The problem
Small businesses often rely on manual steps to collect operational data, check whether it is correct, update records, and prepare reports. This takes time, increases the risk of errors, and makes failed processes harder to notice.
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Detailed project walkthrough
Business Ops Intelligence Hub
A local business process automation prototype that receives operational data, validates it, stores valid records, logs workflow results, and prepares the information for business and workflow-monitoring dashboards.
Local system prototypeBuilt with sample dataNot implemented in a real business
What the system does
The prototype automates the flow of business data from the moment it is received. It checks incoming requests, stores valid records, logs successful and failed workflow runs, and prepares data for operational dashboards.
Why it may be useful
It reduces manual work, keeps operational data in one place, and gives a business owner a clearer view of what was processed, what failed, and what needs attention.
System design
How the parts work together
The prototype connects business data intake, validation, storage, logging, reporting, and workflow monitoring in one local environment.
System thinking
- Incoming webhook requests are checked, validated, and sent through separate success and error paths.
- Successful requests, invalid data, and unauthorised attempts are stored as workflow results for later review.
- SQL views prepare business records and workflow logs for reporting and monitoring dashboards.
Architecture
Business inputn8n validationPostgreSQLExecution logsSQL viewsMetabase
System overview
How the process works
The prototype connects automation, database storage, logging, and reporting in one local environment.
- 01
Business data enters the workflow
Operational data is sent to an n8n webhook. In a real setup, this could come from a form, application, spreadsheet integration, or another connected service.
- 02
The request is checked
The workflow checks whether the request is authorised and whether the required information is present and correctly formatted.
- 03
Valid data is stored
Valid business records are saved in PostgreSQL so they can be reused by reports, dashboards, and future workflows.
- 04
The workflow result is logged
Successful requests, invalid data, and unauthorised attempts are recorded. This makes it easier to understand what happened during each workflow run.
- 05
Dashboards show the results
SQL views prepare operational data and workflow logs for Metabase dashboards showing business activity and workflow health.
Workflow outcomes
Success and error paths
The workflow does not treat every request as successful. It handles valid data, invalid data, and unauthorised requests separately.
Successful requestHTTP 200
Valid data is stored in PostgreSQL and the successful workflow result is logged.
Invalid dataHTTP 400
The workflow rejects incomplete or incorrectly formatted data and records the validation error.
Unauthorised requestHTTP 401
Requests with a missing or incorrect secret are rejected and logged as unauthorised.
Business reporting
Operational data becomes visible
The same stored data can be prepared for business reporting instead of remaining inside the automation workflow.
Executive overview
A business dashboard showing revenue, orders, customer feedback, and changes over time.
Workflow monitoring
Errors and workflow health can be reviewed
Execution logs are also prepared for a separate dashboard showing successful, invalid, and unauthorised workflow runs.
Workflow observability
A monitoring dashboard showing workflow executions over time and the number of results by status.
My contribution
What I worked on
- Designed the system structure and data flow
- Configured the local Docker Compose environment
- Created PostgreSQL tables and SQL reporting views
- Built n8n validation, success, and error paths
- Added workflow execution logging
- Created Metabase business and monitoring dashboards
- Prepared test scenarios and documentation
- Added checks to avoid committing secrets
Technology used
Main tools
- n8n
- PostgreSQL
- Metabase
- Docker Compose
- SQL
- Webhooks
- Git and GitHub
- WSL and Linux
Current limitation
The system was built and tested locally with sample data. It demonstrates how the parts can work together, but it has not been deployed or tested inside a real organisation.