![]() ![]() The folks over at Snowflake have a pretty robust library of documentation here.Īfter logging in to Snowflake’s web UI, we need to create a table in a test database and insert the data containing statistics for all kickers with an attempt during week 1. Throughout this post, I will intentionally leave out some of the details regarding basic navigation and functionality of Snowflake. To get started, you have the option to run SQL statements from the Snowflake web UI, SnowSQL (CLI client), or a third-party tool such as SQL Developer or SQL Workbench/J I’m using the web UI in this case. In preparation for this exercise, I have imported 2016 Week 1 NFL Kicking data to a spreadsheet and modified it slightly to add LAT/LON city coordinates and an indicator for whether the stadium is indoor or outdoor, in addition to the date/time the game started. ![]() #Snowflake json query how to#In this post, I’ll walk through how to query JSON data and join it with a sample data set, make it readily available for a BI tool, and then display the results by connecting OBIEE and DV to the Snowflake Data Warehouse. The syntax is straightforward and makes the process of using JSON data in conjunction with relational data a relative breeze. Among other things, one of my key takeaways from the exercise was how simple it is to query JSON data in the Snowflake Data Warehouse. Employees at the Minneapolis Red Pill Analytics office recently had the luxury of sitting with Snowflake’s Steve Herskovitz for some on-site education. ![]()
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