Multi-source · Daily · 6 nodes
READYManage pipeline execution schedules and monitor job history
| Run ID | Status | Started | Duration | Rows | Action |
|---|---|---|---|---|---|
| a7f3d2e1-4b5c | Success | 2026-06-14 02:00:01 | 4m 32s | 45,230 | |
| b8e4c3f2-5d6e | Success | 2026-06-13 02:00:03 | 4m 18s | 43,891 | |
| c9f5d4g3-6e7f | Scheduled | 2026-06-15 02:00:00 | — | — |
{
"debug_messages": [
"=== PIPELINE CONFIG DEBUG ===",
"Total Nodes: 6",
"Node report:GET_MERCHANT_LISTINGS_ALL_DATA:
{\"type\":\"schema\",\"schemaType\":\"source\",\"entityId\":\"report:GET_MERCHANT_LISTINGS_ALL_DATA\",\"hasContent\":false,\"contentLength\":0,\"hasMockData\":false,\"hasLastRunOutput\":false,\"fields\":25}",
"Node report:GET_AMAZON_FULFILLED_SHIPMENTS_DATA:
{\"type\":\"schema\",\"schemaType\":\"source\",\"entityId\":\"report:GET_AMAZON_FULFILLED_SHIPMENTS_DATA\",\"hasContent\":false,\"hasMockData\":false,\"hasLastRunOutput\":false,\"fields\":33}"
]
}
{
"type": "WorkflowExecutionFailedEventAttributes",
"failure": {
"message": "Activity task failed",
"source": "",
"stackTrace": "",
"encodedAttributes": null,
"cause": {
"message": "Transformation Error: Column missing - 'None of [Index(['rgafsd_currency', 'rgafsd_item-price'], dtype='str')] are in the [columns]'",
"source": "",
"stackTrace": " File \"/usr/local/lib/python3.11/site-packages/temporalio/worker/_activity.py\", line 359, in _handle_start_activity_task\n result = await self._execute_activity()\n..."
}
}
}
| Date & Time v | Workflow Events ≡ | Expand All v |
|---|
| Column | Type | Masking Rule | Action |
|---|---|---|---|
| warehouse_id | string |
Press Play to start the tour.
Welcome to the Sensyze DataFlow interactive product tour. This guided walkthrough showcases how data engineering and analytics teams can design, deploy, and monitor production-grade visual data pipelines entirely on their own secure, self-hosted infrastructure. By keeping data processing localized within your private cloud or on-premise servers, Sensyze eliminates security vulnerabilities, regulatory compliance risks, and row-based consumption costs typical of SaaS solutions.
For organizations operating in banking, insurance, and healthcare, the transition to traditional cloud SaaS tools is blocked by strict data residency laws. The Digital Operational Resilience Act (DORA) in the EU and HIPAA in the US demand complete control over infrastructure. Sensyze is the only modern data pipeline platform that marries the visual ease of cloud ETL with the security of a self-hosted, air-gapped deployment, offering 7x lower total cost of ownership over a 5-year period.
The Sensyze DataFlow interactive product tour provides a comprehensive walkthrough of the platform's core capabilities. This guided experience demonstrates how data engineering teams can build production-grade visual data pipelines using a drag-and-drop node graph interface. The tour showcases multi-source data ingestion from platforms like Shopify and PostgreSQL, Python and SQL code transformation nodes, data masking for PII protection, and destination routing to CSV, JSON, and database targets. Users see the full pipeline lifecycle from source selection through transformation, masking, and output, all running on a self-hosted infrastructure that keeps sensitive data within the organisation's own network boundary.
The interactive tour includes several guided stages that highlight the platform's key differentiators. The visual designer section shows how analysts can connect data sources to transformation nodes without writing code, while retaining the ability to open a built-in code editor for Python or DBT SQL scripts. The data masking stage demonstrates column-level security configurations that automatically redact or tokenize sensitive fields before they reach downstream systems. The scheduling section reveals cron-based job configuration with execution history tracking, row counts, and duration metrics. The observability stage provides real-time monitoring dashboards with per-node latency, error logs, and stack traces for debugging pipeline failures. Each stage is narrated with optional audio and subtitles, making the tour accessible to both technical and non-technical stakeholders evaluating the platform.