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Extend Data Interoperability with Placekey’s Snowflake External Function

Jan 11, 2021 by Placekey

Read more about the Placekey for Snowflake announcement in this morning's press release, Yahoo Finance, GISCafe, The AP, Business Insider, Seeking Alpha, and SalesTech Star.

At Placekey, we are open data evangelists. We firmly believe that high-quality data shouldn’t only live in the walled gardens of technology giants, but instead should be reasonably accessible to everyone. Furthermore, the value of a dataset only increases as it is made easier to join with other data sources. In other words, the number of potentially valuable insights from a dataset exponentially increases as linkages open up new applications. This idea is summarized nicely in this chart from Auren Hoffman, the CEO of SafeGraph:

This idea informs the core goal behind the creation of Placekey: to drastically expand the interoperability of location and place-based datasets. By making it incredibly easy to match addresses and points-of-interest, or POIs, and to perform data deduplication, quality control, and data conflation, Placekey solves core problems faced by data scientists and members of the geospatial community. At the same time, any dataset containing addresses or POIs is instantly made more accessible (and thus more valuable) by appending Placekeys in a new column.

Snowflake External Function

The Placekey Snowflake External Function is an integration which allows you to easily append Placekeys to your address or POI data without ever leaving a Snowflake instance. The function works by taking an input set of columns (for example, street address, city, region, and postal code), communicating with the Placekey API, and delivering Placekeys as a standalone column or as a copy of your original dataset with the Placekeys appended. The Placekey column can then be used to seamlessly join datasets together. 

The Snowflake External Function joins a growing list of other Placekey integrations, including those for Python, R, Google Sheets, Excel, and QGIS (with more coming soon).

Identity Resolution with Infutor

Infutor, a Placekey Partner, curates a best-in-class identity graph that allows marketers and brands to supplement their first-party customer data by resolving individual data points to identities, households, or places (physical addresses). By processing an address as input, for example, Infutor can construct complete identities for residents at this location, enabling omnichannel marketing and high-quality customer targeting.

The identity resolution process isn’t always completely straightforward. The above two records can reasonably be assumed to refer to the same person, but matches like this cannot be reliably made without a sophisticated machine learning algorithm. Furthermore, Infutor has more than 240 million records, so any kind of manual processing would be out of the question.

While Infutor does leverage their own proprietary machine learning algorithms to interleave various data sources together, Placekey is a simple and elegant way to match these records together based on the address field. In the example below, the two differently-formatted addresses both resolve to the same Placekey, enabling a seamless join:

Using Placekey to Streamline Customer Onboarding

A crucial part of Infutor’s pre-sale process with potential customers is comparing respective datasets. Placekey helps potential clients gauge what the match rate will be in advance of making a purchase without exchanging any proprietary data. An address, in addition to the other identity metrics offered by Infutor, is one way of uniquely identifying an individual. Infutor and prospective clients can therefore Placekey the addresses in their respective datasets and objectively compare them in a secure way.

More broadly, Placekey extends the interoperability of Infutor’s data by allowing it to interface directly with any other dataset containing address or POI information. Infutor’s Total Property Profiles real estate database comes pre-appended with Placekeys, enabling users to easily integrate their own complementary data. Zora Senat, VP of Strategic Partnerships at Infutor notes: 

“Our clients range from other data compilers to advertisers & publishers and our use cases extend beyond marketing into risk & fraud as well. So, it’s important we explore new avenues to access our graph. And we see Placekey as a viable avenue to share data securely but also in a way that reduces a lot of the friction in a data procurement process.”

Technical Tutorial: Placekey Snowflake External Function Demo

The Placekey Snowflake External Function enables Infutor and other users of Snowflake to make bulk queries to the Placekey API in order to directly append Placekeys to their database tables without ever leaving a Snowflake worksheet.

In order to Placekey your data using the External Function, simply follow these steps, or watch the video demo below:

Step-by-step Technical Tutorial:

1. Get a free Placekey API key

2. Sign in with an ACCOUNTADMIN role to your Snowflake instance. Alternatively, sign in with a role with access to the CREATE INTEGRATION privilege.

3. Create the API Integration:

4. Create the External Function. Enter your API key into the indicated string below:

At this point, the external function is ready to be used in order to append Placekeys to your data. Use it like so:

5. Create some testing data in a new table:

6. To use the external function directly, call it like so:

7. The functions returns the following:

8. This result can then be joined back to the original table.

Copy and pasteable code, a stored procedure which enables bulk Placekey appending, and a full working example is available on the Placekey Snowflake External Function Repository.

Get ready to unlock new insights on physical places