The cloud hasn’t changed data governance. You still need to be engaged with the business. You still need to have a data catalog. You must build these things; they don’t just magically appear.

Organizations must bring together all the silos of data into one central data platform so people can access it and analyze it—that’s something that both Snowflake and Sigma facilitates.

But it doesn’t help to have a central platform and a great analytics tool to access data if nobody understands the data or its source. These are part of a broader discussion that is resurfacing because of the need for compliance—and the data lake versus data swamp conversation.

We need governed data lakes so that the data is useful. If we want to do machine learning, and we want to do AI, and we want to do business intelligence, we need to embrace more governance. People must understand the source of the data, follow the lineage of the data, and, most importantly, understand the meaning of the data from a business perspective.

How has the cloud changed the way companies approach data infrastructure?

One of the things I’m seeing is the evolution of the data lake and data warehouse. It’s becoming more about a data platform and a place for doing your analytics and getting all the data consolidated. The cloud presents a massive opportunity here because of the flexibility and nearly unlimited scale that it provides. It has removed the on-prem constraints from the conversation.

I’ve been telling people that data lake is not a technology; it’s a concept. And we need to get people to understand that. Big data is the same thing. It’s not a technology, it’s a concept. Data warehouse, it’s not a technology, it’s a concept. The cloud provides us with the technological ability to bring all of this together. In my mind, many of these boundaries are entirely artificial, and it was a result of the foregoing technology limitations that we had at the time. You no longer have to think about these concepts as being different things.