Datasinks and Live Dashboards

Datasinks turn a FluidGrids workflow into the data pipeline behind a dashboard. Instead of exporting spreadsheets or maintaining a separate ETL job, the last step of a workflow pushes its result to a named datasink in BigConsole, and any dashboard that reads from that key refreshes as new output arrives.

The concept addresses a familiar gap. Operational numbers tend to live in databases and SaaS tools that were never meant to be charted together, so teams fall back on nightly exports, brittle scripts or a queue of requests to a data team. Here, extraction, filtering, aggregation and delivery sit in one visual workflow that the people who own the numbers can read and change themselves.

The first illustration shows the cause. A four-step pipeline on the builder canvas pulls orders from Postgres, keeps only paid orders, aggregates daily revenue and ends in a selected BigConsole DataSink node. Its Node Details panel lists the datasink operations (post, upsert, append and delete), a copyable datasink key, a refresh schedule and a note that the node needs no manual input because it collects the previous node's output automatically, with a JSON preview of that payload. The second illustration shows the effect: a live revenue dashboard that names its source key, says when it last updated and traces the source workflow from schedule to datasink, above KPI cards, a thirty-day trend, channel and hourly breakdowns, a top-products table and a regional split.

Datasinks complement the built-in workflow analytics. Those measure how healthy the automations are; this concept puts a workflow's business output on screen. Because the pipeline is an ordinary workflow, the design lets it inherit everything else FluidGrids provides, including schedules, versioning, run history and retries, so a broken dashboard can be traced back to a specific run and step.