Transformations for dbt Core Integrated Schedulinglink

Learn how integrated scheduling works for Fivetran Transformations.

Pipeline overviewlink

Fivetran pipelines use the following elements:

• The start is the interval that initiates the pipeline.
• A connector updates source tables in the destination.
• A junction waits for multiple connectors to finish syncing before it triggers a dbt transformation.
• A transformation is a model or a collection of models that updates downstream tables in the destination.
• An output model generates an analytics-ready table. It is typically a leaf node on your data lineage graph.
• A test is an assertion that you make about the models in your dbt project. A test may succeed or fail independently of model execution.

Fully integrated schedulinglink

Your output model, churn, uses an integrated schedule. The model references tables written by three connectors, each on an hourly schedule. The churn, customers, and revenue models are all refreshed every hour, after all three connectors have successfully synced.

Fully integrated scheduling with overlapping connector scheduleslink

You have three connectors referenced by the same output model, churn. The churn output model uses an integrated schedule and runs whenever there is new data in any source. The netsuite and salesforce connectors sync every hour, but the oracle connector syncs every 15 minutes.

The churn, revenue, and customers models run every 15 minutes after the oracle connector syncs and every hour after the salesforce, netsuite, and oracle connectors sync.

Fully integrated scheduling with sometimes overlapping connector scheduleslink

You have three connectors feeding into the same output model, churn. The churn output model uses an integrated schedule and runs whenever there is new data in any source. The netsuite and salesforce connectors sync every 2 hours, but the oracle connector syncs every 3 hours.

The churn, revenue, and customers models run every 2 hours after the salesforce and netsuite connectors sync, every 3 hours after the oracle connector syncs, and every 6 hours the salesforce, netsuite, and oracle connectors sync.

Fully integrated scheduling with downstream independent scheduleslink

You have three connectors feeding into the same output model, customers. You set the customers model to a fully integrated schedule, so it runs every 15 minutes. The two downstream models run on independent schedules - the revenue model runs every hour and the churn model runs once every 24 hours.

Partially integrated schedulinglink

You have three connectors feeding into the same output model, churn. The oracle connector runs every 15 minutes, the netsuite connector runs every hour, and the salesforce connector runs every 24 hours. You set the churn output model to update once a day to save on costs, but you don't want to run it until your destination data has been updated.

At the 24-hour mark, the churn, revenue, and customers models execute as soon as the three connectors successfully finish syncing.

Independent scheduling with upstream connectorslink

Your connectors run every hour, but you set the churn output model to update once a day to save on costs.

At the 24-hour mark, the churn, revenue, and customers models execute independently of the connectors, even if the connectors are currently running.

Independent scheduling with no upstream connectorslink

The churn output model is not related to any Fivetran connectors, but it lives in your dbt Core project and references an externally populated source table. You can still schedule churn and its upstream models in the Fivetran dashboard and run on an independent pipeline.