How do you design surrogate keys for hierarchical or dimensional data models?

Simple surrogate keys are often used when you need a straightforward, unique identifier for each row in a table. They are typically auto-incrementing integers. They are easy to implement and maintain, provide a unique identifier without business meaning, and simplify joins between tables. This approach is beneficial in scenarios where you want to ensure data integrity and avoid data anomalies. In a customer dimension table, a simple surrogate key might be an auto-incrementing integer that uniquely identifies each customer.

The most abstracted and main concept is use a unique value to identify an entity, so it requires two components: > Define the universe of the possible values. > Mechanims to guarantee uniques value always. Don't matter if the value is string, image or audio with incremented or decremented mechanism to guarantee the uniquiness by naive storage component, integrated storage component or business system.

The following best practices help you to effectively use simple surrogate keys to improve the design and management of your hierarchical or dimensional data models. Use a unique identifier: Ensure that each surrogate key is unique, even if the underlying data changes. Avoid using complex algorithms or calculations to generate surrogate keys. Choose a naming convention that is easy to understand and maintain. Evaluate the impact of surrogate keys on database performance, especially for large datasets. Do not use natural keys (e.g., customer ID, product ID) as surrogate keys, as this can make it difficult to manage data changes. Clearly document how surrogate keys are generated and used in your data model.

Designing surrogate keys for hierarchical or dimensional data models involves creating unique, non-business-related identifiers for each entity within the model. In a dimensional model, surrogate keys are typically used in fact tables to link to dimension tables, ensuring consistency and simplifying joins. These keys are usually auto-incrementing integers or UUIDs, which remain stable even if the natural keys change. For hierarchical data, surrogate keys help manage parent-child relationships by maintaining a clear, unchanging reference to each node in the hierarchy, enabling efficient querying and flexibility in handling changes in the data structure.

Composite surrogate keys are useful when you need to maintain relationships between multiple entities or levels in a hierarchy. They are constructed from multiple columns, often from different tables. They help preserve the hierarchical or dimensional relationships within the data and reduce the number of joins needed in queries. This approach is suitable for complex data models with multiple levels of hierarchy. In a product hierarchy, a composite surrogate key might combine a category key and a product key to uniquely identify each product within its category.

Use composite surrogate keys to represent relationships: Composite surrogate keys can be used to represent relationships between entities in a hierarchical or dimensional data model. Keep them simple: Composite surrogate keys should be easy to understand and maintain. Avoid using natural keys as part of composite surrogate keys: Natural keys can change over time, which can make composite surrogate keys difficult to maintain. Consider using generated sequences to create composite surrogate keys: Generated sequences can help to ensure that composite surrogate keys are unique and easy to manage. Test composite surrogate keys thoroughly: Composite surrogate keys should be tested thoroughly to ensure that they work as expected.

such kind of key (especially, if it uses meanungfull non-int columns) could make debugging and data quality analytics much easier rather than hash

Composite surrogate keys serve as a trick to represent additional context in your SK. Given the value is made up of other identifiers, once you see the value, it's easy to understand what that row is uniquely representing. In these cases, this is much better than using a single auto-incremental column that does not have any meaning.

The following best practices help you create hashed surrogate keys that are secure, efficient, and easy to manage. Use a hash function that is resistant to collisions and has a large output size. Normalize the data before hashing to ensure that the hash values are consistent. Consider the length of the hash value: The length of the hash value should be sufficient to prevent collisions but not so long that it impacts performance. Use a hash function that produces the same output for the same input data. Test the hash function to ensure that it produces unique values for all possible combinations of input data. Consider using a salt: A salt can be added to the input data to make the hash values more difficult to reverse engineer.

Hashed surrogate keys are ideal for ensuring uniqueness across distributed systems or when dealing with large-scale data. They are generated by applying a hash function to one or more natural keys. They provide a consistent and portable identifier across different systems, ensure uniqueness, and can anonymize sensitive data. This method is effective in environments where data distribution and collision avoidance are critical. In a customer table, a hashed surrogate key might be generated by hashing the customer's email address or a combination of other unique attributes.

Some additional considerations: 1. Some database engines have better hash functions than others, so its important to ensure you run robust tests on various permutations/conditions of the hash to ensure it is deterministic and truly unique at the scale you're dealing with, as unpredictable collision might occur with certain hashing functions (e.g., postgres hashtext) 2. Ensure consistent null and whitespace behavior in either the hash or composite surrogate approach. Snowflake's HASH() method for instances produces different values for NULL + '' 3. Depending on the pipeline and data storage solution, indexing can facilitate a retrieval of whatever surrogate was created in ETL processes.