Скачать или смотреть How to Fill Null Values in Snowflake SQL for Previous Quarterly Data

Learn how to fill null values with the latest available data in Snowflake SQL, ensuring each user has their quarterly classifications correctly represented.
---
This video is based on the question https://stackoverflow.com/q/77818506/ asked by the user 'rien312' ( https://stackoverflow.com/u/20979109/ ) and on the answer https://stackoverflow.com/a/77818922/ provided by the user 'SelVazi' ( https://stackoverflow.com/u/4286884/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, comments, revision history etc. For example, the original title of the Question was: Finding previous quarter null and fill with the previous quarter Snowflake SQL

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Fill Null Values in Snowflake SQL for Previous Quarterly Data

When working with data in Snowflake SQL, one common problem is managing missing values. Specifically, in cases where data for certain quarters is absent (e.g., Q3 in our example), it is critical to fill those gaps with the most recent valid data from previous quarters. In this post, we'll explore how to accomplish this step-by-step.

The Problem

Imagine you have a dataset that keeps track of user progress across four quarters. However, due to data entry issues or other reasons, one or more quarters may not have associated entries.

For instance, consider the following dataset for user progress:

user_id
date_at
quarter
type_class
123
2022-01-13 8:30:25
1
beginner
123
2022-02-13 7:29:25
1
beginner to mid
123
2022-04-26 17:30:59
2
mid
123
2022-12-15 12:30:33
4
expert

As you can see, the data for quarter 3 is missing. Our goals are two-fold:

Fill the missing quarterly data (i.e., for Q3) using the last available values (in this case, the result should be “mid”).

Ensure that only the latest classification per quarter is recorded. Here, we need to ensure only the latest type_class for each quarter is retained.

The Solution

Define the Dataset

Let's start with our sample data structure in SQL:

[[See Video to Reveal this Text or Code Snippet]]

Prepare the First CTE

The first Common Table Expression (CTE) is used to assign a row number for each entry within its respective quarter to identify the latest values.

[[See Video to Reveal this Text or Code Snippet]]

Cross Join for Missing Quarters

Next, we need to ensure that we have entries for all four quarters using a CROSS JOIN. This will give us a complete set of records for each user_id across all quarters.

[[See Video to Reveal this Text or Code Snippet]]

Final Selection

Finally, we select the necessary columns, ensuring we only retain the latest type_class for each quarter:

[[See Video to Reveal this Text or Code Snippet]]

Results

After executing the above SQL queries, we can attain the desired result:

USER_ID
QUARTER
TYPE_CLASS
123
1
beginner to mid
123
2
mid
123
3
mid
123
4
expert

Conclusion

In summary, filling in the missing quarterly data in Snowflake SQL involves creating a complete list of quarters and associating them with the most recent valid data for each user. By following the steps outlined, you can ensure that your dataset accurately reflects user progress without missing information.

Implement the provided SQL solution in your Snowflake environment to manage your quarterly data effectively and maintain data integrity across your analytics.

Happy querying!