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A collection of useful SQL queries and view definitions for Panoply Data Sources

Directory structure

Every Panoply data source should have its own directory in the top level of the repo. Each data source directory should have two subdirectories: views and queries.

For example:



views are queries that perform significant ELT transformations and create tables to facilitate analysis and reporting. This will often be used to join and normalize tables that were created from nested JSON or create roll-up reporting tables that are easy for non-technical BI tool users to use with their BI tool of choice. Simply put: views are building blocks for queries.


queries demonstrate how you can query your data in Panoply. Most queries will probably fall into one of two buckets: "metrics," calculations like Customer Lifetime Value that can be further segmented out; and questions, like "What is the best day of the week to post on Instagram?”

Markdown file templates

Each Panoply data source will have its own directory modeled after the .github/data-source-template directory. Within that directory, there are two subdirectories: /views and /queries, each of these contains a corresponding template markdown file.

The main differences between the two templates are: views files have the CREATE VIEW syntax commented out. The CREATE VIEW syntax is not necessary if saving the view in Panoply. The line can also be uncommented when saving the view in other SQL workbenches. views files also contain an example query that could be used with the view definition. Finally, queries files contain a data dictionary of the columns that the query returns.


A collection of useful SQL queries for Panoply Data Sources







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