Hello, everyone, and welcome to the ThoughtWorks podcast.

My name is Mike Mason.

And I'm another of your regular host, Neil Ford.

And we're joined today by two of our colleagues.

I'll let them introduce themselves.

I'm Ken Collier.

I'm the head of data science and data engineering at ThoughtWorks. Hi introduce themselves. I'm Ken Collier. I'm the head of data science

and data engineering at ThoughtWorks. Hi, everyone. I'm Jamek DeHanee, and I'm a technical principal

at ThoughtWorks from San Francisco. And of course, you might recognize Shemak as one of the hosts

of the podcast, but in fact, today we have her as a guest, so we're going to be picking her brains.

That's right. We're into one of her areas of domain expertise, and so we're going to be talking

today about data and data architecture, and in particular, the ideas around what's the next

generation architecture beyond the data lake. So many of you may be familiar with the concept of

data lake that Martin Fowler writes be familiar with the concept of data lake that

Martin Fowler writes about in his website, but we've been doing some thinking about what goes

beyond that, and that's what Ken and Jemacher here to talk about. Thank you for having us.

So what's the problem we're trying to address here? Well, so data, I'll jump in a little bit because I'm an old guy who goes way back in data.

Data management and data architectures have largely been a centralized focus.

So from enterprise data warehousing to even data marts and and Kimball style architectures.

We've continued to focus on centralizing data.

In about 2009, James Dixon introduced the concept of Data Lake, which captured everyone's

attention and got everybody's imagination working,

...