We are on site, Coalesce24.

I am sitting here with Scott from Brooklyn Data.

Scott, there's a lot of people who listen to this podcast who know who you are already.

Take a minute to just say hi and give a little bit of background.

Sure.

So I'm Scott.

I'm founder of Brooklyn Data.

We're a data consultancy that works with, let's say, companies all shapes and sizes to help them with their data strategy and then to implement that strategy.

And, you know, one of the tools we work with very often is dbt.

And I guess personally, I've been involved in the dbt community.

Oh, my God. 2016?

I mean, you are the dbt community.

I've had the pleasure of kind of, you know, knowing Tristan and the dbt gang for ages.

And it's just been a pleasure to watch it all grow.

And we're going to talk a lot more about your background.

Before I ask you my first question, I just wanted to do a little behind the scenes.

Both of us have been here all week.

This is Thursday, right?

I can't tell you.

I think it's Thursday.

We were both just talking about how our voices are like an octave lower than they normally are and because of the long week.

And it was really funny right there.

You and I have had a certain level of like end of conference energy.

And then I asked you this question, we're on air and you just you just did it.

And you like you brought the energy.

I'm like, OK, I will do it.

All right.

All right.

We're to rally.

That's good.

We haven't had a lot of sleep and I don't know what time zone or date is, but we'll rally.

OK, good.

I'm here with you.

So you have some some news to share that I think you've been talking with some some different folks about.

So I don't think we're going to break this live or anything, but but it is a little bit new information.

Do you want to get it out there?

I started Brooklyn Data in summer of twenty eighteen.

That is kind of crazy.

The number twenty two.

Yeah.

Something like that.

Yeah.

That seems all right.

Six years, six years, two months.

We grew rapidly.

I mean, I think big thanks to, you know, DBT and all the success the DBT community has had and build something really special.

And about a year and a half ago, we went to an acquisition we were acquired by Valir, which is an amazing digital agency based out of Boston.

And I couldn't have asked for a better home for Brooklyn Data.

And for the last year and a half, I've been working hard on integrating and making kind of any acquisition is like a marriage.

And I feel like I can do a whole podcast on just kind of integrations and acquisitions and everything I've learned.

But the story is the integration has gone great.

We're one company.

And as of kind of the end of this month, October, I'm going to be stepping back from the day to day.

So I'll still be a board member of Valir and Brooklyn Data.

I'm going to be involved in the strategy, big picture, all that kind of fun stuff, but kind of won't be doing any more hands on keyboard and not quite sure what's next.

No plans.

I mean, you know, my last day is, you know, end of October and the next day after that, I literally do not have a plan.

So I feel like I'm going to have to ask Tristan for some help on coming up with hobbies.

Yeah, I maybe I can help you just a tiny bit, but I'm not great at hobbies.

I don't remember the details of this, but when when you were at Casper, obviously, and I want to hear the whole history, but you were very involved in DBT and the DBT community, and then you started Brooklyn Data and and we kept in close touch.

At first, I was like, oh, like what's going to happen to DBT at Casper?

But that actually turned out to be totally fine.

But then I was like, OK, this is interesting.

At the time we were Fishtown Analytics, we were and you, a longtime friend and supporter, were now a competitor because, you know, you were also a professional services company.

But, you know, there's like this bond between the different people doing this very hard thing.

And so we stayed in touch.

And I seem to remember in the early days asking you, like how you were managing to be a husband, a new father and the start like the what did I say?

And well, and your answer was something like, I just don't sleep a lot.

And you said it a little bit with like crazed look in your eyes.

Can you talk about like, what did it take to get this thing off the ground?

Yeah, I think the answer is I didn't sleep a lot.

You hear the saying like it doesn't work if you love what you're doing.

And it's true.

I mean, the reason I have to find a hobby is because building Brooklyn Data has been a hobby.

It's been, you know, any free processor time I had on my mental CPU, I was thinking about new and innovative ways in Brooklyn Data, not because I was on the clock, not because I had to, but because I loved it.

And so the journey has been great.

We met when you were kind of, you know, working with us at Casper and helping us set up DBT.

And I felt kind of very privileged to be in the know on something that's like DBT.

It was special and cool.

And I told all my friends not because, you know, there was anything in it for me or I thought I'd start a business in it because DBT was awesome.

It was changing my life, changing my team's life and changing, you know, the data scene, especially in the New York data scene.

And so, you know, we had a lot of people asking us for advice because I think at that point we had probably one of the more sophisticated DBT setups back in, you know, 2017, 2018.

You'd already gone through some refactoring efforts then.

Yeah.

I remember the first time you had the DAG visualization.

And we were kind of you had to manually run it for us and it shook like it was like this.

Yeah.

Like this nest.

Before you could visualize the DAG, you just kind of built whatever.

You yellowed it.

And then all of a sudden you could see it.

And you're like, oh, yeah.

What did we do?

Man, it's like living in like a pigsty.

Then someone put some ice and you're like, oh, my God.

But yeah, then some people would ask me for questions and advice.

And I think there was a point where like, hey, I think there's a business here.

I think everyone, you know, very smart people are working on very cool pieces of software, DBT, Snowflake, you know, Looker at that time.

But, you know, there was a gap in professional services, people that could guide companies on this journey to get the most out of these tools.

Because the kind of classic consulting companies like had not really woken up.

Totally.

This.

And you couldn't just like show up to Accenture and say, like, help me build a modern data stack and move faster and all this stuff.

There's a whole crop of company.

You know, there's I think the original one was Dash 42.

That's right, too.

And super sharp.

For a little while, Das and Lucas and Nick were my like arch nemesis.

Really?

Well, just we were competing for all the very few deals that were out there.

And I can't believe that you at Casper ended up selecting us.

Anyway, it doesn't we don't have to get into all that.

But Das was out there.

Then we started and there were a couple like Montreal Data Co.

Yeah, Montreal Analytics is great.

Yeah, right.

And there's Serial and awesome.

There's Data Climber.

Do you remember anybody else from this?

I was catching up with Aaron yesterday.

Data Climber, Data Culture.

And there's a few different freelance folks.

But I think those were those were the usual suspects.

So it really was that these folks had gotten to see how to use this new set of tools ahead of where the market was.

I saw the light.

And everybody that I talked to at that time said, I think that there's another McKinsey to be built.

Yeah, I think you said that.

I think I said that multiple times to you.

And you're like, I don't know about that.

So now there's this kind of been this life cycle.

And I think every one of those companies has now joined a larger entity.

Yeah, I mean, Aaron Data Climber, you know, joined a larger company about, I know, six months ago and Montreal Analytics about a year, year and a half ago.

Yeah.

Do you think that the McKinsey of the modern data environment is just McKinsey?

Maybe.

Is there still like a great independent consultancy to be built out of this era of data?

I don't think there will be a pure play large scale data consultancy.

I think that's too narrow.

You need to be a broader.

You need to be a broader.

You need to go.

So there's a few things.

And the reason why I think you'll see that kind of Aaron and the rest of the gang ended up kind of joining forces with larger firms is you need scale.

And what's happened over the years is that the industry has just matured and you need scale for brand awareness to scale the investment systems and account management and sales teams and sponsoring conferences and all the things that, you know, when it was just me and my Brooklyn apartment coding, I couldn't have even imagined or afforded.

And so you need that scale.

And I'm a big believer that at least one of the reasons that Brooklyn Data and we chose to join Valeer, which is a digital agency, is you need multiple service lines, multiple complimentary service lines because data work by its very nature will ebb and flow.

You know, not every organization is going to refactor their data warehouse every single year.

And don't get me wrong.

We have these kind of long, durable, amazing relationships with our clients.

It typically starts with kind of a bigger project than it evolved to kind of other different projects.

And for many, many of our clients, we have a long, durable, you know, similar size relationship for many years.

And I think the best way to kind of keep those long, durable relationships is to take that trust that you have built with this client, with this kind of, you know, your stakeholder, with this organization and help them with other stuff, help them with other stuff.

Yeah.

And it's you've got their trust, you know, their organization, you're not doing a cold start.

In fact, you know, the beautiful thing about data is it plugs into everything.

And so we're already working with the marketing team.

So we're already working with the supply chain team.

So why not help them with other things?

Yeah, it is so interesting.

You know, I started my career at Deloitte and I've now gotten to see things on the other side, partnering with lots of the largest consulting organizations in the world.

And it really does seem like the biggest competitive mode that you can have is those like partner relationships with the business stakeholders.

You got that.

The trust and the context is just not replicable without like years and years of relationship building.

People buy from people.

It's with any product people buy from people, but with services, the people are the product.

So it's like doubly true.

And, you know, I've tried to kind of reinforce to my colleagues at Brooklyn Data that we're somewhat in the hospitality business, you know, we're in the surprise and delight business.

We're in the kind of really, you know, listen and read behind the lines, give people what they want and give them what they need.

You know, it isn't as I'm sure there are organizations that, hey, here's a spec, we'll build it.

But I think truly successful consultancies that we built at Brooklyn Data are empathetic, have these great relationships and are, like you said, partners.

Not it's, you know, listen, at the end of the day, there is going to be a transactional relationship to any third party consultancy, but it should feel as much like a partnership as possible.

And I think we've done that.

A lot of our clients call us like the consultancy that doesn't feel like a consultancy.

And I think that is the compliment.

Yeah.

Let's go back in time a little bit.

Your story and I don't I don't actually know that your full professional story and I want to get it out of you.

But I think that you are a little bit emblematic of like the data practitioner of a particular era.

I think that's very true.

You like started as an econ person, right?

Well, yes, I started.

I studied business.

I did management consulting, kind of like you, strategy consulting for four years, Excel, PowerPoint.

And it was very quantitative, very quantitative, but no sequel, no little VBA, record a macro, that kind of stuff.

But that's as technical as it got.

You built like models to forecast economic things and economic things, revenue, financials.

You know, I remember having, you know, waking up at two in the morning early in my career with Excel nightmares.

I feel like anybody that's done that and just now I look back and I see the testing and all the version control that you have in data.