A conversation between Colin Zima and Jordan Tigani about building Looker and Google Cloud BigQuery — and why they're building the next generation of data tools at Omni and MotherDuck.
Editorial note: This blog is based on a recent chat between the Omni and MotherDuck co-founders on the past, present, and future of the data stack.
Jordan’s decision to become an entrepreneur came after more than a decade at BigQuery followed by two years at SingleStore. “We had some of the biggest companies and data warehouses in the world using BigQuery, but the stuff people actually queried tended to be much, much smaller,” recalls Jordan. “I thought: ‘If everyone is chasing the few customers that are using really large data, there have to be opportunities to build something for everyone else.
"The core thesis of the governed data model and centralized BI persisted throughout the Looker experience, and we couldn’t just go and undo that because it’s what customers came to us for. But I always wanted a product that could compromise between centralized and decentralized BI, and it felt like a big gap in the market. That was the thesis for Omni from day one, and it’s exactly what we built."I think it’s the innovator’s dilemma here too.
One of the reasons we’re focusing on simplicity and ease of use is because customers will come to us and say, “I have this messy CSV file that has all these problems, and I need to make sense of it and then join it with the data in my warehouse.” That ends up being the kind of thing you can spend a lot of time on. We want to make that easy because asking the question is much easier once that first part is done.
I feel like databases are always competing over how fast you can return 50 terabytes of data and never over how they can run some median percentile function that can mix between data types in a way that’s convenient. That’s been a fun development for us because those are the problems that we would tackle as a BI provider. When a database addresses it, it gives us an advantage.“When GPT-4 came out, people thought it was going to put everyone out of their jobs.
Broadly, I think there’s a need for a semantic layer that allows you to ask and answer these types of questions. But I think there’s a bunch of other pieces that are needed before that’s actually viable, and Omni can probably help with some of that.: The first and most important use case for us is co-pilot. As I mentioned, we created a feature that uses AI to write Excel calculations.
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