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Discover effective techniques to combine and simplify SQL queries using conditional aggregation in Snowflake for better data analysis efficiency.
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Combine SQL Queries for Efficient Data Analysis in Snowflake

In the world of databases, particularly when using powerful platforms like Snowflake, one of the common challenges data analysts face is managing multiple SQL queries. When dealing with similar datasets, it’s often beneficial to simplify your work by combining queries. This not only makes your SQL scripts cleaner but can also enhance performance.

In this guide, we will discuss how to combine two SQL queries that share the same table but have different conditions in their WHERE clauses. Let's dive into the details.

The Problem: Two Separate Queries

Consider the following two SQL queries targeting the same table but retrieving different sets of data based on varying conditions. Here's an overview of the existing queries:

Query 1

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Query 2

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As we can see, both queries perform similar operations on the same table but differentiate based on the item_no condition.

The Solution: Conditional Aggregation

To create a more efficient query, we can utilize conditional aggregation. This allows us to combine both queries into one, making it easier to read and execute. Here’s how you can do it:

Step-by-Step Breakdown

Common CTE (Common Table Expression):
We'll start by creating a CTE that calculates the necessary intermediate values for both the original queries.

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Select with Conditional Aggregation:
Next, we can leverage the CTE to summarize data based on both conditions in a single SELECT statement.

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Complete Combined Query

Putting it all together, we get the following:

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Conclusion

Combining SQL queries using conditional aggregation is a powerful technique that enhances the readability and performance of your SQL scripts. By understanding how to structure your queries effectively only once, you can save time and resources in Snowflake.

Next time you find yourself repeating queries with minor adjustments, consider consolidating them into a single, streamlined query. Happy querying!