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Course

Data Types and Functions in Snowflake

IntermediateSkill Level

4.8+

Updated 01/2026

Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

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SnowflakeData Manipulation3 hr11 videos38 Exercises3,000 XP2,100Statement of Accomplishment

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Course Description

Nail down the fundamentals of Snowflake, starting with data types. You'll gain an understanding of the different data types that Snowflake can store, and the operations that can be performed on that data. Once you've developed an understanding of Snowflake's different data types, you'll begin to manipulate and transform that data with functions like TRIM, AVG, SUM, and DATEDIFF . You'll even define your own functions to customize and streamline data manipulation.Once you're comfortable manipulating and transforming data, you'll add a few handy tools to your tool belt. You'll pick up the best ways to flatten semi-structured data and build multiple common table expressions. Before you put the finishing touches on this course, you'll master the art of pivoting data in Snowflake.

Prerequisites

Data Manipulation in Snowflake

1

Data types

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.

Text data types

Is that text data?

Working out in the big city

Defining text data

Numeric data types

Go with the FLOAT

Creating a retail table

Datetime data types

Building datetime values

Which timezone?

When did you check in?

2

Manipulating Data

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.

Manipulating text data

Managing display length

Transforming text data

Motivating member marketing

Numeric calculations

Comparison operators

Adjusting membership prices

What burns more calories?

Manipulating datetime data

Breaking down a timestamp

How long were you at the gym?

Making appointments

User-defined functions in Snowflake

Creating your own Snowflake function

Ranking gym members by efficiency

3

Advanced Snowflake techniques

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.

Flattening Semi-Structured Data

Retrieving nested data

Working with personal info

Building a gym member description

Multiple common table expressions

Identifying high-performers

Comparing senior workouts

Pivoting Data

Evaluating workout length

Is CrossFit a popular workout?

Which workouts burn the most calories?

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Data Types and Functions in Snowflake

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FAQs

Who will benefit from this course?

Data analysts, data engineers, SQL developers, and anyone working with Snowflake who needs to understand data types, manipulate text and numeric data, work with timestamps, and handle semi-structured data effectively.

What skills do I need to have to join this course?

You should have basic SQL knowledge, including SELECT statements and simple queries. Familiarity with Snowflake's interface and basic navigation is helpful but not required, as fundamental concepts will be covered.

What practical problems can I solve after completing this course?

You'll be able to clean and format text data, perform calculations on numeric columns, extract date components for reporting, parse JSON and XML data, create reusable custom functions, and transform data layouts using pivot operations.

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