How do you use surrogate keys and natural keys in a snowflake schema?

Surrogate keys are system-generated identifiers assigned to each record in a table, while natural keys are inherent attributes of the data that uniquely identify each record. In my projects, I've often utilized surrogate keys for primary key columns in dimension tables, as they provide a stable, non-changing identifier for records and simplify joins between tables. Natural keys, on the other hand, are commonly used for primary key columns in fact tables, where the natural attributes of the data (e.g., date, product code) uniquely identify each transaction or event.

In a snowflake schema, surrogate keys and natural keys play distinct roles. Surrogate keys, like auto-incremented IDs, uniquely identify rows without inherent meaning. Natural keys, such as social security numbers, naturally identify rows based on their data attributes. Surrogate keys enhance performance and simplify joins, while natural keys maintain data integrity and provide meaningful identification. Depending on the scenario, either or both types of keys can be utilized effectively.

A surrogate Key is sequentially generated number i.e. unique/auto-increment and attached with each and every records in a Dimension table in Data Warehouse. A natural Key is column that already exist in the table attributes of the entity within the data warehouse and uniquely identify a record in the table. So as per need we used Surrogate key because it has no business meaning and we provided relation with our fact-dimension table and Natural key has business meaning so if we used and our requirements changed so we need to rework on our keys.

Surrogate keys offer numerous benefits in a snowflake schema. They provide simplicity and consistency through numeric, sequential generation, aiding in easy storage and indexing. Their stability and independence prevent cascading updates, ensuring data integrity. Moreover, their flexibility allows for seamless adaptation to new data or business rule changes without impacting existing keys, enhancing scalability and maintenance efficiency.

Natural keys and surrogate keys have different functions in a DW structure. Similar to auto-incremented IDs, surrogate keys are used to uniquely identify rows that lack inherent meaning. Rows can be organically identified by natural keys, such social security numbers, depending on data properties. While natural keys preserve data integrity and offer meaningful identification, surrogate keys improve efficiency and make joins simpler. These two kinds of keys can be used together or separately, depending on the situation.

In my opinion, the root cause of the all drawbacks of natural key that affect any table is the heterogeneous way of data sources is implemented. Each data source implement in diferent way the natural keys based in their own technica perspective of business context to work: data type, data quality on data model, index can use, handle of changes on time, etc. So the main challenge is define how structure your table to support the key natural for all records despite the heterogeneity of the data sources: what part to normalize and what parts can store in nested field like json.

Further to the mentioned drawbacks, natural keys can lead to issues in maintaining historical data integrity, especially when business rules change. For instance, a natural key based on a product name might become obsolete if the naming convention evolves. This can create challenges in maintaining accurate historical records. Using surrogate keys helps ensure that historical data remains consistent, even as natural attributes change over time.

In a snowflake schema, I typically assign surrogate keys to dimension tables, ensuring each dimension record has a unique identifier. Natural keys, meanwhile, are often used in fact tables to establish relationships with dimension tables based on common attributes. By carefully selecting and utilizing both types of keys, I maintain data integrity and optimize query performance within the snowflake schema.