As Dr. Phil says, “Never put more into a relationship than you can afford to lose.” Not sure what that has to do with Excel but it sounds vaguely wise, which is the whole point. Tim and Michael try to be your relationship coach for Microsoft Excel. Despised by data scientists, but used by everyone else, where are the boundaries and who has what it takes to enforce them. Join us in an exploration of our digital analytics love/hate affair with that most ubiquitous of analytics tools.
(Cell) references made in this episode include:
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[00:00:24] Hi everyone. Welcome to the digital analytics power hour.
[00:00:29] This is Episode 39. Talk to any good data scientist and eventually you’ll get their opinion on Microsoft Excel. It’s usually negative and doesn’t self deserve those slings and arrows.
[00:00:43] Or is Clippy just as useful today as he was. I can’t even get to the intro. Tim’s already laughing though is the question we’re going to talk about. What is the place for excel in the world or the tool box to the digital analytics professional as Clippy might ask. It looks like you’re attempting to listen to a podcast. Would you like some help with that.
[00:01:06] Because here is Tim Wilson senior partner at Lileks demystified and quite frankly one of those Excel gurus that you’ve been hearing about him actually the senior Xol correspondent just mystified. The direct like a correspondent and I am Michael Healthlink. And once upon a time I taught a class on Excel to some people. All right Tim should we just uninstall excel. Are we ready for that industry or does excel still have a place. And if so what is that place. It is hard for me to imagine a world where there is no excel where hating this topic at a point where I am highly conflicted.
[00:01:47] I think for one reason I think you may be conflicted some. I’ve been a longtime user of Excel. I have taught classes many times on Excel. A big proponent of it but at the same time I feel like I’m hitting a point where I see other tools that really can go beyond excel. I’ll say when I went Tablo was a little bit more in its nascent see and a lot of times people would say Oh to have so much more awesome than excel and then more often than not I would see what they would do. And actually this is still the case. There are people who just rave about Tablo and their output from it is I guess kind of underwhelming and we can kind of debate. I don’t know that we can debate but there are times where they say yes but it was so much faster and Tablo and now I come back and say yes but it’s so much less portable than that Tablo file to the 99 percent of the business users who won’t be able to see it outside of a PDAF and I will send my Excel file to every one of those who will be able to open it. So I think it has its place. Absolutely. I don’t see it going anywhere soon but at the same time I’m finding and as has been mentioned many times on this before as I’m spending the year exploring are there are lots of things I’m finding and are that I’m saying wow I couldn’t or wouldn’t even attempt this in itself would be such a nightmare.
[00:03:08] Even as a fairly sophisticated Excel user what do you think. Well no I’m I’m in the same boat.
[00:03:14] I think Excel gets use by default by so many businesses. In fact it always surprises me. Or maybe it doesn’t surprise me anymore but it used to surprise me a great deal. How many companies really big ones had so much of their operational capability tied up into some sort of business running Excel workbook. And if that thing ever cratered and disappeared like there would be big trouble a lot of important data and important data manipulation was happening and a lot of times what I feel like the main complaint is that people do tend to sort of push out past the boundary of what Excel maybe should be doing and attempt to do too much because Excel gives you it gives you avenues to go down you know can stuff in it to do statistics and it’s got stuff in it to do. Data visualizations has cast in it too. You know if you if you put some things in there like power pivot or power B.I or whatever. A lot of really powerful tools inside of it but it’s you start going out past what it’s really good at and certainly more recent versions of Excel have expanded its capabilities even more. You know I used to work in a world where you know we had the we had the luxury of being blocked it. What was it like.
[00:04:36] How many rows was it was the 10000. It went up to a million. It jumped to a million. It was 64000 64000. It was was it just sixty four. I thought it was in the thousands. No no no it was there was two to the whatever the 60 for the five six. Well it definitely comes through. I mean it was it was a huge jump when I went to a million.
[00:04:57] That tells you I’m not an Excel guru because I don’t remember that number off top of my head but it used to be back in the days when we would try to put a log file into Excel because you know why not.
[00:05:08] You can only guess how.
[00:05:12] I remember when they jump to a million and I actually took a logfile and threw it in. And I said Well is this going. Is this going to crater it that it’s a theoretical I will allow me to have those rose but in practice it’s not going to let me in and actually handled it pretty well. I was kind of heading a different way or thinking a different way when the companies that are. I’ve definitely seen the spreadsheets. There are these monsters. And there’s you know like one guy who knows how to update it and it’s kind of expanded and bloated over time more often than not though I tend to see that as the fragility tends to be because it wasn’t really built out with a plan. And you know what Anscombe it and the class that had a couple of months ago like when I talk about like building dashboards. Part of the core thing I talk about is having like a good structure and so that you can kind of extend it and it’s scalable. And I’ve seen a lot of those spreadsheets where it’s this massive like bloated thing and then you look at it and you’re right. But it’s also impossible to follow. There’s no organization. This is like it’s the equivalent of looking at somebody who just wrote shitty shitty code and somebody saying oh this programming language is terrible because this thing is you know fragile and bloated. It’s like no you built it wrong.
[00:06:28] Well and you know vb script is pretty terrible PBA.
[00:06:33] Yeah that. But. Well that’s maybe a good sixty five thousand five hundred thirty six. If my math is correct his number of rows that says I’m sitting I was thinking sitting with my HP 12 see what’s going to happen is when this is being edited the editor is going to google it and say that was dead wrong do we let them spew off oh yeah we’re totally going you know.
[00:06:56] Well and that’s that’s I think what it is is that Excel is really useful for some things. And honestly dashboards I feel like using Excel for dashboard is actually potentially great use of Excel depending on what’s in your dashboard and what you need to show.
[00:07:12] Well and that’s I think maybe part of that is excel whatever the version wherever they started and making it easier to pull in data from external sources. So obviously with report better for Adobe or for any of the shuffle point or super metrics or you name it for GA you can pull it in. But then also even linking to an DML to an SML you know you are Ehle and polling data and so you can pull in and refresh the data. And I agree. I think dashboards because of their portability and because I’ve built a couple of weeks ago just a simple little mini dashboard and I put on the part of what they wanted it was like the top 50 of X and I built this nifty little thing and I had it go on a PTF because it was just this nice little 2 page thing. And one of the requests came back in was hey can we get that in Excel because we want to build a copy and paste those top 50 out of there. So I’m like oh I get the report. But the simple report about a query on tab 2 is really what you want but when people want to be able to take data and put it somewhere else yeah there’s a downside to PDAF definitely. But I thought you were going to be is I am leaning towards are you. I feel like you have been doing exploration around Domo is that seems like kind of another Excel alternative right that’s kind of part of their pitch to get out of Excel get into a more powerful. Well
[00:08:33] and I think for businesses that are running like big chunks of their business in Excel getting out of that and sort of not a not being stuck with just one person who knows how this whole thing works and if they get hit by a bus. Our whole business goes with it and that’s where stuff like Domo can come in really handy. But again like with any technology I always look at it on a continuum in terms of your sophistication your capability whatever it is. And so as you kind of progress towards being able to maybe utilize this data more collaboratively across teams or something like that. Dan tools and systems like Duomo or sweet spot become way more compelling.
[00:09:16] One of the reasons why I mean like one of the things that you’ll hear like the from the sweet spot guys is just standardizing across these boyfriend sweet spot intelligence just to be clear you’re not talking about that sweet spot and you’re talking about the sweet spot intelligence. Sergio Maldonado world. Exactly.
[00:09:34] That’s right. You know standardizing across a lot of different groups is something that’s difficult to do with Excel because too many people can kind of manipulate all the things that are in there unless you really how locked down various pieces of it and so on and so forth and so a more single purpose tool like a sweet spot or Domo would be more useful for kind of curating those aspects of your data. So yeah. I think there’s multiple boundaries right. There’s the boundary. We talked about personal data limits. Right. Haddaway what’s the point or the boundary from Wango from Excel into something that’s better exploring bigger pieces of data. Then there’s the analysis side which you were talking about with our like when’s the what’s the frontier Axtell into deeper statistical tools and I think what’s the boundary from exile into better visualization or communication tools. So those are the kind of three main categories I think I just gave three main categories where if I said forward that the bonus category of where you work with Excel up to you get to that point of OK now I need to go and do something else. I think part Chaley too. There didn’t used to be options outside of Excel for a lot of companies you know in the last ten years we’ve seen a lot more options out there for people and now somebody is going to come tell me I’m super wrong about them but well although you think back to it you were talking about some of the control and the.
[00:11:05] So I worked at a place where certainly we used Excel but we had Cognos and we had powerplays. So we were building cubes and it was the B team was heavily involved in like what are the cubes and then lots who get access to the cubes. And that was kind of an environment where they could safely slice anything within that environment. And the cubes were being sourced from the warehouse. I still feel like a lot of times I’d get to something and they would copied and pasted into excel. But when you talk about those three or four however many buckets it is one where Excel has been around long enough and it is easy it is to beat up on Microsoft. They have steadily improved the maturity to do all of those right. Their data visualization has steadily gotten better and in some cases they’ve added functionality they shouldn’t be giving to people you know 3D cone graphs.
[00:11:59] Nothing tells a story like a 3D cone graph you know but from a storing the data like to be a little smart right when they get they go up to a million rows which I think was at least ten years ago at this point. When it comes to allowing the manipulation you know how can I share even putting statistical functions and you know the analysis tool pack. They sort of wisely said you’ve got it it’s free. You just have to know you have to be smart enough to go at it before you start clicking on stuff in your head explode. And I think it’s got kind of a lousy experience just like the query builder tool which still looks like it’s from like 1997. So yeah it’s one of those where it does. It’s the broadest but maybe not not all that deep but what do you say to people and maybe it is the data scientists as you said it up who say you know that tools.
[00:12:51] Yeah. Well and in fairness like I try look at it from both sides and I I definitely come from the business user a business analyst side. I’m not a data scientist so when I’ve heard people say that I’ve thought OK what is it from their perspective that makes excel so not a great tool to use. And I do think it has to do with flexibility and options. You know a data scientist is thinking and working very quickly through a number of different things. They need to be able to just very quickly take the data any direction they see it going without worrying about those boundaries. The other thing I think is that excel has been so entrenched that probably really smart data scientists have seen companies people business units whatever do you just really dumb stuff just so they can do it in excel as opposed to leveraging a much much better tool for that purpose for whatever that reason might be. And I think that probably builds a sense of frustration of why can’t we just use good tools or appropriate tools for the job that you’re trying to do. And I’m trying to think about last conversations I’ve had with people in the data science side of things and sort of what I remember hearing them say but I feel like that gets to probably where some of that frustration lies. It’s like I would never I’ve heard people say I would never willingly use Excel for anything. And those are the data scientist type people. Yeah yeah.
[00:14:21] And because like the things that they’re doing they can they have better ways of doing all those things with different tools but then then. But then my argument back is but yeah not everybody’s going to have the access and intelligence and training and training to work with all those tools. I can barely get my head around left outer join or something. Right. So you know then for me to be like you know conceptually had whooping it up that is not going to happen probably and that maybe that is from a iterating on the data.
[00:14:59] I think if some of the other tools that I’ve kind of crossed paths with you know Clementine from SPSS and if they bought it from somewhere it was kind of a visual laying out a sequence of doing things with data in that so it sort of had on the fly EDL but then also kind of you know manipulation of the data and that is one of those if you’re saying I start with the data and in situation A and I want to join with set B and I want to do this and do this and then I want to rapidly iterate through doing a bunch of stuff. You know once you’re in the analysis tool pack in using the solver it does feel like all of a sudden you’re working with a dialog box where you’ve got like eight things you can set. Now ninety nine and a half percent of the people using Excel don’t know what those eight fields mean. You know the residuals. What are you talking about. Which I don’t think is salver that’s progression. Maybe I don’t know just ordered a new book of statistics. I take my third and final run at it and then quit and go paint trees on PBS.
[00:15:57] Ooh. There’s a pretty cloud.
[00:16:03] Did you think of an example or even a type of example when you say people have seen companies do things that don’t make sense or that are a bad idea just because they could do it in excel.
[00:16:16] Well anytime you see companies pushing Excel out past sort of it’s natural boundaries you know whether that be trying to use it as a database trying to extend it out past kind of like where it should be from data sharing their data collaboration perspective using it. I mean any time you’re using it to Lake manually gather multiple sources of data just using it as the marketing calendar that everybody’s going to update the master bloated Excel file that that’s one of those the least favorites. I mean we get into Google sheathes search discovery and then for all collaborating at the same time it turns into a mess because usually it devolves very quickly into like people actually entering fields to try to make fun of whoever else is in there and or add in animated GIFs or something like that which Google Sheets is another interesting one that does feel like it is carved off if if Excel is trying to cover a very wide span and I do think there is. I
[00:17:20] still contend that there are times when people say you’re pushing Ixil too hard. And it’s like no you’re just pushing them the wrong way. To me is becoming very very stable platform. You know there was a time when it was just you know it’s about to speak corrupted and once it was corrected you’re fucked. Beck is in sheet’s started out as being this super simple like oh remember you know Lotus 1 2 3 you know Excel 1995 Excel 95. It was like it’s basically your rows and columns and you can put formulas on it. And because it had the collaborative ability it’s in the cloud it’s you’re not going to lose it because your hard drive crashes it sorta you know he started pulling from that lower end use of Excel and there are many many cases now where if I don’t have these heavy visualization needs Dell Yeah you know use ustedes. So it’s actually carved off to me a big chunk of what it is made a vast improvement on Excel can do. And I don’t know Excel has that kind of cloud based solution. Right.
[00:18:20] All the stuff they’ve been doing with SharePoint integrations and I don’t really even do I still operate with the individual files but it seems like they’ve kind of tried to head that off a little bit to be a little more collaborative and cloudy.
[00:19:02] I’m not good at either one. So let’s talk a little bit about some of the boundaries. So if someone’s listening.
[00:19:08] OK let’s let’s talk about data visualization and using that to communicate a story around data. We talked a little bit about dashboards. That’s one method of communicating data but there’s also an analysis there’s reporting where do you see the boundary between Yeah that’s good and you can keep using Excel for that or. All right. Let’s talk about other tools now we need to put you in a better spot. So you’re not you’re not kind of doing more harm than good.
[00:19:36] So I like that way to look at it. So visualization so dashboards because they’re inherently or even for reports that require some level of formatting that are going to live on and be updated refreshed on a daily weekly monthly basis.
[00:19:52] You know you can afford to put a lot of care into exactly how should this data be represented. And is it going to continue to work even if the data fluctuates when it comes to I’m presenting this Dedo one time I’ve done an analysis I’ve found my thing in let’s say that I found that in Excel I was crunching it and now I need to get a visual that I want to show you know ultimately it’s going to go in a presentation PowerPoint keynote whatever I feel like there’s it’s almost like half of the time. Excel it is be a horizontal bar chart. It’s going to show what I want. I can accept my one bar that highlighting the thing a drop in in your presentation. Maybe I draw an arrow or put an annotation next to it or as we speak it has slowly gotten me to realize that if I’m doing that a lot of times it makes more sense to use the native chart builder and PowerPoint because that’s basically excel under the hood and has it’s not as clunky as it used to be where I’m starting to waver a little bit when it comes to doing a Venn diagram and excel. You’re kind of shit out of luck. You can calculate how big things have to be but then you wind up really hacking stuff you know and even I’ve done. I feel like I’ve done sort of crazy things with bubble charts where I’m just kind of forcing circles to move around to arrange them how I want them just so I can copy and paste it.
[00:21:09] I have a sense that that’s the sort of thing that Tablo does way better and then even as I’ve been diving into are those are some things that I feel like oh with the R has a completely different paradigm for charting or the G.G. Patu package where it’s like forget everything you know about the basics of a chart and the chart types there’s really only one chart type and the way that you describe and define it. You can make anything and I haven’t fully internalized that language yet but it does get to you so much I think faster richer opportunities to say you’re not you’re not trying to make something of visualization. Nobody’s ever seen before. You still got to be using the language of lines and dots and circles and bars. But I think six months ago I would’ve said That’s bullshit. I can I can visualize anything I want to and Excel and I think I’m changing on that and maybe part of that is from the number of data visualization blogs and conversation going on and people point to things like I’ve never seen something visualize that way and then I think and that’s a really effective way to visualize it. I think I could never do that. So yeah.
[00:22:15] So it comes down to as your toolset expands and has your visualization capability expands. You start needing or wanting more ways than one cell gives you to present data.
[00:22:29] Yeah. So you know one thing Excel doesn’t do animation really. I mean it can I mean I Chandu dot org has all sorts of examples but yeah I remembered it a duty.
[00:22:39] Some juice analytics ones where you can use the offset function like tab through and update your you know cool little trickery and that that’s actually the thing is creative people can take and stretch excel and so many cool different ways and have have done right because necessity was the mother of invention. Have done some amazing things inside the confines of Excel and that’s also maybe why people get frustrated because it’s like why apply all that creativity here when you could apply it over here and get faster better results.
[00:23:10] And even if you being one of the people who has hacked it a lot waterfall charts are another one candidate. Oh yeah that’s all kind of thing famously Excel like you’ve got to go unpack all sorts of bar chart yet with no frills. I can do it but you can do it. You know I can I can say all day long. You know what. Because I know what I’m trying to do. I can do it pretty quickly and pretty efficiently. But come on like I’m inherently hacking something and experimenting and tweaking and gee if I had somewhere else that I could say I’m doing a waterfall chart. So let’s go with it.
[00:23:42] Yeah. Like the first three times you try to make a bullet char or something like that and Excel and it’s just been like Butchart going through all this pain.
[00:23:52] But yeah because there have been Bagpuss how to make a bullet chart and Excel and it quickly laid out for me to step at the same time along the AC line if you’re doing that if you’re doing a dashboard where you have 10 bullet charts you know it is one that if you do it right once you have it you know okay you put that extra hour into investment and once and that’s nothing you know six months or three months into it going out. But yeah and you made it portable. And I would say there is probably a goofy little benefit of you know analysts we want to be included in the conversations because that’s what we need to be and it has happened many times I’ve gotten roped into doing Excel classes because that’s what people really wanted to learn. They wanted to be more efficient because they would they would be doing something incredibly tedious they’d happen to ask me and I’d have it done in like two minutes. And they’re like oh my god. That’s very helpful.
[00:24:48] And so yes and it fell down like well.
[00:24:57] So it is a way for the analysts to get kind of. This is the analyst has telling me that the analyst can help you clarify your objectives and establish your eyes and help you with validate hypotheses all kind of squishy if it’s hey the analyst can’t help you not spend the next the entire day you know manually doing something annoying.
[00:25:19] And so there’s a way to get kind of in graces and have a instant kind of solid relationship and really helping a business user not necessarily running the business but giving them more hours in their day and they’re going to remember that and then they’re going to rember to come ask you the next time and the next time. And as long as they don’t think that’s all you do you’re somebody who can help them out. And there’s there’s value in that. If I tell them that yeah then you tell me exactly what they’d want so that I can set it up and pull it with our or Tablo and then I’ll send them a PTF and they’ve got to go into my queue. That’s not necessarily as helpful.
[00:25:53] All right. So let’s jump over into the analysis side of where’s the frontier. Can you use Excel for analysis or does it you know is your chlef where’s your cliff where people need to start thinking other tools here. I’ll start this one because your answer will be way better than mine so I got to get my licks in early. I’m starting to believe and and it might. You may be having an impact on me but I’d like to think that I’m just really intelligent. I’m starting to believe actually.
[00:26:27] And therefore you’re moving forward despite me having an impact on you.
[00:26:31] Well I’m just saying like you know the fact that you and I might agree on something along these lines should not be viewed as anything more than purely coincidental.
[00:26:43] There is no significance to this. Correlation is not causation emission.
[00:26:48] So I’m starting to believe more and more of that real analysis isn’t something that you do very much in Excel. I mean I’m all so so when I simplify analysis down to its basic fundamental thing it’s learning the difference between two things and more and more. Good analysis encapsulates the data at its lowest level not the data aggregated and exported from reporting tools like Adobe analytics and Google Analytics and so on and so the rise of tools that allow us to export the lowest level data event level data the hit level data and then do an analysis on those data sets. And if you look at where big Querrey fits into analytics 360 we look at where analysis workspace fits into Adobe analytics. This is the usage of something that hit level data to create better analysis capabilities excel. I think quickly runs out of room to be the right tool for analysis and I want to say are is better do.
[00:27:52] I mean it in essence it becomes a really good tool in the toolset because it can do good analysis at that point for that type of data or other types of analysis tools as well.
[00:28:05] Well so yeah I mean we wind up in the definition of what is analysis and if I say if we if we agree that analysis is validating hypothesis it kind of depends on. Yeah it’s the tale of two things. This is different than this and I can prove it with by these methods. So I feel like I have. So using excel as using it smartly and giving this gives gets a little to the discussion of giving business users enough data that they can play around with that without hurting themselves you know exporting a data set where you’ve got one way to get more granular data is to add more dimensions. So if you have a bunch of dimensions and you have a bunch of metrics and let’s not talk about users are unique visitors then you install you quickly get a larger data set more rows in your table and then you’ve got the ability with a pivot table to look at that a whole bunch of different ways and even with calculated fields. So I do think there are cases where enabling marketers to do self service analysis by thinking through and building out that kind of master flat table given them a pivot table giving them slicers giving them kind of visualizations tied to that that does enable some level of exploration that I’m sure the data scientist would say in analysis because that’s not applying any sort of statistical or just doing a modified comparison but those.
[00:29:33] Okay so I do love me a good pivot table that you that one took me back a step from where I started. So that’s good.
[00:29:42] But at the same time if I say Well gee now I’ve got that big flat thing and now want to take a one more level either.
[00:29:48] I want to take it one more level to super granularity or if I don’t want to rely on what I decide to slice and filter by I want to have this is not machine learning but this is I want a machine to I know what I’m looking for I’m looking for outliers when I look at this metric crank through all the different ways you can do this. To me that’s one example of where no Excel doesn’t do that real well. I think after our last I went back to I do have John Corman’s data smart book. I realize that it’s not a good book to have as an e-book because you’re supposed to be doing size so it’s not good bedtime reading. But he talks about you know salver as one of those things but I still feel like excel with those tools like solver is kind of constraining. You’re being given this very powerful tool to work in a very narrow situation you have to recognize it and then use it. And I feel like some of the other tools are a little more broad where you got a little more control over the number of inputs the number of outputs and you can kind of configure it more. But I am absolutely schizophrenia on this entire subject right now.
[00:30:56] Well and that I think it’s okay because actually a couple really good things I think popped out at me anyways and hopefully that will mean for a couple other people too. You know if you are a data scientist and you’ve made this or if you’re one of the two people listening to this podcast. Yeah. Okay so then the third one was around I guess data manipulation. So I think you just hit the boundaries of that when you run out of memory.
[00:31:19] I mean well no but I think you also hit it from a I mean data manipulation there’s the traceability part of it right. I could bring it into Excel and say I’m going to you know remove the outliers. I mean a sort by this and do this as soon as you start manipulating data it’s much harder unless you’ve written a macro to do it to have traceability.
[00:31:38] And I think that’s another these other tools that are out of an EDL and I feel like that also is part of what you’re doing as part of analysis too. So I feel like maybe it’s not so easy to break those two apart. But some of the similar points I think still apply.
[00:31:54] I mean I think that I’m so spinning like every free moment that I have like fucking around with are the this is helping me I’ll clarify some of this stuff that repeatability. Remember Tom Miller telling me this that the metrics that the metrics Boston I think he was like it’s repeatable stuff. And the way that you’re working on it you can do it where you’ve got no no audit trail but you pretty quickly learn that the way you should be doing this is in a way that you know you can go back and repeat. You’re keeping track of all the steps that you’ve followed and it’s not really great at that. You know you need to be diligently taking notes what you did with it and where you got the data. So right.
[00:32:34] I remember Eric Goldsmith Echosmith one on our episode had some similar points. So that’s and that is pretty important stuff. All right well let’s pivot this.
[00:32:47] Table this discussion and pivot to our last call.
[00:32:52] This is a portion of the show where Tim and Michael talk about things that they’re interested in that have happened lately in the world of analytics.
[00:32:58] So I go first. Yeah go for it. So I got a I’m going to give you the choice I can go with the I’ve got it I’ve got a very tactical tool free tool thing but I don’t want to wind up in a rut where I’m trying to do is coming up as a tactical tool last time I did.
[00:33:14] So there’s that or there’s the completely whimsical that is a stretch to say how close it is to analytics but it’s got it’s got some geeky in it. Let’s do that one. OK.
[00:33:24] So let me couch this by saying I in my life have read one graphic novel so I’m not a graphic novel guy. Not even really a comics guy but I’ve also think only wound up as a funder of one the Kickstarter project and those two come together and a graphic novel called geeks and Greeks.
[00:33:48] And it is it is a very entertaining light read. The guy who wrote it was sort of crossed paths with him he was about five five years older than me. He was in my fraternity at college but he graduated I think literally the year that I was going to show up so I don’t think we crossed paths. He’s had a name Steve Altice and he has been he’s been kind of a renaissance man. He was actually in Die Hard With a Vengeance is one of the German terrorists. So he had like an eye for a kind of fame. Yeah he has a B.S. in aeronautics and astronautics from MIT as well as a master’s a couple of master’s degrees and then he wound up as an actor. And I think he’s been like motivational speaker and writer. And so he had this idea for a graphic novel about the Greek system the fraternity system meets the nerd system loosely based on real life events at MIT when he was an undergrad and has this graphic novel and it’s if you search for geeks and Greeks it’s kind of a crappy little site that you can you can buy it. I got but I got it as part of my Kickstarter I got the eBook version and it was fun enough that I ordered the print version. Guy named Andy fish. And I think maybe his wife maybe illustrated it. But it’s fun and it’s a little bit of a gag. So it’s a nerd doing nerd things in a fraternity culture.
[00:35:13] So there you go. Yeah I think you’ve said enough such high on that whimsical.
[00:35:20] No that’s we all want the call to be whatever is interesting to you. Right. I recently finished it so and OK. Well you can go the other extreme. Well recently not too very long ago. Everyone’s probably heard about it now. But Google announced Firebase which is actually a way to build applications mobile applications. But in the middle of all that is an analytics platform or a brand new analytics platform. And that is very fascinating to me and I’m excited to see the ways that it will sort of overtake or be part of the mix in the mobile application analytics space. You know we’re doing more and more of that. And so I’m getting more involved and more excited about the potential for those kinds of things. So yeah I’m excited to see about it and I’m sure by the time this episode airs they’ll probably be some amazing stuff that have already happened to this couple months since the announcement now. All right so that’s my last call. All right well Tim I believe we saved Axelle today. So great job. But we also found out when not to use it.
[00:36:30] I think we found that it is not a it it’s not black and white. Anybody who wants to treat it that way.
[00:36:36] We would love to hear from you as well. I imagine that the rate I mean accuracies at least from my part of the podcast has been very high. And would like nothing more for all of our listeners to mention them on our Facebook page or on the measure slack or hell even go to iTunes and write or write us a review.
[00:36:57] Well maybe not after this show until we get a really cool guest to come on and go right through you on. But as always it’s a pleasure. Tim thanks for taking the time. We’d love to hear from you so drop us a line. And this is Michael Hubli saying keep analyzing and excel.
[00:37:20] Thanks for listening. And don’t forget to join the conversation on Facebook Twitter or measures like grit. We welcome your comments and questions. Facebook dot com slash analytics our analytics on Twitter. Chose they made up.
[00:37:40] Work. Yeah go look. Yeah with a lot of energy. OK. Take. Well. Like senior Ekso correspondent for The mystifying Daily Show action. In the your movie Jack London Jack London. He used to make these noises Oh yeah. Paranoid people follow me on Twitter. I gave it away. I’m an idiot. We don’t have to read. It yet if you’ve read this far probably just go ahead and shut it off. We’re not. Both sides. Still independent because they’re American. Save us. Save a horse ride a cowboy and save it. It’s the name of the song. They decide to get over themselves and not spit on it. Well they should be nice to me. That. You’re. Like you. Like down for.
[00:39:29] Red flag and Microsoft. Oh hold on one more rock flag and that table.
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