What

Columns is a data workflow product designed to help spreadsheet users, analysts, engineers, and managers move from fragmented data handling to a more structured, persistent workflow. Based on the page, it focuses on connecting data sources, transforming data in plain language, keeping outputs synchronized on a schedule, and turning results into shareable reports and visual summaries.

The product appears positioned between lightweight spreadsheet work and more brittle script-based data operations. Its core workflow is to connect sources such as warehouses, files, APIs, or upstream nodes, apply schema-aware transformations, automate recurring updates, and publish outputs for internal reviews, external audiences, or validation-heavy intake processes.

Features

Connected source ingestion — Connects warehouses, files, APIs, and upstream nodes so teams can centralize data inputs in one workflow.
Plain-language transformations — Lets users describe transformations in natural language, which can reduce manual wrangling for non-developer stakeholders.
Schema-aware transforms — Applies transformations with awareness of data structure, which is useful for maintaining consistency as workflows evolve.
Scheduled automation — Runs flows hourly, daily, or weekly to keep downstream systems and reports updated without repeated manual effort.
Rule-driven alerts — Supports thresholds and notifications so stakeholders are informed when specific data conditions are met.
Shareable reporting and guided upload flows — Publishes summaries, visuals, and customer-facing upload workflows to support reporting, onboarding, or data QA processes.

Helpful Tips

Assess whether your main bottleneck is spreadsheet sprawl, unreliable scripts, or cross-system handoff issues; this type of product is most useful when recurring data processes need structure and visibility.
Validate how well plain-language transformation works on your actual datasets, especially if your team relies on complex joins, edge-case logic, or strict governance requirements.
Use scheduled sync and alerting carefully to avoid unnecessary notifications; define business-relevant thresholds before broad rollout.
If external-facing upload or validation workflows matter, test the intake experience with real users to confirm it handles data quality checks clearly and consistently.
The page mentions auditability and clean handoffs, but it does not detail governance depth, versioning, or approval controls, so those areas should be reviewed in product documentation or demos.