
Number of coins in my pocket over time (spoiler: it is decreasing)

There are hundreds of amazing companies that sell software and tools to data scientists and machine learning teams. In fact, many of the best companies in the last 15 years have been exactly that.
But outside of SafeGraph (where I work), there are almost no companies that specialize in selling data to data scientists.
Why?
Partially it is because it is MUCH easier to get to $10 million ARR by selling applications (traditional SaaS). Partially it is just tradition coupled with stagnation. Partially it is because venture capital firms have been wary of funding data companies. And, most convincingly, being a data-only business is less exciting to most entrepreneurs because data is a supporting role (see the last section on data and humility).
But selling data to data scientists is starting to be a big business.
Selling data (DaaS or Data-as-a-Service) historically has not been a great business. Outside of Zoominfo and a few others, there have been almost no pure-play data unicorns built in the last 20 years.
Check out the DaaS Bible — the ins and outs of running a data-as-a-service business (DaaS accounting, winner-take-most dynamics, and more)
That’s because very few companies had the ability to make use of raw data in the past. 10 years ago, only the most advanced engineering teams were able to make use of external data. But that’s changing. An order of magnitude more companies buy data today than did five years ago. That’s because a good engineer with a tool like Snowflake can be as productive as a great engineer was 5-10 years ago.
This is happening across industries.
One example is hedge funds. Not that long ago, just ten funds were buying significant alternative data. Today it is still under 100. But there are 500-700 funds that are currently making the investment to ingest large amounts of data.