Data Management

Leveraging new data technologies to accelerate business growth

Meet the expert
Kieran Kennedy
Kieran Kennedy
Head of Marketplace, Snowflake

Kieran is the Head of Marketplace at Snowflake where he oversees the Snowflake Marketplace, which enables organizations to find, try, and purchase data, data services, and applications to power innovative business solutions. Prior to Snowflake, Kieran was the Executive Relationship Officer for Strategic Alliances and Partnerships at FactSet, and spent over 31 years there driving go-to-market partnerships with top-tier technology and consulting firms. Kieran is also a founding board member of Academics in Motion, an educational nonprofit that targets high school students at risk that participate in sports and provides additional tutors and other resources. Kieran holds a B.A. in Economics from Syracuse University.

Data used to be difficult to find and access. With marketplaces, consumers can find everything they need in one place, from a variety of providers. We spoke with Kieran Kennedy, the Head of Marketplace at Snowflake, about how far data management has come, and where the industry is heading next.


Can you tell us about Snowflake’s “north star”?

Sure. Snowflake is a platform for companies to grow their business. So when we think about our metrics in terms of ‘how are we doing? What are we aiming for?’ We think about how we’re helping both consumers and providers of data in the Snowflake ecosystem. How can we facilitate those conversations? Those questions help guide us.


You’ve been in the data business for a little while. How have the fundamentals of the data business changed since you started?

Oh boy, that’s a long time. It used to be that if you wanted to start a data company, you’d take a brute force approach: pick a data set to collect, hire armies of people, and send them out to collect that data. Twenty or thirty years ago, that data went into an excel spreadsheet, and you’d distribute it by emailing the spreadsheet.

Now the approach has been streamlined. We can collect data in bulk, just from the cloud. Then, there are a variety of methods to share it so that customers can get it quicker and easier. Snowflake is really changing the game around secure data sharing.


How are companies using data gathering and management technologies to accelerate client outcomes? Is there anything they aren’t doing that they should be doing?

The biggest thing is that you can now gain insights where you couldn’t before. So for example, if I’m a retailer and I sell beach-wear, I can now look by latitude and longitude for what the weather is going to be like in certain locations around the world. I can find a place that is sunny with 75 degree temperatures 250 days of the year, and decide that location is a good place to put a retail outlet, right? A lot of consumers of data are now taking advantage of that kind of data. They can gain insights on their customer base and consumer behavior.

Still, though, what they’re not doing is fully leveraging those insights to really make business decisions based on data. They still use a lot of intuition and instinct. They may know there’s data out there to bring in new insights, but it’s been difficult to wrangle data and put it into a usable format – that’s where Snowflake comes in. A platform like Snowflake can provide analytic-ready data that gives them the ability to easily ingest alternative data that they may not have considered before.


Analytics teams and data scientists are hungry for all kinds of data–first party, second party, third party. Can you share some of the ways companies are able to leverage this data, now that they have so much available to them?

If we were talking about twenty years ago, if I had an idea in 2003, I’d have to search for all the data sets, maybe literally search in Google. Then I had to contact the company and ask them for a sample data set. They’d have to get back to me. That kind of ping pong back and forth took a long time.

Now, within my Snowflake instance I can find data sets, sample them, see if the data confirms or denies my hypothesis, and then decide about purchasing the full data set. The data buying process is ‘Find → Try→ Buy’. With the marketplace we took a process that used to take weeks and have distilled it down to, in some cases, hours.


What kinds of opportunities are there for Snowflake clients to utilize artificial intelligence and machine learning?

Part of the challenge with powering AI and ML and LLM models is that you need broad data sets that are analytic ready. It’s not hard to have a broad data set – there’s data all over the place. But is it in a format where you can run models against it? That’s what Snowflake Marketplace offers, too. Data is in an analytic format so that it’s ready to start running queries and training models.


Would you say that Snowflake customers have a leg up when it comes to utilizing data sets and machine learning models?

Yes, definitely. It’s easy to add, easy to find; it’s all in one place – Snowflake’s platform.

And from a provider side, providers are always worried about where their data is going. They want to know who their data is being used by. When their data is available via the Snowflake Marketplace, they have that information about who’s accessing their data, how much and when they are accessing it. So providers can have confidence knowing where their data is going.


As you mentioned, buying data can be a relatively long process. What needs to happen on the data provider and buyer side to make it easier for data customers to find, test, and buy the data they need?

As much as Snowflake Marketplace has increased the efficiency of the Find→Try→Buy process, there are still legacy data providers that have commercial models based on legacy subscription models. So if you buy a package from cable TV, you get the channels you want and the channels you’re never going to touch. Why should you pay for the E Channel if you never watch it? What we’re finding more and more is that data companies are setting up new data models that give you the opportunity to only pay for what you’re using.

Consumers like this model because they’re only getting charged for the data they use, and it lowers barriers to entry. And providers like it because they can get very granular – down to the individual column, level, row, or data item, to charge fees.

And again, because in the Marketplace providers have transparency into what the consumers are using, they have the security and comfort of knowing where their data is going and how it’s being used.


Is there anything you guys are working on that you’re super excited about? What’s on the top of your mind right now?

We’ve got two things I’m excited about. One is that the Snowflake Marketplace now has the capability for providers to monetize their products and use Snowflake as a charging and billing mechanism. And, coming this summer, customers can use Snowflake credits to buy products. We’re trying to facilitate conversations and make it easier for transactions to occur.

The next big thing is what we call Native Applications. So if a consumer has a database of sensitive data, maybe personal identification data, they don’t want to move that data to a less secure spot to do their analysis and enrichment; the move is too risky. In the Snowflake Marketplace they can download an app that was built into Snowflake using Snowflake primitives, and run the app right there to analyze the data. The customer can do everything they need without ever leaving the protection and security of the platform.

We’ll be sharing more about both of these big things – platform monetization and Native Apps – at our upcoming conference, Snowflake Summit. I’m very excited about both.