10 Snowflake Naming Convention Best Practices
A good naming convention is important for any project, but it's especially important in Snowflake, where names have a special meaning. Here are 10 best practices to follow.
Snowflake is a cloud-based data warehouse that enables organizations to store and analyze large amounts of data. It is important to have a consistent naming convention for the objects in Snowflake to ensure that the data is organized and easy to access.
In this article, we will discuss 10 best practices for naming conventions in Snowflake. We will cover topics such as object naming, object prefixes, and object suffixes. Following these best practices will help you create a consistent and organized data warehouse.
1. Use lowercase letters
Lowercase letters are easier to read and understand, which makes it simpler for everyone in the organization to remember what each object is. Additionally, lowercase letters make it easier to search for objects within the database since they won’t be confused with other words or phrases that may contain uppercase letters.
Using lowercase letters also helps ensure consistency across all of your snowflake objects. This will help you avoid confusion when someone else is looking at your code or trying to figure out how something works. Finally, using lowercase letters can help reduce errors due to typos, as it’s much harder to accidentally type an uppercase letter than a lowercase one.
2. Separate words with underscores
When you separate words with underscores, it makes the names easier to read and understand. This is especially important when dealing with long or complex names that contain multiple words. By separating them with underscores, it’s much easier for people to quickly scan and comprehend what the name means.
It also helps make sure that all of your snowflake objects have a consistent naming convention. This can be helpful if you ever need to search for an object in the database, as it will help ensure that you get the correct result.
3. Avoid using reserved keywords as identifiers
Snowflake is a SQL-based database, and as such it has certain keywords that are reserved for use in the language. If you try to use one of these words as an identifier (such as a table name or column name), Snowflake will throw an error. This can be very confusing and time consuming to debug, so it’s best to avoid using any of the reserved keywords as identifiers.
To make sure you don’t accidentally use a reserved keyword, check out the official list of Snowflake reserved keywords before creating your identifiers. That way, you can ensure that your naming conventions are compliant with Snowflake standards and won’t cause any unexpected errors.
4. Don’t start an identifier with a number or an underscore
When you start an identifier with a number or an underscore, it can be difficult to distinguish between the different objects in your database. For example, if you have two tables named “1_table” and “2_table”, it’s hard to tell which one is which without looking at the actual table names.
By avoiding numbers and underscores as the first character of an identifier, you make it easier for yourself and other developers to quickly identify what each object is. This will save time when writing queries and debugging issues.
5. Don’t use non-ASCII characters in identifiers
Non-ASCII characters can cause problems when used in identifiers because they are not supported by all databases and applications. This means that if you use non-ASCII characters, your code may not be compatible with other systems or databases.
Additionally, using non-ASCII characters can make it difficult to read the code, as some of these characters may look similar but have different meanings. For example, a hyphen (-) is often confused with an underscore (_).
Finally, using non-ASCII characters can lead to errors due to encoding issues. If the wrong encoding is used, the character may appear differently than expected. To avoid any potential issues, stick to ASCII characters for snowflake naming conventions.
6. Don’t use special characters (except for _ and $) in identifiers
Special characters can cause confusion when writing queries, and they can also lead to errors. For example, if you use a hyphen (-) in an identifier, it could be interpreted as a minus sign instead of part of the name.
Also, special characters can make identifiers difficult to read, which can lead to mistakes when writing or debugging code. To avoid these issues, stick with letters, numbers, underscores (_), and dollar signs ($) for your identifiers. This will help ensure that your code is readable and error-free.
7. Don’t use Snowflake-specific quoting characters in identifiers
Snowflake-specific quoting characters are used to identify objects in the database, such as tables and columns. If you use Snowflake-specific quoting characters in identifiers, it can lead to confusion when trying to reference those objects. For example, if you have a table named “MyTable” and you use double quotes around the name (i.e. “MyTable”), then someone else might think that the object is actually called “MyTable” instead of “MyTable”. This could lead to errors or unexpected results.
To avoid this issue, make sure to only use standard SQL quoting characters for your identifiers. That way, everyone will know exactly what object they are referencing.
8. Choose meaningful names
When you choose meaningful names, it makes it easier for developers to understand the structure of your data warehouse. This is especially important when working with large datasets and complex queries. Meaningful names also make it easier to debug errors in code because they provide context about what each table or column represents.
Finally, meaningful names can help reduce confusion among team members who are unfamiliar with the snowflake schema. By choosing descriptive names that accurately reflect the purpose of a particular table or column, everyone on the team will be able to quickly identify which part of the data warehouse they need to work with.
9. Be consistent
When you have a consistent naming convention, it makes it easier for everyone to understand the structure of your data warehouse. It also helps with troubleshooting and debugging when something goes wrong. Additionally, having a consistent snowflake naming convention can help reduce errors in queries and make them more readable.
To ensure consistency, create a set of rules that all team members must follow when creating new objects or tables. This will help keep everyone on the same page and prevent any confusion. Additionally, consider using prefixes or suffixes to indicate the type of object being created (e.g., “tbl_” for tables).
10. Keep it simple
When you have a complex naming convention, it can be difficult to remember what each part of the name means. This can lead to confusion and mistakes when creating or modifying snowflakes. Additionally, if your team is ever onboarding new members, they will need to learn the entire naming convention before being able to work with existing snowflakes.
To avoid these issues, keep your snowflake naming conventions as simple as possible. Use short, descriptive names that are easy to remember and understand. For example, instead of using “snow_customer_data_table,” use something like “customers.”