Unveiling the Utility of EQUAL_NULL in Snowflake: A Comprehensive Guide


Snowflake, a cloud data platform, offers a unique feature known as EQUAL_NULL. This feature changes the behavior of the equality operator (=) when comparing values against NULL. In the realm of data manipulation, NULL values represent missing or unknown data points. While NULL values are commonplace, handling them effectively is crucial for ensuring data integrity and accurate analysis. Snowflake, a prominent cloud-based data warehouse, offers the EQUAL_NULL function, specifically designed to address the nuances of NULL value comparisons. This article delves into the EQUAL_NULL function, exploring its purpose, advantages, and practical applications.

EQUAL_NULL: Changing the game

EQUAL_NULL alters this behavior. When enabled, NULL values are considered equal to each other. This feature is particularly useful in scenarios where NULL is used to represent an absence of data, and equality between such absent data points is logically meaningful.

Advantages of Using EQUAL_NULL

  1. Simplified queries: Reduces the complexity of SQL queries involving NULL comparisons.
  2. Improved data joins: Enhances the joining of tables where NULLs need to be treated as equal.
  3. Data consistency: Ensures consistent handling of NULL values across various query conditions.
  4. Accurate NULL value comparisons: EQUAL_NULL accurately compares values, including NULL values, ensuring that NULL values are not overlooked or misinterpreted.
  5. Enhanced data integrity: By correctly handling NULL values, EQUAL_NULL contributes to improved data integrity and consistency within Snowflake datasets.
  6. Simplified data analysis: EQUAL_NULL simplifies data analysis by providing a consistent and reliable mechanism for handling NULL values, leading to more accurate and meaningful results.

Real-World use cases of EQUAL_NULL

The EQUAL_NULL function finds application in various real-world scenarios:

  1. Customer data analysis: In customer relationship management (CRM) systems, EQUAL_NULL can be used to identify customers with missing contact information or incomplete profiles.

  2. Financial data analysis: In financial data, EQUAL_NULL can be used to detect missing transaction amounts or incomplete financial records.

  3. Inventory management: In inventory management systems, EQUAL_NULL can be used to identify products with missing stock levels or outdated information.

Create Table and Insert Data:

  name VARCHAR,
  nickname VARCHAR

INSERT INTO people (id, name, nickname) VALUES
  (1, 'Sachin', NULL),
  (2, 'Ram', 'Raju'),
  (3, 'David', NULL),
  (4, 'Wilson', 'Willy');

Data Merging Query with EQUAL_NULL:

Suppose we want to merge this table with another dataset where the nickname might be NULL.

SELECT a.name, b.name
FROM people a
JOIN people b ON a.id != b.id AND EQUAL_NULL(a.nickname, '');

This query utilizes the EQUAL_NULL function to compare the contact_number column to both NULL and an empty string (”), effectively identifying all customers with missing or incomplete contact information.

Snowflake important urls to refer

Author: user