ServiceNow ITSM data pipeline

Operational reporting needs a clean, trustworthy view of what happened to every ticket: when it was raised, how its state changed, and whether it met its SLA. The raw ServiceNow data does not arrive in that shape.

I built an end-to-end dbt pipeline that integrates incidents, cases and SLA data into the warehouse and turns it into a single, published view for SLA and resolution reporting. State changes are modelled with temporal satellites, so there is a full audit trail of how each ticket moved over time, which is what makes root-cause analysis possible.

What I built

• Data Vault 2.0 modelling (hubs, links and satellites) for incidents, cases and task SLAs.
• Temporal satellites tracking state changes, giving a complete history of each ticket’s lifecycle.
• Data contracts enforced across cleansing, refined and published layers, so downstream consumers get a stable, governed shape.