Last month I attended our first Snowflake Summit since First American Data & Analytics joined the Snowflake Data Marketplace last March. It was also Snowflake’s first in-person event since 2019, which was exciting in and of itself. The show was very well attended with nearly 5,000 people on site, 300+ sessions and one of the busiest tradeshow floors I’ve ever seen. Over four days, data management professionals, business intelligence officers and data scientists gathered to network, collaborate and exchange essential knowledge about Snowflake and emerging trends in data and analytics.
But amidst the presentations and networking, there were some major announcements by Snowflake about data innovations and some great takeaways our clients should consider to get the most out of our data on the Snowflake Data Marketplace.
One of the larger announcements to come out of the conference was that Python, the preferred language of choice for machine learning, can now be used in Snowflake. Being able to use Python will ultimately make Snowflake more accessible to data scientists, machine learning engineers and developers. This is especially valuable when leveraging First American’s property data for model development, both as a stand-alone dataset, as well as when enriching existing customer data.
Being able to hear Snowflake’s plans for the future and their new innovations in data and analytics first-hand was fantastic. But, more so, being able to sit down with our Snowflake team and learn how we can help our clients access, integrate, share and analyze our data to gain a competitive advantage was even more beneficial.
One of the biggest takeaways for me was the importance of setting up clean rooms to handle first-party data in a privacy-preserving manner. Snowflake clean rooms allow for sensitive data, such as emails, names, IP addresses, etc., to be accessed while preserving privacy. By using clean rooms clients can alleviate the need to download data in bulk. Clients can run a quick query, for example, and search how many properties in California have X amount of equity, produce a list and automatically download the data. As quickly as First American is able to provision data in Snowflake, this means customers can be up and running with test data remarkably fast.
The First American data packages available on Snowflake allows FinTech and PropTech users to quickly turn data into insights with real property information, including property tax information, robust deed and mortgage history, homeowner’s association (HOA), and automated valuations. Users also have the ability to comingle their own information with First American assets, fueling advanced insights and competitive advantages for their businesses.
From a partner perspective, it was exciting to see the momentum Snowflake has generated as a relatively new company with a rapidly expanding ecosystem. As data becomes even more powerful and valuable, First American is proud to provide our customers with everything they need to imagine or disrupt markets, making the art of the possible…possible.
To learn more about what data sets are available on Snowflake, click here. We also license in several other capacities. Learn more here.