For a Dataflow Gen2 creating a new dimension table that must immediately relate to the central fact table, which schema option should you select in the data destination?

For a Dataflow Gen2 creating a new dimension table that must immediately relate to the central fact table, which schema option should you select in the data destination?

• A. Dynamic Schema
• B. Fixed Schema
• C. Hybrid Schema
• D. Flat Schema

Answer: (B)

When you’re adding a new dimension that must immediately relate to the central fact table, you want a destination with a stable, predefined set of columns. A fixed schema locks in the column names, data types, and the surrogate key used to join to the fact table, ensuring reliable foreign-key relationships and predictable downstream queries. If you used a dynamic schema, the sink could automatically evolve with new attributes, leading to schema drift that can break joins and complicate migrations and reporting. A flat schema would merge everything into one table, which undermines the clear dimensional relationships, and a hybrid approach doesn’t guarantee the stable, join-ready structure you need. Therefore, fixed schema is the best fit.

When you’re adding a new dimension that must immediately relate to the central fact table, you want a destination with a stable, predefined set of columns. A fixed schema locks in the column names, data types, and the surrogate key used to join to the fact table, ensuring reliable foreign-key relationships and predictable downstream queries. If you used a dynamic schema, the sink could automatically evolve with new attributes, leading to schema drift that can break joins and complicate migrations and reporting. A flat schema would merge everything into one table, which undermines the clear dimensional relationships, and a hybrid approach doesn’t guarantee the stable, join-ready structure you need. Therefore, fixed schema is the best fit.