Declarative Scheduling is an exciting feature in Dagster that allows data engineers and analytics engineers to orchestrate dbt models with improved ground-breaking improvements. Unlike other orchestrators, Dagster uses software-defined assets (SDAs) which enables users to build a fine-grained understanding of the dbt graph, its upstreams, and its downstreams. This allows Dagster to provide scheduling guarantees that other orchestrators cannot. With Declarative Scheduling, users can specify freshness policies for their models, which simplifies the scheduling process and saves resources by reducing redundant model runs. Users don't need to explicitly add their models to a job or think about cron schedules, and Dagster will automatically ensure that all dependencies are met. The feature has been introduced in the latest Dagster release and is available as part of the dbt integration.