Data Types and Functions in Snowflake

Before you can change the world using Snowflake, you need to know the type of data you'll be working with. You'll start with text data, learning to use it in queries and define columns, plus discover how to retrieve column details from any table. Then you'll master numeric data types and date/time data, understanding precision, scale, and how to convert strings to timestamps.

Now that you know your Snowflake data inside-and-out, it's time to manipulate and transform it. You'll begin with text data manipulation using TRIM, SPLIT, and CONCAT, then master numeric operations like arithmetic and summary measures with SUM and AVG. You'll explore timestamp transformations by extracting components like year or hours, calculating intervals between dates, and create your own custom Snowflake functions (UDFs) to implement personalized logic.

In this final chapter, you'll crank the heat up with Snowflake's more advanced functionality. You'll start with VARIANT data types (semi-structured data), learning to parse top-level and nested data using dot-notation and bracket-notation, then master common table expressions (CTEs) by building and using multiple CTEs. Finally, you'll wrap up by creating pivoted tables using the PIVOT keyword to transform data into an easy-to-digest format, ready for reports and analysis.