Why Data types in Snowflake? - Purpose & Use Cases

The Big Idea

What if your data could organize itself perfectly every time, without mistakes?

The Scenario

Imagine you have a huge spreadsheet with mixed information: numbers, dates, text, and more. You try to organize it by hand, guessing what each piece of data is. It's confusing and messy.

The Problem

Manually guessing or mixing data types leads to mistakes like treating numbers as text or dates as strings. This causes errors, slow queries, and wrong results. Fixing these mistakes takes a lot of time and effort.

The Solution

Snowflake's data types let you clearly define what kind of data each column holds. This helps Snowflake store, process, and retrieve data efficiently and correctly without confusion or errors.

Before vs After

✗ Before

INSERT INTO "table" VALUES ('123', '2023-01-01', 'hello'); -- no data type checks

✓ After

CREATE TABLE "table" (id INT, date DATE, greeting STRING);

What It Enables

With proper data types, Snowflake can quickly find, sort, and analyze your data accurately, making your work faster and more reliable.

Real Life Example

A company stores customer orders with order numbers as integers, order dates as dates, and customer names as strings. Using correct data types helps them quickly find orders from last month or total sales without errors.

Key Takeaways

Manual data handling causes confusion and errors.

Snowflake data types organize data clearly and safely.

This leads to faster, accurate data processing and analysis.

Practice

1. Which Snowflake data type is best suited to store true or false values?

easy

A. BOOLEAN

B. VARCHAR

C. NUMBER

D. DATE

Solution

1. Step 1: Understand the purpose of BOOLEAN data type

   BOOLEAN is designed to store logical values: true or false.

2. Step 2: Compare with other data types

   VARCHAR stores text, NUMBER stores numbers, and DATE stores dates, none are for true/false.

3. Final Answer:

   BOOLEAN -> Option A

4. Quick Check:

   True/False = BOOLEAN [OK]

Hint: True/false values always use BOOLEAN type [OK]

Common Mistakes:

• Choosing VARCHAR for true/false values
• Using NUMBER to represent logical states
• Confusing DATE with BOOLEAN

2. Which of the following is the correct way to declare a VARCHAR column with a maximum length of 100 characters in Snowflake?

easy

A. VARCHAR{100}

B. VARCHAR100

C. VARCHAR[100]

D. VARCHAR(100)

Solution

1. Step 1: Recall Snowflake syntax for VARCHAR

   Snowflake uses parentheses to specify length, e.g., VARCHAR(100).

2. Step 2: Identify incorrect syntax

   Options with brackets or no parentheses are invalid in Snowflake.

3. Final Answer:

   VARCHAR(100) -> Option D

4. Quick Check:

   Length in parentheses = VARCHAR(100) [OK]

Hint: Use parentheses for length in VARCHAR [OK]

Common Mistakes:

• Using brackets or braces instead of parentheses
• Omitting parentheses for length
• Writing VARCHAR100 as one word

3. What will be the result of this Snowflake SQL query?

SELECT CAST('2024-06-15' AS DATE) AS my_date;

medium

A. 2024-06-15

B. '2024-06-15'

C. Error: Invalid cast

D. NULL

Solution

1. Step 1: Understand CAST to DATE

   CAST converts a string in 'YYYY-MM-DD' format to a DATE type in Snowflake.

2. Step 2: Check the output format

   The DATE value is returned as 2024-06-15 without quotes.

3. Final Answer:

   2024-06-15 -> Option A

4. Quick Check:

   CAST string 'YYYY-MM-DD' to DATE = date value [OK]

Hint: CAST string 'YYYY-MM-DD' to DATE returns date value [OK]

Common Mistakes:

• Expecting quotes around the date output
• Thinking CAST causes error for valid date strings
• Assuming NULL if format looks like a string

4. You try to insert into a table with this column definition:

price NUMBER(5,2)

But Snowflake gives an error. What is the likely cause?

medium

A. The scale (2) cannot be greater than precision (5)

B. NUMBER(5,2) is invalid syntax in Snowflake

C. NUMBER(5,2) means 5 digits total, 2 after decimal, so max 999.99 allowed

D. NUMBER cannot have scale and precision specified

Solution

1. Step 1: Understand NUMBER(precision, scale)

   Precision is total digits, scale is digits after decimal.

2. Step 2: Calculate max value for NUMBER(5,2)

   Max number is 999.99 (3 digits before decimal, 2 after).

3. Final Answer:

   NUMBER(5,2) means 5 digits total, 2 after decimal, so max 999.99 allowed -> Option C

4. Quick Check:

   Precision=5, Scale=2 means max 999.99 [OK]

Hint: Precision includes all digits; scale is decimal digits [OK]

Common Mistakes:

• Thinking NUMBER(5,2) syntax is invalid
• Confusing precision and scale order
• Assuming scale can be greater than precision

5. You want to store a timestamp with timezone in Snowflake. Which data type should you use to keep both date, time, and timezone information?

hard

A. TIMESTAMP_NTZ

B. TIMESTAMP_TZ

C. DATE

D. VARCHAR

Solution

1. Step 1: Review Snowflake timestamp types

   TIMESTAMP_NTZ stores timestamp without timezone; TIMESTAMP_TZ stores with timezone.

2. Step 2: Identify correct type for timezone info

   Only TIMESTAMP_TZ keeps timezone data along with date and time.

3. Final Answer:

   TIMESTAMP_TZ -> Option B

4. Quick Check:

   Timestamp with timezone = TIMESTAMP_TZ [OK]

Hint: Use TIMESTAMP_TZ for timezone-aware timestamps [OK]

Common Mistakes:

• Choosing TIMESTAMP_NTZ which ignores timezone
• Using DATE which lacks time info
• Storing timestamps as VARCHAR