Note: This piece is excerpted from a longer post on the Snowflake blog, which discusses how a Snowflake customer and data provider in Snowflake's Data Marketplace leverages Placekey by using the External Functions framework to merge their data with additional datasets. Read here for more information.
Snowflake's Data Cloud provides the unique ability for anyone to join their own data sets with thousands of live third-party data sets near-instantly, securely, and without moving data. Businesses operating in the Data Cloud gain a huge advantage over their competitors who are stuck in data silos and struggling with stale data sets downloaded from their legacy data providers weeks, months, or years ago.
Snowflake's interest in Placekey started with Senior Product Manager, Andrew Meyendorff, asking this question:
"Consider how it would change your business if you could instantly analyze or enrich your own data with any other live data set you can imagine."
At the time, location intelligence was a quickly growing segment in the world of analytics, and there was certainly no shortage of providers with interesting location data, including companies like SafeGraph. Partnering with these providers enabled businesses to add new dimensions to their business’s analytics. However, location data such as coordinates and addresses from different sources often had minor differences, despite referring to the same place.
Meyendorff found that Placekey's address matching and entity resolution API service solved this challenge, by encoding the coordinates and other characteristics of a location into a single identifier. This gave Snowflake users a simple and effective way to join location data sets together, regardless of their source. The Placekey API's being free also allowed them to easily use it to enrich their own data or data customers got from elsewhere.