I remember the first time that someone asked me about cloud computing. I was attending a software conference in 2008, representing a BI vendor. One of the conference officials came to our booth to ask if anyone from our company would be willing to sit on a panel for a discussion about cloud computing. At the time, I had heard a few whispers about the concept of cloud computing, but I didn’t have a firm grasp of the concept or any idea of the impact it would have.
I declined the offer to sit on the panel, and instead watched from the audience. There were some interesting ideas presented in that discussion. However, as someone who frequently worked with very sensitive customer data, it seemed far-fetched that these same customers would push their data to an external location. Fast-forward 3 years and suddenly cloud computing was gaining incredible momentum. Amazon’s AWS had made it easy to spin up resources for any size of business. That year I spent a good chunk of my free time working on a startup that hosted its service in AWS and I learned a lot. Unfortunately our venture didn’t get very far, but the seed had been planted.
Shortly afterwards I joined a much larger cloud-based BI startup. There I began to really understand how the scale of the cloud was a game-changer. At the time, we had to work hard to convince most of our potential customers that the cloud was secure and that they could entrust their most valuable data to someone else. That was a crazy ride where once again I learned a great deal. When the time came to make a change, I made the jump to the cloud leader and joined Amazon.com. While I was not in the AWS business unit, I quickly learned that the cloud was very much at the heart of how Amazon ran everything. Flexibility and scalability were essential for such a dynamic organization. I was providing BI for a key development team and their business partners and the cloud was a key resource in my daily work. I loved working at Amazon, and once again I continued to learn. One key principal for building a successful career in BI is to constantly be on the lookout for the next new technology. When I first heard about Snowflake Computing, the problems that they were trying to solve really resonated with me. A totally new data warehouse, purpose built for the cloud with a focus on scalability and performance. The website in those days was little more than a few buzzwords and the profiles of the founders. I realized that they had assembled a team capable of building something truly transformative and I decided that I needed to investigate further.
At first, my inquiries were mainly aimed at satisfying my curiosity. However the more I learned, the more I realized that I needed to seriously consider joining their team. As I mentioned earlier, I was very happy with my current role, so I took things very slowly. At each step of the process there were more questions, but the things I heard made me think that this company was something special.
After a few weeks and interviews, it came time for me to interview at the headquarters. My first interview was with Benoit Dageville and Thierry Cruanes, two of the three founders of Snowflake. I actually started the interview off in French since they are both French and I once lived in France. However as we turned to technical subjects we transitioned to English so that I could understand the details. I was blown away by what they told me about what they had built over the past two years. I was sold, and decided to make the jump.
Snowflake has built a database that truly leverages the flexibility and scalability of the cloud. By separating storage from compute in a unique way, they have enabled customers to handle their data in ways that no one could even consider previously. For example, with unlimited storage at a reasonable cost you can load raw semi-structured data into Snowflake without worrying about consuming valuable storage in a traditional database cluster. Snowflake built on that foundation and added built-in parsing to discover the schema of the semi-structured data to enable schema on read. The applications are practically limitless, and the speed and ease-of-use far exceed any Hadoop implementation I have ever dealt with.
On top of the freedom to store data in new ways, Snowflake’s architecture allows for scalable compute resources to handle variable loads and practically eliminate resource contention. We are just beginning to see the applications for this functionality, as customers are no longer tied to a fixed amount of compute resources.
With all of this functionality, one would assume that managing Snowflake would be a challenge. But the beauty of the cloud is that we are able to deliver all of this a service that requires little to no administration. Simply define a data model, load your data, and start querying.
Some database gurus may feel that they want to get under the hood to tune the database to meet their specific needs. I am one of those who felt that my skills were the key to providing access to the right data in the right way. I have come to realize the while I may be good at getting the most out of a database, Snowflake engineers are great at making a database that is easy for anyone to use. Snowflake’s database allows users from analysts and engineers to data scientists to leverage their skills with data in an environment that is automatically optimized for performance and scalability.
To use an analogy, I can make money in the stock market by researching stocks and buying and selling on my own. Still, I won’t ever be able to beat the top fund managers that are paid to be the best at what they are and have the tools and focus to suceed. Snowflake lets you leverage the work of some of the top minds in the industry that have made a database that runs better than any other database in the world.
It took a number of years for me to realize, but the idea of cloud computing is enabling solutions we never could have dreamed of 7 years ago. I am not a gambler, but I am “all in” on the cloud and feel confident that this is one bet that will pay off.