PixelOkay / Creator tools / Data Storytelling Studio

Data Storytelling Studio

Build a narrative from numbers, one insight at a time.

↑ Import datasetOpen project

Explore the dataInteractive controls for this slide

Filter value

Chart data

Data storytelling for anyone

Import a CSV or JSON dataset, turn rows into clear visual insights, and connect those insights into a story your audience can explore. Create business reports, research summaries, classroom explainers and campaign performance narratives without sending your data to a server.

How to build a visual data story

Start with a dataset, choose a dimension and a measure, choose a suitable chart, then add a headline and explanation. Create more slides to explain the changes over time. Preview the result and download a self-contained HTML story, images, a PDF slide deck, or an editable project backup.

Charts support bar, line, area, donut, scatter and tabular views. Numeric aggregation and missing values are explained in the editor so readers are not misled by silently changed data.

Using Data Storytelling Studio

Import a supported table or use the built-in example, choose a chart and explain the result with narrative and source text. Arrange the slides, then save a project and export the story format you need.

Chart, row and filter budgets apply; advanced joins, calculated fields and causal analysis are unsupported. Shared HTML still contains plotted values and labels, and project JSON can contain the full dataset. PDF is rasterized rather than editable vector text; review shared content for sensitive data.

Choose an editable data story or a viewing handoff

Project JSON: retain supported slides/settings and potentially the full dataset.

HTML: share the supported interactive story, which still includes plotted values and labels.

SVG, PNG or PDF: share visual output; PDF pages are rasterized rather than editable vector text.

CSV: review the selected data export and its aggregation/filter context.

Practice: explain a fictional comparison

Import a small fictional table and choose a supported chart.

Add a narrative describing what is shown and a source note identifying the data as fictional.

Inspect filters and labels, then save JSON and review the chosen viewing export for sensitive information.

This is an authored storytelling exercise, not researched evidence or a causal finding.

Data-story export questions

Does sharing only the HTML hide every data value?

No. HTML contains plotted values and labels, while editable JSON can contain the full dataset. Review both narrative and data before distribution.

Can chart changes establish causation or perform advanced data preparation?

No. The supported workflows are bounded and do not supply advanced joins, calculated fields or causal inference. Explain aggregation and filters explicitly rather than treating a visual comparison as proof.