Help Center

Learn how to get the most out of SlateData

Visualizations

Build interactive charts and maps from your data using natural language queries and AI-powered recommendations.

Creating a Visualization

On your workspace's Overview, click New, then Visualization.
The editor opens on Choose your data. The Data panel on the left lists the workspace's datasources and their tables; Search tables and columns finds one. Open a table to see its rows.
To shape the rows yourself, click SQL in the bar at the top, edit the query, and click Run Query.
With AI on, you can ask the assistant bar in the middle of the page instead — for example, "Show me revenue by region over the last 12 months". It writes and runs the SQL, and the rows appear here.
With rows on screen, click Visualize.
Pick one of the recommended chart types under Choose a chart type, then click Create chart. The visualization is saved to the workspace.

To chart data that isn't in a datasource — a CSV or Excel file, a file on the web, or rows you paste — click Add data at the bottom of the Data panel, or New, then Upload a file on the Overview.

Supported Chart Types

SlateData recommends the chart types that fit your data's columns, so not every type is offered for every result.

Chart Type	Best For
Bar chart	Comparing values across categories (shows the top 10 when there are many)
Line chart	Time series and trends over time
Stacked area chart	Time series showing composition over time
Pie chart	Part-to-whole comparisons with a handful of categories (3–6)
Treemap	Part-to-whole with many categories (24+), or whenever you ask for the parts of a whole
Nested treemap	Part-to-whole across groupings that nest (Region › State › City), each group headed by its name
Sunburst and icicle charts	Groupings that nest, as rings or bands from the outermost level in
Circle packing	Groupings that nest, as circles within circles
Waffle chart	Shares of a whole as a grid of 100 squares, for a few categories (2–6)
Marimekko chart	Part-to-whole across two groupings: bars as wide as their totals, split into shares
Lollipop chart	Ranking many categories with less ink than bars
Funnel chart	The steps of a process (stages, phases) and how much carries through each
Waterfall chart	How signed changes add up to a running total
Polar area and radial bar charts	Comparing a handful of categories around a circle
Scatter plot	Relationships between two or three numeric variables
Histogram	How the values of one number are distributed
Violin and ridgeline plots	How one number's values are distributed in each group: violins side by side for a few groups, ridges stacked for more
Beeswarm chart	Many groups (stores, counties) as one dot each along a measure, in a swarm per group above them
Calendar heat map	A number for each day, colored on a calendar to show weekly and seasonal patterns
Bullet chart	Each category's number against its target (quota, goal, budget), on one scale
Dumbbell chart	Each category's value in two series (two years, say), joined across the gap between them
Population pyramid	A population split in two (women and men) over ordered bands such as age
Fan chart	A forecast as a line with its intervals around it, the widest lightest
Parallel coordinates	Many numbers per row, a line per row across an axis for each
Gauge	One number on a dial, when you ask for one
Candlestick chart	Prices over time: each period's open, high, low and close, with the volume traded
Heat map	Two-dimensional comparisons using color intensity
Sankey and chord diagrams	Flows between two groupings (origin to destination, from to to), sized by a measure or the row count
Network and ring diagrams	Relationships between the values of two groupings, as linked nodes
Radial heat map	Circular heat map for cyclical or compact data
Radar chart	Comparing multiple metrics across categories
Map	Geographic data on an interactive map
Table	The rows themselves

Editing a Visualization

Open any saved visualization and use the Admin settings panel on the left. Change its title in the Title section, its type with Change chart type under Visualization, and its data with Edit query under Data (then Update chart); other sections cover the legend, axes, values, and more. Click Save at the top of the page to keep your changes, or Discard to drop them.

The Colors section picks the chart's Palette, sets Series colors (or one Color for a single series), and can Emphasize one series, keeping it in color and graying out the rest. Use patterns in addition to color in Accessibility helps readers who can't tell colors apart.

Version history in the More visualization actions menu lists every saved version, with Undo, Redo, and Restore to go back to one.

Sharing & Embedding

Click Share below the chart and turn the switch on to make the visualization shared:

Share URL — Copy the direct link. Anyone with it can view the visualization; no login is required.
Embed Code — Copy the generated <iframe> snippet to embed the chart in any webpage.
List on Explore — Show the visualization on the Explore page so other users can discover it.

Private visualizations can't be opened by link or embedded, but you can still give individual people view access under Share with people: type a name or email in Add people, pick the person, and click Share. No email is sent, so let them know yourself.

Examples. Organization admins can share a visualization or slide deck as an example with every workspace in the organization, and SlateData shares some with everyone: open its Share dialog and choose who under Share as an example. An example can only use organization or SlateData datasources. Other workspaces find it under Examples, open it read-only, and use Copy to workspace to make an editable copy (a deck's visualizations are copied with it). Switching off a datasource an example uses hides the example too.

Data Source and Query

Below the chart, click the datasource name (or View query) to see where the data came from, when it was fetched, how many rows it has, and the SQL that produced it. Use Download to get the data as CSV, Excel, JSON, TSV, or Parquet, or the chart as an image.

Verified Visualizations

Verifying a visualization tells readers someone checked its data, SQL and chart and that they're accurate to the best of their knowledge. People who can edit it choose Verify visualization from the More visualization actions menu (save or discard any changes first), then Verify.

A Verified badge shows who verified it and when.
Its data doesn't refresh while it's verified, so the numbers stay the ones that were checked.
Saving a change asks whether to Save and verify or Save without verifying; any change otherwise removes the verification, and so does undoing or restoring a version.
Remove verification in the same menu takes it off and fetches the latest data.