Hello! In this section, we will explore the best practices for modeling in Data Vault. They will help you avoid common mistakes, improve warehouse performance, and make the data model more understandable and scalable.
Main Best Practices
1. Clear separation of entities and relationships
- Hubs are used only for storing unique business keys.
- Links are intended exclusively for modeling relationships between entities.
- Attributes are stored only in satellites.
Example:
If you are modeling passengers and their bookings, then:
- Hub_Passengers stores unique passenger identifiers.
- Hub_Bookings contains unique booking numbers.
- Link_PassengerBookings links passengers to their bookings.
2. Use surrogate keys for linking
- All tables are linked via surrogate keys, not directly through business keys.
- This improves query performance and simplifies model management.
Example:
Instead of storing a long passport number in the link Link_PassengerFlights, use surrogate keys from Hub_Passengers and Hub_Flights.
3. Separate slowly changing attributes (SCD)
- Store attributes with different change frequencies in separate satellites.
- This optimizes data updates and reduces storage volume.
Example:
For the hub Hub_Passengers:
- Create a satellite for static data, such as date of birth (Sat_PassengerStatic).
- Create a separate satellite for frequently changing data, such as phone number (Sat_PassengerDynamic).
4. Do not add business logic to the model
- The warehouse should be a source of facts, not interpretations.
- Business rules are applied at the report or analytical data mart level.
Example:
If in one source a customer is recorded as "Ivan," and in another as "Ivan Ivanovich," both values should be loaded into the satellite. Consolidation occurs at the analytics level.
5. Optimize links for complex relationships
- For links with a large number of hubs (many-to-many), create additional links to avoid excessive complexity.
Example:
If a passenger can be linked simultaneously to flights and bookings, create two links:
- Link_PassengerFlights (passengers and flights).
- Link_PassengerBookings (passengers and bookings).
6. Use Load Date and End Date for versioning
- In satellites, always specify Load Date (load date) and End Date (expiration date).
- This simplifies data analysis for historical periods.
Example:
In the satellite Sat_PassengerAttributes:
| Hub Key | Phone Number | Load Date | End Date |
|---|---|---|---|
| 1 | 1234567890 | 2025-01-01 | 2025-01-15 |
| 1 | 1122334455 | 2025-01-15 | NULL |
7. Automate the loading process
- Use ETL/ELT processes to automatically generate surrogate keys, populate Load Date, and manage End Date.
Example:
In SSIS, create separate Data Flow Tasks for loading hubs, links, and satellites. Ensure the load date is recorded automatically.
Conclusion
Following these practices will make your Data Vault model robust, flexible, and performant. By applying them, you can easily scale the warehouse, add new data sources, and ensure high accuracy in analytics.
