It was destined to be. I live in the mountains, at the foot of a glacier, literally surrounded by snow year round. As my Snowflake two year anniversary comes and goes, I’ve been thinking back on how it all started. The beginning of my relationship with Snowflake took off just after the launch of Snowflake Marketplace in 2019. At the time, I was an analyst at Forrester Research, researching and advising companies on how to enter the data economy. I’d already been beating that drum for years at that point, with reports like It’s Time to Take Your Data to Market and Data Commercialization: The Tech Leader’s Guide to Taking Data to Market.

I ❤️ ❄️  

In 2019 I did a deep dive into the new data marketplaces that were emerging to facilitate data transactions. There were players of all sorts, including Snowflake, which provided a marketplace to enable customers to discover and share data more easily and securely. I did some advisory work with the marketplace team to discuss features I was seeing out in the market—features that are now available like try-before-you-buy. But the real “gotcha” moment for me was hearing it all come together as the Data Cloud. In an analyst briefing via Zoom, the Snowflake team presented the vision to truly “mobilize the world’s data.” 

As an early evangelist of the data economy and having heard innumerable briefings on data tools and infrastructure, this one really got me. I opened the chat window and typed, “Are you hiring?” The immediate response was “You?!” With my “yes,” the journey began.

Fast forward two years, and I’m just as excited today as I was then. Maybe even more so as I know what’s coming and I see the delight of our customers and partners. 

What am I (still) excited about? 

Snowflake’s vision remains to help mobilize the world’s data. And, for many companies, that really resonates. Since I joined, Snowflake’s customer base has more than doubled. At our recent earnings call, we reported over 7,800 customers across all industries as of January 31, 2023, and 573 of the Fortune 2000. But it’s not just the big guys. Snowflake’s startup program attracts entrepreneurs from all industries, and the uses of the Snowflake platform have multiplied. We had year-over-year growth of 54% and 158% net revenue retention. Oh, and a net promoter score of 72. That’s extremely high—three times the industry average of 21, based on the Qualtrics 2021 NPS Industry Benchmarking Report. 

What started as a cloud data warehouse evolved into the Data Cloud, which includes the content—data, services, and applications—that customers and partners bring to the cloud. OK, that sounds like I’m copying from our marketing content. But it’s really true. The mission of “mobilizing the world’s data” means enabling companies to collaborate. 

Data collaboration. That’s what attracted me to Snowflake: the ability to share and collaborate not only internally but broadly across an external ecosystem. Snowflake customers report significant growth in data collaboration internally, with customer and “product 360” initiatives that combine data from different business units and functions. But we’re also seeing more interest in acquiring external data and finding ways to share data with others. Another of my Forrester reports, from back in 2014 and (embarrassingly) entitled Find a Date to the Data Dance, discussed finding partners to build these new data products and services. But the “data dating” that I find more exciting today are the relationships being built across partners. For example, Kraft Heinz shares data with retailers in “joint value planning” — a win-win collaboration to provide consumers with the right products at the right time, in the right place, and at the right price, making sure to avoid the dreaded “out of stock.” 

Secure data collaboration. Sharing is good, but sometimes data can’t be exposed to others. We’re all familiar with GDPR and other privacy regulations. But have you heard of clean rooms? Snowflake’s Global Data Clean Rooms allow customers to “share without showing,” a concept I’ve discussed in this blog post. In short, collaborating parties specify exactly what type of analysis can be performed and the exact information to be returned. That enables the parties to identify, for example, numbers of joint customers without sharing who those customers are. Targeting advertisements is currently the most popular use case, but identifying sites for clinical trials or designing joint product offerings are other common ways companies use data clean rooms. And, Snowflake continues to add features that enhance the privacy measures for the data that is “shared.” The recent acquisition of LeapYear brought differential privacy capabilities to further obfuscate the underlying data. 

Decision-support tools (aka data apps). The Holy Grail of data-driven decision-making is an application, or a “decision-support tool,” that delivers the insights directly into a business context. A product manager wants to prioritize features. Sales ops leaders want to optimize the price of a deal. Logistics wants to route a shipment to avoid roadblocks (literal and figurative). I’ve been thinking about decision-support tools as a means of delivering insights for some time now. Summarizing the results of a 2017 Forrester Wave, I wrote that “The insights providers who rated highly in our study and whose customers were most satisfied were those who provided rich decision-support tools, allowing decision-makers to explore the findings, evaluate alternative actions and trade-offs required, preview predicted outcomes, and confidently address the challenges and decisions they faced.” 

Now Snowflake makes this much easier to do, whether the “decision” is made by a machine or a human. Snowflake’s support of native applications, the launch of Snowpark, and the acquisition of Streamlit all help partners and customers build and deliver these offerings.

Snowflake’s Powered by Snowflake program helps turn customers into partners, helping them take their data applications to market. Piano, for example, analyzes web traffic and enables its customers to present personalized offers to specific website audiences. Pricemoov enables pricing optimization by defining pricing strategies and structures, applying prices consistently across products and channels, adjusting prices for promotion or liquidation, and performing impact simulations to avoid surprises. 

Of course, not all applications are end-user facing. Some applications guide automation, making decisions for us without human intervention. The common theme is that they serve a specific function in a workflow, and ultimately deliver business value. 

Snowflake Marketplace. And, that brings me back to how I got here, my Forrester research on data marketplaces. Last year, Snowflake Marketplace dropped the “data” from its name because it now delivers even more. Snowflake partners publish their data and their apps on the Marketplace, to be discovered either publicly or by specific Snowflake customers. By creating a “listing,” data and application publishers can define exactly what they offer—from metadata to data tables to business logic to full applications—as well as specify to whom, at what price, for what time period, and for which purpose. Snowflake makes it easy to build and deliver data and applications to customers across clouds. Take a look at a demo of Snowflake Marketplace to see how easy it is to navigate and use.

I could go on and on. Most of all I’m excited about what we enable our customers to do with the platform and in the Data Cloud.  

Bottom line: I love my job. Happy anniversary to me. If you’d like to hear more or share your own stories, don’t hesitate to reach out.