This is episode number 682 with Mikko Yuck, host of the Analytics on Fire podcast.
Welcome back to the Super Data Science podcast.
Today I'm lucky to be joined by Mikko Yuck, a straight shooter who pulls absolutely no
punches in her assessment of, well, of anything, but particularly about vendors in the data
analytics space.
Mikko is host of the popular Analytics on Fire podcast which has a cult following.
She co-founded the BI brains group and analytics consulting and solutions company that has
taught over 15,000 students analytics, visualization and data storytelling courses, including at
major multinationals like Nestle, FedEx and Procter and Gamble.
She authored the data visualization for Dummy's book and is a sought after keynote speaker
and TV news commentator.
In this episode, Mikko details her BI business intelligence and analytics framework that
persuades executives with data storytelling.
She fills us in on what the top BI tools are on the market today and the BI trends she's
observed that could predict the most popular BI tools of becoming years.
All right, let's jump right into our conversation.
Mikko, welcome to the Super Data Science podcast.
I've been trying to get you on the show for ages and now you're finally here.
Where in the world are you calling in from?
I'm from Atlanta, Georgia.
I've never been to Atlanta, but I've heard good things.
Yeah, I mean, we have a lot going on here.
I don't know if you saw recently got the FIFA and Olympics coming here.
So like, construction is in and traffic is insanity.
Not that we need more, but like we got awarded votes.
So it's in the wrong code here.
It's the longest commute in America.
Oh, so I'm like you, like we're talking before the show.
I live on one road and I just go back and forth.
I, you know, in Atlanta, you have to do it for your sanity.
Yeah.
So I had, do you recommend it to me as a guest by several people?
And I think the last person of at least three people that recommended you was Kate
Strashney, who's a wonderful person in the data community.
And so on the third recommendation, I was like, all right, we're doing this right away.
And then it took a while to get you booked.
You're a very tough, a very hot ticket in town down in Atlanta, but we've now finally
pulled it off and you're here.
So you're the host of the analytics on fire podcast.
It's, it has been, and it may even be still today, the number one podcast in analytics.
You are in the top 2% globally across all podcasts, including like all the mainstream
podcasts out there, which is wild.
And you have somewhat of a cult following.
So I understand you can tell us a bit more about this, but when you go to conferences,
you have people coming up to you.
Yeah, tell us about it.
Yeah.
So I like sunfire is a cult.
It's no longer a podcast.
That's what we call it a cult.
And because I will go to conferences and because we didn't produce like teachers and
cops, people will print their own things, come up and be like, Hey, Nico, like I've been
watching you for like how many years and I have my cup with me because I knew you were
here or the two shirts or like, you know, I have people that will like walk up and many
times and be like, Oh, when I started my job, your podcast was mandatory to my job.
So you know, because we're like your podcast, we're like, you know, educational week, bring
in leaders, taught leaders like yourself and they talk about topics that are relevant
that can really help people.
So the whole premise of it is that we do no BS.
So there's no fluff on our podcast.
We tell it as a is good and bad.
So I think people appreciate that, you know, there's no marketing.
Yeah, you are famously no BS.
That's one thing that I know about your future.
Yeah.
So speaking of educational, you also co-founded an organization called BI brains like business
intelligent business intelligence brains, but the brains has a Z on the end or Z depending
on where you are in the world.
Yeah, we'll talk about the jerk off that wouldn't sell us the one with the S because
he's known.
Okay, I see.
What a job.
All right.
As or not, BI brains has been a big hit.
You've had 15,000 students use some kind of education from the platform.
So you have online students, but also in person trainings.
And so you've had seven figure revenue for the online course alone, eight figure revenue,
if you include the other kinds of training.
It's all day.
Yep.
Yeah, consulting.
And so I understand that a big part of what the I brains teaches is your bids framework.
This is the BIDS framework, which is the BI slash analytics data storytelling framework.
And so the idea here is it's a framework for allowing data storytelling data visualization
to persuade decision makers, right?
All right.
So I started off as a consultant and enterprise quickly rose up to top 1%.
I worked in New York.
I think I told you that on 42nd or second quickly became like top 1% in the world in
that field and then realized that like I went through so much that I wanted to help other
people and enterprises basically go through what I didn't go through.
And so I actually developed a framework to help people that were like me.
Then it would become such a hit.
Let's be honest.
Like I put it out there and I was like, oh, you know, I'm going to put it out there.
And before, you know, community and all this stuff and then, you know, who knew there were
so many people like me that were really struggling with this, you know, just we were, we had
data visualizations, we had reports, but it's like, how do you tell the story?
Like, how do I get John to make a decision?
Because putting a chart in front of John is not working, right?
And so crafting that story and created the framework around that, particularly for enterprises,
where there's all these complexities and the Pumicee and all that stuff, that became a
hit.
So it was, you know, it was even surprising for us to be honest.
Yeah.
Tell us about the framework.
Break it down for us.
Yeah.
So without advertising, it's very straightforward.
So one of the things I noticed, John, and you'll appreciate this, because, you know, you're
in a decision-making role, right?
You're an executive is that a lot of times, you know, when you come to need a report in,
people tend to focus on two things, right?
They focus on the data and they focus on the medium, the output, whether it's the visualization
of the report.
What I tend to realize and what I learned was before you get to all that stuff of visual
and data, you actually need to understand what the hell the person wants.
And so what I did is I created a framework on three tenants, which is the first one is
what you ask.
So when you're working with someone, what are the exact type of questions you need to
ask and not ask, then it's what you write.
So the second part is about actually how to storyboard and we've created our own storyboard
and then it's what to visualize or draw, right?
So then it's what, how do you express and communicate that?
So we kind of went backwards, but that was again just based on my experience consulting
with Fortune 500 companies around the world.
And that has been a hit.
We've had multiple companies adopted from Shell, Ericsson, to Nestle.
You name it across the globe.
They've brought it in, you know, a lot of time we get data leaders or BI leaders that
will bring it in adopted and it works with any BI tool.
So we're too like that stick.
Oh, gotcha.
So some people, I guess kind of the big kind of tools in the BI space are Tableau, Power
BI, correct.
That's about correct.
And so with us, it doesn't matter, right?
I mean, the reality is that you noticed on all these tools have a bar chart, right?
Now, you know, one of them, it take two clicks to get a bar chart, another one, it take
three clicks, but you know, they all have a bar chart.
And so we stayed away from the tool and we focus on the framework and whatever output
you have, you can actually build in any tool that you want because you notice the tool,
the tool is like the Fortune 500, right?
It comes and goes.
I mean, in the next three years, it's all going to change again, right?
It was Tableau, yes, first it was business objects, then Tableau knows Power BI.
Two to three years from now, it'll be, you name it.
You know, so it was very smart for us at the Hook and the Tool because I think tools come
and go, but you've got to have the foundational knowledge.
Nice.
Do you have, from your perspective there, do you have any insights for us on to what the
next tool might be?
Yeah.
So I have some thoughts.
I get access.
That's actually the number one question I get asked.
Oh, really?
I was like, I got such a smart question.
I've had no one.
Oh, but I used to never answer it across the world.
It's literally, I'd be in these keynotes.
I'd be at these customer events, like at the vendor event, and they're like, Mika, what
totally you prefer?
I'm like, oh, I'm like, well, it's not the tool of the vendor.
I'm speaking out so...
Right?
So I was like, I'm feeling, I'm feeling the fifth, but I don't know.
I have some hope but thoughts, but I think they're doing some super cool stuff.
They're kind of ahead in NLP and kind of how they approach it.
There's some containers up and coming.
You know, there's this headless BI concept.
No, companies like Good Data, my good friend Ryan Dolly works there.
So there's some stuff that I don't know.
I think Parbia is going to be the king of the land or queen for at least another three
to four years solid.
I just don't see anybody that's close enough.
And I think Tableau is going in a different direction.
So if anybody may be a thought spot, maybe, maybe a good data.
So I have a few questions coming out of this.
So first of all, what is headless BI?
What does that mean?
Okay.
So I know you've heard about Reversity.
Yeah, but maybe you can break it down for our listeners.
Okay.
Well, I am no specialist in Reversity.
But I could tell you what it is only because I know the two companies very well that do
it, which is high-touch or size census.
I think you've heard about the doors.
So essentially Reversity, what ETL used to be was you would have to take the data and
get it into one place, right?
And then when you get it in one place, you would do all this stuff data and then you
could use it.
Reversity is the opposite.
Reversity is, you know what?
We're not taking the data in one place.
We're going to put everything.
We're going to take all the data sources and let you kind of pull from them, pull it together,
pull from them as needed and do what you need to do.
So essentially what it does is it kind of eliminates this kind of single source or
a truth.
I live through the data warehouse era.
I hate to eat myself, right?
And I call it the data warehouse era, the Lord of the Rings.
Why did I call it this?
Why did I call it the Lord of the Rings?
You remember the Ring and Lord of the Rings?
It was the precious.
That is what a data warehouse is.
Do you remember how he went down the dark panel to try to get it?
He never came.
I see, I see.
You get it, right?
So I would look through the data warehouse era where everybody wanted a single source
of the truth.
And so it's kind of funny today to see that they're like, you know what?
The hell with that.
Stop it.
You no longer want that.
Just give us our data.
And so I think all of that, it has bread stuff like reverse ETL and quote unquote headless
BI, right?
So a company like Good Data, and I hope I get it right, right?
And explain it to me.
They're not focused on having an encompassing like a poor BI tool where they then hold
your data and then you have the visual end, right?
They're focused on allowing you to take the data and you can actually connect it to any
tool that you want, right?
So it's a headless BI.
It doesn't have its own quote unquote face, like a poor BI or Tableau.
Does that make sense?
Gotcha.
Gotcha.
So it's kind of more like an API than a UI.
That's exactly correct.
And don't get me wrong, they do have a visualization element or element to report on, but you don't
have to use it.
So they allow people with all these different data sources to kind of be a bit more free,
I guess heterogeneous in terms of their approach in how they want to visualize, right?
I think it's a result of the field data lakes.
It's a different discussion.
It's a result of the data lakes that everybody wanted like five years ago to fail.
Yeah.
Yeah.
Right.
So now we're headless.
We're like, have those BI.
So yeah.
All right.
Pretty animated there.
All right.
I'm going on a run.
I've been doing this for a while.
So what is it about Power BI that makes it the default choice today?
So it's not a great tool.
Okay.
Power BI is not a great tool.
I just, and forgive me, Lord, I have so many friends that Microsoft.
That must be the first Microsoft tool that people don't like.
Right.
Yeah.
Okay.
I don't have any, I'm like, if people haven't figured this out from the show, I don't have
any Microsoft software anywhere.
Okay.
I'm Apple girl.
So I think I have Microsoft on my desktop, granted, but the licensing is always an issue
because they can never get it right.
But anyway, so Power BI is not a great tool.
The power of Power BI is the fact that you get everything that comes with it, like Azure.
Right.
So I think what, what they have done though is that they've allowed Power BI to show up
in Office 365 where anybody can download it.
But it's a visualization tool coming from like a sophisticated tool like business topics
of how low like I did.
Power BI is like, chump change, baby change.
So, you know, I love Microsoft.
Oh God, let me help you.
Microsoft people, I love you.
I was a Microsoft R.D.
and a part of this.
I need to put it out there.
They do amazing research.
They actually publish more than any of the other big tech companies.
Well, I call them the Mercedes Benz of, of, of our industry, right?
Mercedes Benz has more patents than anybody else.
So I consider them to be, but what is good about Power BI is Microsoft, Microsoft innovation
cycle and the way that they're innovating.
That's why I would get Power BI, not because the tool is great because they are not stopping.
You know, you could see how quickly they jumped into Open AI.
I mean, they were on it before the thing got hot, you know, so I think with Power BI,
what you see is people see that Microsoft is leading as a company and they realize, hey,
this tool, one isn't going to disappear and it's going to continue to evolve.
Gotcha.
So it's, it's the queen because Microsoft evolves so quickly.
They integrate things so quickly and it also gives you great connectivity with Azure.
Yeah, like take an example, the Python thing.
Microsoft bought R, the Power BI team saw Python was running.
Yeah, they bought, they bought R.
They bought R.
I believe so, yeah.
Yeah, I think they, I think they, they bought R, they did a stick in it.
They identified that Python was, Python was hot and even though R was a big investment,
they just, they just opened the door to Python.
You know, they, they are, they are very forward thinking.
Oh, yeah.
I see.
Yeah.
So Microsoft acquired revolution analytics.
Correct.
In 2015.
And yeah, graduation was a commercial provider of R software.
Yeah, yeah, yeah.
Correct.
Right.
And so think about that.
They made this big investment and because they thought that was the way forward.
Again, they were ahead of their time, saw Python pick up and I was there when, you know,
when that decision was made and they said, you know what, investment or not, we're open
to the work of Python.
And so part of the I fully works with Python.
And so, you know, that level of thinking where you're willing to be heterogeneous and even
cannibalize your own products, that's a company that's going to thrive.
So I guess with how big they are, they're going to have to be cannibalizing.
Correct.
Borturing.
cannibalizing.
Cannibalizing.
They're going to have to cannibalize something because they've got tentacles in everything.
In everything.
Correct.
Yeah.
So I think that's the way that the
process is a winning, they're winning all around and I don't see that stopping anytime
soon.
I mean, you know, you have sales force, you have Google with looker.
You know, one point I thought looker was going to be up there.
Google acquired them.
You have to have low sales force acquired them.
I mean, what do we really have left?
You know, I don't know if that's going to get acquired.
You know, micro strategy has been hanging around.
No one will buy it because of the extra CEO.
So yeah, it's, you know, it's, it's, it's, it's, could I not say that on this part?
No, I'm glad that it's awesome to have you be so open about.
Yeah, I try to, I guess I'm too diplomatic, maybe too much of the time.
I should take, I should take another do book.
I love it.
I'm really.
Oh, you didn't see my last post telling people say and I were.
Oh, yeah.
I was like, what viral you didn't see it.
Yeah.
I posted something controversial and I lost like 150 followers, like within hours and they
were all like the top viewers were CEOs, founders, directors, executives.
And I said, say in our and he went.
Oh, my goodness.
That's what I mean.
After the pandemic, like life is, you know, it just, it's got to be me.
Um, well, it's great to have that on this show.
Thank you, Mika.
Um, yeah.
So F.W.C.E.O.
Michael, I mean, he's my concealer.
Like he's all Bitcoin also, you know, it's, if you want to get it, you know, it's, it's
like you want to do Bitcoin, you can invest in Mika Shatterty.
Okay.
Yeah.
So this is all news to me.
But, uh, okay.
So we've talked about the frameworks, uh, sorry, we've talked about these different
BI tools and gotten your great insights on them.
I actually dragged you over here on a tangent.
What we were talking about was your state, your bids framework, uh, BI and analytics,
data storytelling framework.
And so you were telling us about it.
You were saying that you break things up into three categories of questions.
And so there was what kinds of questions to ask.
And then there's how do you visually communicate and I didn't catch what the third one was.
And it's what are you right?
So we go from asking questions, taking the answers and putting this storyboard.
So that's the written part.
And then we take that and we visualize and communicate it because what I found, what
I found in your New York, right, John?
Yeah.
Okay.
So you know, in your code, it's a tough code.
It's, it's, I started my career in New York and I got my handed to me every day.
It was like clockwork.
I got, I went to work, got my handed to me, went back home, looked at it, cried, went
back to work, but it handed to me again.
Right.
Um, and so, and so what I learned, what I quickly learned in New York taught me that
lesson was that I was asking the wrong questions.
So I would open my mouth and it would be like, begin, like, again, lorded a ring.
It's like, it would just like open the door to all these crazy responses that I couldn't
control.
What I learned was I break the framework, going into specific questions that you asked to get
the right answers.
So that was, that was a big start at the point of how you actually get the conversation under
control.
Nice.
Um, so I mentioned how you are, are you were a co-founder, I guess you, I guess you're
co-founder, somebody's co-founder forever.
It's present tense.
You are a co-founder of the, the BI branch group.
It does the education around this framework, uh, and that has all these students and seven
figure, you're amazing.
But that no longer is your focus.
And actually your most recent role was at count as their chief data evangelist, but you're
also, you've stepped back, uh, from that for the most part, you're just doing a little
bit of advice for you.
Did it by year?
Yeah.
Correct.
Yeah.
And, uh, so now you're looking for your next big thing, at least at the time of recording.
Yes.
And so yeah, tell us about that search.
I know from a post that you recently made, I'm going to include this, a link to this
post in the show notes, but you mentioned how, uh, when you scroll through your news feed
and you see who's being affected by layoffs, it has to be, uh, disproportionately affecting
some groups.
Correct.
Yeah.
So this is again, not to me, like, so just so we're clear, count is amazing.
Um, I was not treated in any way discriminatory.
I need to put that out there because then people wrote me and said, what did count do
you?
I'm like, count did nothing.
My RCO is amazing.
I was treated amazingly, but this is just my observation.
And I've been watching it now for months.
So if you go to tech layoffs, anytime you see tech, like Shopify layoffs or not the
product, any company, just any of them, just roll down.
And what you mostly see is either women, older people, or just minorities as a whole.
Okay.
And so I, I've been tracking this and I kind of started, I looked at it and I said, well,
you know what, this is not conclusive, right?
I was a data scientist.
So I'm like, you can't just look at a LinkedIn.
Maybe women are more expressive, you know, and maybe they just go online and post.
So I decided to start to speak to people.
And unfortunately, behind the scenes, I had gentlemen, white males confirming to me that
hey, something does look a little stinky, you know, in multiple companies.
And I said, well, you know, like what's going on?
And they said, well, there's so much happening.
Like it's happening so fast, you only could see it after the fact.
But I did actually go back in and confirm through a few companies with no names at all
that like, you know, some people are watching this going, hey, this is a little stinky.
Like, why do we get rid of the women on maternity and why we get rid of all, you know what
I mean?
So there is some discrimination going, you know, I had multiple women tell me, yeah,
I'm, you know, 35 or 38 or 45 and all that's left is a 20 year old women.
I have, I've heard that multiple times, you know, or I had gentlemen tell me that they're
like, yeah, I have all this experience, you know, and all that's left is one set of age
because of good examples.
So I'm, again, not conclusive until you have the data.
I was a data scientist, so I'm sensitive to that.
I understand that, but it's very visual and it tells a lot.
And so, you know, there's definitely something happening.
And I think my biggest fear is that we're, you know, three, four years from now going
to look exactly how we look before like we're reversing, you know, and so it's just a big
fear, but I went viral.
Yeah, I just, I just put it out there because I was trying to call out to say, hey, if you're
reading this and then I got a bunch of private VMs of gentlemen telling me, you know, hey,
Michael, what you do matters and, you know, thank you for pointing this out.
But you don't want to be public, but, you know, they're like, what you do matters, you
should just know that what you do matters.
Don't lose your voice, what you do matters.
So I know that if it's saved one minority in any category, whether it's gender, ethnicity,
race or age, it was worth the loss of followers, you know.
Yeah, I am aware of at least one big tech company that in layoffs was, I think there's
a lot of constraints against letting people go when they're in maternity leave.
Right.
But so something that they were doing was people who had been approved for maternity
leave say to start next week.
That's correct.
And that's wild.
And they just sabotage it.
But no, I spoke to women that were at home with their babies.
I mean, they've got the acts.
I mean, this is what I got the acts.
Like they were scheduled to come back to work next week or dada dada and they just told
them don't bother to come back.
You know, so, you know, don't get me wrong.
Like I, I'm not saying again, without conclusive data, we're data people, we got to be careful
that it's maybe it's only visible, the people who type of people who post, but it, you know,
walk into people, I got a good perspective that, yeah, there's a little smelly stuff
for it, you know, that supposedly it's random, but it just keeps all looking the same.
Yeah.
Well, so there's a good project out there, maybe for a listener where something that I've
said on air before is that, you know, if you're looking for maybe your first data analytics
job or your first data science job, having your own portfolio of research on some independently
on some project that you independently conceived of.
So good.
So this could potentially be one where I agree with this problem and see whether this is
in fact, you know, something that you can, that bears out in the data.
And yeah, if that is the case, then please tag me, go and me in a post about that.
Yeah.
So anyway, so that was just something that I saw again, not hopefully not necessarily
affecting me, though I did have an interest in experience, but yeah, I'm out there looking
for my next opportunity.
I'm interested in helping to build communities.
I'm very, I'm very, um, gone up by how big he got on Slack.
You know, that was very exciting for me.
So I'm pretty excited, you know, not to develop our advocate because I'm not as technical
anymore, but anything like drives community events, engagement, that's kind of where my
sweet spot is.
I'm a community like you, or I'm with your person, community person, right?
Well, no doubt.
I like to build a cult.
Yeah.
You're going to find an amazing cult to lead next alongside the cult that you continue
to lead the AOF fam analytics and fire fam cult.
After I just defamed like five companies on the program, but yeah, that's fine.
I mean, it's going to be every company.
So Miko, this has been a really fun episode of course, and we've also learned some great
perspective on the BI and analytics landscape.
So before I let my guests go, I always asked them for a book recommendation.
Yeah.
So this is definitely not your typical data book.
There's actually two books that I like.
The first one is The Richest Man in Babylon.
It's by George Claisen.
It is epic.
I heard it first by it was recommended by Noah Keehan from Atsumo.
I'm assuming you're familiar with Atsumo.
And he recommended it.
And so I took it and I did the audio version, which, you know, audio books are always weird
depending on our reader.
It's such a good book.
It's kind of like, some dog millionaire style, but the lessons that are learned are amazing.
And if you put like that book, one of my other favorite books I'm reading right now is The
Psychology of Money.
Those are both like epic books.
Psychology of Mind?
Of Money.
Of Money.
It's epic.
Yeah.
So those are both, you know, and so much more than money, obviously, I know they both talk
about wealth, but the way and the style of the books are written, it's so much more deeper
than, you know, just financials, right?
It's just overall my sake because, you know, financial wealth is a journey, right?
It's not a marathon.
It's not a silver bullet.
So those are two books I recommend.
Nice.
Very cool.
Great, practical and economical tips for our audience there.
Thank you, Miko.
All right.
So I imagine there are lots of listeners out there who want to be able to follow you
after this episode and get more real talk.
Except the vendors.
What's good?
What's bad?
No punches held back.
So obviously your analytics on fire podcast is a way for them to go.
How else can they follow you?
Yeah, so most people follow me on LinkedIn.
It's pretty easy.
Miko Yuck, M-I-C-O-Y-U-K.
And then recently I opened up my Instagram account.
I'll be doing more on there.
So feel free to follow me.
And as you know, I'm getting ready to start my YouTube channel.
So any of those channels will be great as a free.
I do a lot on Instagram on LinkedIn, but YouTube is next.
Nice.
We'll be sure to include links to all of those in the show notes.
Miko, thank you for finally being on the show.
It has been an absolute hoot to have you on and hopefully it won't be too long before
we can get you on again.
Yeah.
All right.
Well, hopefully you don't have any sponsors to get pissed off, but yeah, I'll be happy
to come back.
Thank you so much, John.
Thanks, Miko.
What a switched on person.
Miko is about the analytics industry.
In today's episode, she covered her bids BI data storytelling framework for persuading
decision makers.
She talked about how Microsoft Power BI is the queen of analytics today while ThoughtSpot
could be the heiress.
And she filled us in on how headless BI tools like good data allow for reverse ETL.
That's extract, transform and load operations.
All right.
That's it for today's episode.
Until next time, keep on rocking it out there, folks.
And I'm looking forward to enjoying another round of the Super Data Science podcast with
you very soon.
Yeah.
Yeah.
Yeah.
Yeah.
Yeah.
Yeah.
Yeah.
Yeah.