In Databricks, the sequence pattern is ideal for representing the progression of data through different stages of refinement. This mirrors the Delta Lake architecture's approach, which typically involves bronze (raw data), silver (cleaned or conformed data), and gold (aggregated or report-ready data) tables. Each stage signifies a phase in the data transformation journey, with dependencies ensuring a systematic and sequential flow through the pipeline.