Turning helpdesk data into a structured operational reporting pipeline
Before: Ticket data was scattered across the ticketing platform, automations, a database and reporting tools – a combined view required manual reconciliation.
What was done: Everything was connected into one structured path – from ticket intake through SQL to the Power BI report, with controlled ticket classification.
Now: Reports come from a single place, far less manual work remains, and you can always see who did what and when.
Problem
Ticket data and change records were distributed across service, workflow, database and reporting tools, leaving disconnected process steps and manual reconciliation.
Existing systems
- Ticketing platform
- Power Automate
- SQL Server
- Power BI
Constraints
- The workflow had to preserve operational ownership across several existing tools.
- Classification needed to remain controlled and reviewable rather than becoming a zero-touch decision.
- Internal schemas, ticket content and operational volumes were not public-safe.
Solution architecture
Webhook or service intake feeds an automation layer, structured SQL models and controlled classification, followed by Power BI consumption.
Text alternative
- Helpdesk tickets
- Automation
- SQL
- Power BI
Implementation
The work connected ticket ingestion, workflow orchestration, SQL modeling, controlled classification and reporting into one traceable pipeline.
Technologies used
- Power Automate
- SQL Server
- Power BI
- Azure OpenAI
- PowerShell
Outcome
- Created a structured, traceable reporting pipeline.
- Reduced disconnected manual process steps.
- Provided a clearer foundation for operational reporting and classification review.
Lessons / reusable pattern
- Reporting reliability starts with a defined data path and ownership at the intake boundary.
- Classification is safer when it is placed inside a reviewable workflow with explicit exceptions.