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Devolp Customer Data Platform using dbt part 1
- Understanding customer behavior is crucial for business growth, and developing a user-friendly BI solution can make insights quick and easy to access.
- The Event Schema provides the perfect foundation for creating a simple, scalable solution that stands out as the ideal candidate to handle all event-related data with ease.
- The dbt project ensures a well-organized, multi-layered approach to data modeling that enhances data quality and usability.
- The YAML file is used to provide more context about the data being held and improve clarity.
- An incremental model can be used for fast-changing tables to append new data only, keeping things efficient and fast.
- Tests are used to ensure data consistency across tables and confirm that each order item can be reliably linked to related records in other table.
- Business rules for pricing integrity can be incorporated with a package that allows for conditional logic similar to WHERE clauses in SQL.
- The foundational 'seeds' for the journey tables form the core structure of the activity schema, capturing the relationships between various events in the customer journey.
- Using these seeds as building blocks, we can layer in additional business logic later to refine and enrich the customer journey.
- Documentation is used in the YAML file to give context to the approach and data structure of the order journey model.
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