seth is maybe a we a weave in point of Seth what you

36:48 we a weave in point of Seth what you were talking about and Tommy maybe what you’re talking about here the different off ramps to different systems and things right so I liked that analogy and Seth you were talking about the CRM system and so my mind goes to like okay one that I’m familiar with and kind okay one that I’m familiar with and know is like Salesforce right there’s of know is like Salesforce right there’s a there’s a system that’s made of Salesforce I believe the Salesforce app developers have their own priorities in mind when they’re selling that software because they’re trying to build a tool that Services as many companies as

37:18 that Services as many companies as possible and so Salesforce is I’ll give you all the custom everything and they and literally they could care less about your data integrity and all the data things you’re trying to like they’re they’re trying to build a solution about what their tool can do give you everything that you need to use solely their tool cool get it but there’s all these other systems like we have internet traffic we have other apps that we’ve built that are custom in house like how do we identify these customers across all these various apps how does

37:48 across all these various apps how does everything synchronize so as more companies I think off-road off of custom software that they’ve built they found it cheaper to go with pre-built Solutions but pre-built Solutions are incomplete because it’s a solution by itself it doesn’t

38:04 it’s a solution by itself it doesn’t necessarily talk well with other software and so there’s a competing priority between the Enterprise datas and then the app built data or the things you’re buying off the shelf so I feel like that’s one thought here was one there’s like I feel like there’s a lot of competing priorities between who wants to give access to what data and who’s prioritizing what things and then your latter comment at the very end of your statement there’s Tommy you said people are going to go find the lowest path of least resistance and I think that’s right I think people are

38:35 are naturally built with entropy I don’t know it’s a very scientific term entropy the lowest level of energy right it’s it’s we allow it weow this this is allow this comment isow ENT no hey we’re at 38 minutes in there’s all the all the all the flakes have already fall off the podcast we’re only into the hardcore listeners now at this point so I can use big words at this point so every everyone everyone is trying to get down to like that that minimum level of energy to be able to expend to do something so I’m always trying to do that what’s what’s what’s the efficient

39:05 that what’s what’s what’s the efficient way to do things and if it’s efficient for me not to learn something new not to use a new tool just to do it in Excel I’ll just do that because it was efficient I know how to do it move on but I think there’s you have to push people sometimes because getting to that low level isn’t necessarily always what we want to do strategically to get us better at our collecting our data and so I I don’t don’t that comment really fits with what you were what you were thinking about Tommy there but better communication between apps might solve some of that that would require every

39:35 some of that that would require every app you use to have better communication with every other app yeah there they’re they’re all the the the little app that save the day right like all of them are like aligned for a singular purpose and all it requires is somebody to learn the tool and then they’ll want to learn that like use that tool any company they go to yeah and that’s how you get 30 thirdparty applications in your company not saying not saying that that’s a bad thing right it just happens but to your point like you you typically engage with

40:06 point like you you typically engage with those third third parties in a more strategic way when you have data programs that ensure that like what you’re going to go apply meets the greater need of the organization as opposed to spending a bunch of money just for your One Singular thing yes because that could drive the decision between the one or two or three apps that you were going to choose to solve business problems correct I’m going to lean into like Tommy’s comment around no there are no roads because I think

40:37 no there are no roads because I think it’s very applicable in data as well as this visualization article that we’re talking about over time right cars right when when they first came out not everybody had them yep right they’re expensive everybody you had to feed the engine all the time right like a lot of Maintenance but when you saw one like there that that was unique same with visualizations but if we if we keep on that analogy right we can drive

41:07 that analogy right we can drive anywhere now everybody’s got a car Offroad but it depends on the road right there is a signif and this is where I think if we if we extrapolate this idea that anybody and everybody can create visualizations or build bad data structure right it’s because you have access to the car there is a significant difference and maybe we don’t ourselves delineate it enough and maybe we should have a framework that helps folks because the

41:38 framework that helps folks because the way I see this is there’s a huge difference between having a car and knowing how to drive through a small small town with one stop sign Point yeah versus a small City with stop lights versus big city with many types of signs that you’ve never seen before m driving highway speed versus Big City six Lane highway speed and and the final like driving conundrum that even traps adults who’ve

42:09 conundrum that even traps adults who’ve been driving for forever in a day is the dreaded roundabout roundabouts oh boy right like how do you navigate that roundout in there anywhere well if we if we start to if we start to say that hey like there are three four five different kinds of levels for for data for visualization for what is the path that we need to recommend or guide users or even organizations down and say hey like to your point Tommy it almost sounds like you your experience was Yeah man

42:40 like you your experience was Yeah man they they they were they wanted roundabouts and we were still talking small City stop lights right like there was no structure there was no infrastructure to support the things that they want all be at if you have a small City at stop LS roundabouts are a great solution like but it’s like the big you want the big city six Lane highway right with a population of you highway right with a population of 5, 000 know 5, 000 people like there there’s a bunch of ways in there it’s like like I don’t even know if that was a good analogy but it’s like you’re you’re

43:11 analogy but it’s like you’re you’re there’s a disconnect between like what what it is you think you can have or think you’re ready to pursue versus like the reality of do you have your data infrastructure do visualization do how to build a good-looking report that’s valuable and drives insights as opposed to Great you built a pretty looking thing and nobody knows how to use it and this part of the choice thing by the way my brain’s going to when I went to Italy and the way they developed roads I thought they were trying to kill

43:41 roads I thought they were trying to kill people the way the road merge together which is like I I didn’t drive but I just remember like holding my wife’s hand going we’ll make it we’ll make it and like to like Chicago or even New York but it’s funny you say that though too because you’re right with I keep going back to this theme with this article because as I read the article the the most foreign thing to me in the article is this lack of resources that everyone had to deal with which is such nonexistent today on whether I’m

44:12 nonexistent today on whether I’m building on the web or building in powerbi desktop or what data do I need which all the choices available to us really I think requires whether you’re the sole Builder or an a team to have a standard process and that goes to your training your Skilling up in data viz again I don’t know how much I would push on the manag self-service to like you need to read storytelling with data but man like there’s got to be

44:42 with data but man like there’s got to be some fundamentals that we put on bar charts are simple and they look simple but that doesn’t mean that what we’re trying to convey to your ear way earlier Point Seth has the value right I can easily build a bar chart whether or not that actually has the intended impact is up for discussion and that goes to me because we have this very giant flux of all customizations without kind all customizations without a standard set of what we’re going to of a standard set of what we’re going to do I don’t know if you had anything on that because I had a really fun

45:13 on that because I had a really fun question to ask you guys so I want to see if you had anything there well I I want to keep going I like your point there and what you remind me is a something that we’ve talked on a previous one I think we a full episode on it is Javen Paradox Joven I don’t know how you say it yeah yeah yeah but Jen’s Paradox I’m going to say Joven but probably said differently but it’s the idea that is as you bring the cost down on something to use it it gets used more and so that’s what like the commoditization of things like so if I

45:43 commoditization of things like so if I give you it’s supply and demand basically it’s basic supply and demand stuff right the cheaper I can make something to run or do or use or consume the more people will then use it because it’s just like nothing and so now we have this concept of like light light was analogy to this like a light analogy where when it was very expensive to make a candle and you had to make the wax and get the W and make it and put it together you’d have candles in your house but you wouldn’t have a lot of them well now today we have this problem of the exact opposite

46:13 have this problem of the exact opposite we have this electricity stuff and it’s so cheap to consume and now we have light we have this thing called light pollution now because we literally have so much of it that we’re polluting the area you can’t even see the stars because we’ve make so much of our own light here on the US or the world or whatever so it’s like that same concept if you want people to consume more of something make it a commodity make it so easy to use and I think of this I get I think all the companies are trying to do this now so I just saw a video the other day and this may have been out for a while I don’t know but Tableau public

46:47 a while I don’t know but Tableau public just announced a desktop installer that is now free of switching what now I think previous well you think about it right this is this is this is making it a commodity right nine years later well Microsoft pushed this button nine years ago making their desktop application free and again granted there’s a lot of limitations on this thing but like you’re seeing other visualization programs in order to keep up and not lose market share they’re trying to compete at the same level and

47:18 trying to compete at the same level and so now they’re also trying to commoditize the same thing that Microsoft is doing with powerbi so other companies are beginning to compete in this space so yeah I think it’s I think it’s very appropriate to say like look if you want to get people to use more stuff and Microsoft’s Advantage tier is if I get

47:37 Microsoft’s Advantage tier is if I get more companies to heavily rely upon this data coming out of these reports they will continue to buy month after month this tool this resource over and over again and as it becomes more of a commodity as it becomes more easier you’re going to continue needing a bigger premium sko you’re going to get more data you’re going to need to buy more capacity units so like the pricing model is genius here because they’re going to just keep making it easier and easier and easier to use because you got to just keep buying more and more capacity units to keep up with the demand of the higher amounts of

48:07 demand of the higher amounts of usage back to my point I think very early in the conversation here was well now we need to really evaluate what’s good stuff and what can we carve off and say that’s not good because it’s just becoming too much a commodity I I love I love talking to you guys gosh it’s just the highlight of my week so I think we looking back a lot so I’m actually really excited to ask this question there a little thought exercise pretty pretty straightforward I’m not going to do too much ad8 with the question even I’m already doing that right now anyways if we’re to push data

48:38 right now anyways if we’re to push data visualization forward and if you could choose one of the three what’s going to be the main factor that’s going to push data visualization forward for organizations and for people is it going to be the technology and as it rapidly involves better access to build reports on the web yada yada is it going to be the amount and the access to the right data not just data but more structured or is it going to be the people and their cognitive load more people will be viewing visuals thus more people have

49:10 viewing visuals thus more people have ability to understand visuals of those three you could pick one what’s going to be the major contributing factor to getting better data visualization moving forward in the future yeah the what where I’m struggling right for now for me is when you say the word better visualization I think I have to Define that first in order to answer your question so I’m going to say I’m going to measure the event I’m

49:41 say I’m going to measure the event I’m going to measure better visualizations by pure oh man I on one hand I want to do pure consumption numbers like I want to say better visual better usage of this is means more views right that’s what I’m thinking on one hand I’m like just use it more is better yes but I know that’s a very shortsighted answer and I would like to have a more elaborate answer of our organization if I if I think about my organization I want my organization to rely upon reports that produce value and

50:12 reports that produce value and ultimately produce better product or services on the output so we already yeah we already know we’ve done one of our previous episodes they actually do polls on data culture so let’s let’s use that as our measurement so if I’m trying to if if better reporting is increasing the value of data culture or using more of it in our organization I’m going to say it’s not the technology at this point I think it’s more I think the best move we can be doing is supporting our existing reporting with

50:42 supporting our existing reporting with easy to find and matching up the need the value for why this report exists to people answering their questions about the data I don’t think it’s I think it’s more of a people and education part of the challenge then it is actually technology driven at this point that’s what I’m going to go with we’ll allow it so I get two allows and one one question say what restate

51:12 and one one question say what restate your your question what forward what’s gonna Push It Forward people and their cognitive loan the technology Tech why I’m I’m intrigued you actually really said that so I was not well like ultimately like building building good visualization I think ultimately you’re you’re not going to get tons more people investing in understanding the intricacies of some of the visualizations eventually

51:42 of the visualizations eventually technolog is just going to I think get so simple that it’ll start using utilizing those guidelines that we harp on all the time to create better and good and valuable visualizations along with the appropriate cont text for people to digust so it’s it’s not amount like I don’t think it has anything to do with access to data either because it requires people to understand how to work with data and the vast majority of people don’t right so if if I’m going to pick one of those it’s where everybody’s

52:12 pick one of those it’s where everybody’s putting all their eggs in one basket right now with AI anyway eventually there’s going to be enough structure there’s there’s going to be enough structure there where technology is is doing the is removing the complexity of of of the the jobs that we have and it’ll do the same thing in visualization I honestly was not expecting that answer because I’m going to probably choose the the people and solely the people why why yeah oh if the technology

52:43 people why why yeah oh if the technology and our data current way we Access Data come stayed the same for the next five years but we actually taught an organization how and understanding how to look at data and consume it to me the more they know what data is doing the more they can ask the right questions they don’t know what the technology they can do right now right and we’re already trying to say the technolog is going to move forward and the structured data they don’t know those words I don’t need to tell my CFO what a semantic model is go forbid if I had say that

53:14 go forbid if I had say that word to him or her but if they have a better understanding I’ll smack the semantic model out of you Tom smack the semantic out of you yeah but if they have a better idea of what possible on the canvas to interact with it they’re going to help me they’re G to ask better questions than me they’re GNA have a better dialogue with the people building the report or building the visuals and this is we’re going to deal with this to me the same thing with AI is the AI is gonna get a ton better I think the guy from

53:44 get a ton better I think the guy from chat GPT just said listen we’re developing chat pt5 we’re embarrassed by chat pt4 he just said that so which is insane so we could barely get a handle I’m going off on a tangent but we’re we can barely get a handle on the technology now Outlook changed drastically now and everyone’s getting used to that M probably working on the next new new outlook and so people are always behind the technology can I get people a better language around data visualization not just the higher ups

54:15 visualization not just the higher ups and not just people building but across top down wide left right across the people who are utilizing their data to say I know where to access it and I know I’m looking at therefore I can ask a better question to my bi author or to the bi team or to my manag selfservice to say I see the data this way I would like to see it this way so so they can ask me better questions so that’s that’s where I put my eggs in that theoretical basket I like it I I think this is a

54:47 basket I like it I I think this is a good topic I don’t know we’re not gonna kick out the answer here at this point but time will tell we’ll see if set large language Model come out here soles the I’m gonna let your last comment just slide into an argument for another another podcast MEP I’ll put okay so nope I already wrote it [Laughter] down it’s a great closer though Tommy I’m just gonna be quiet now all right let’s wrap with some final

55:17 right let’s wrap with some final thoughts here about this article Tommy some your okay Seth’s already done his final thought tell final 100% with Seth all right good two final thoughts done I will say I think my final thought here is again I enjoy this topic I like this area I think this is a really good place to be in I think we are in a very interesting space where things are going to get easier and more commoditized it’s now going to be how do organizations wrestle with that what is self-service and what is Central bi how do we keep it

55:47 and what is Central bi how do we keep it to have quality those are going to be the challenge we’re going to struggle with so anyways with that I want to say thank you very much for listening to the podcast I hope this hour of time was worth your time you’re spent or if you’re running I hope you had a successful run and safe run wherever you’re doing we heard a lot of people run and do exercise through this podcast maybe we should do a podcast where all three of us are in treadmills and we’re just huffing and puffing through like we’ll actually participate on some activities here as opposed to just build your calculate

56:17 statement maybe they wouldn’t go over so well on on video so maybe we’ll pass on that one but anyways thank you so much we appreciate your listenership if you don’t mind if you like this podcast if you found some from this conversation please share with somebody else we’d love to get the word out more about what’s going on in the podcast Tommy where else can you find the podcast you can find us in apple and Spotify wherever you get your podcast make sure to subscribe and leave a rating it helps us out a ton do you have a question an idea or a topic that you want us to talk about do you disagree with something that was recently said

56:47 with something that was recently said head over to powerbi. com amm Central and join the conversation on all of power. social media channels excellent but that we’ll say thank you very much appreciate it and we’ll catch you next time

Thank You

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