Then create a Snowflake stage area like this. (Presumably that is because they would prefer that you define the column data types and number precision and size yourself.) create table weather( Unfortunately, Snowflake does not read the header record and create the table for you.
Upload this data to Amazon S3 like this: aws s3 cp paphosWeather.csv s3://gluebmcwalkerrowe/paphosWeather.csv We have worked with this data in other tutorials, including Loading CSV Files from S3 to Snowflake.) This is just a small subset of 1,000 records, converted to CSV format. (We purchased 20 years of weather data for Paphos, Cyprus from OpenWeather. Download 1,000 hourly weather records from here.
You need some data to work through this example. Use the right-hand menu to navigate.) Sample data (This article is part of our Snowflake Guide.
In this tutorial, we show you how to use Snowflake statistical functions with some examples. Basic analytics is all you need in most situations, and it is the first step towards more elaborate analysis. You can, however, do analytics in Snowflake, armed with some knowledge of mathematics and aggregate functions and windows functions. (If you want to do machine learning with Snowflake, you need to put the data into Spark or another third-party product.) It only has simple linear regression and basic statistical functions.