Slicing / Dicing

About

About

Slicing / Dicing is a small publication for readable, interactive data stories.

We make charts, essays, explainers, and dashboards built around one clear takeaway and backed by sources. Our interactives are designed to make the data easier to follow. We like good design, but not at the cost of legibility. Every piece should tell you what matters, how to read it, and where the evidence comes from.

This page explains how we publish, how to choose what to read, and how we handle sourcing and methods.

If you’re new, start with Amuse or Starter; if you want depth, jump to Entrée or Chef’s Table; if you want trust details, go to Back of House.

Our Menu (How We Publish)

We structure our publishing like a menu so you can grab a quick bite, sit down for a full meal, or check the receipts in the kitchen.

Short Order

Low time commitment

Amuse
One chart, one surprise—fast. Designed for a quick scroll, with a single clear takeaway. ~30–60s
Starter
Fast context. We take one chart and add the guardrails: definitions, baselines, and a clear breakdown of what the data means (and what it doesn’t). ~3–5 min
Dessert
Delightful visual experiments, data toys, and micro-interactives that reward a brief pause. ~1–3 min

Main Course

High time commitment

Entrée
Deep dives—a complete, coherent explanation grounded in sources, structure, and careful analysis. ~8–15 min
Chef’s Table
Our signature interactive projects: original datasets or deeper analysis with guided scrollytelling and exploration. ~10+ min

The Regulars

Recurring updates

Prix Fixe
A periodic briefing with data signals, updates, and distilled insights, sent to your inbox when there is something worth sending.

Back of House

Trust and sourcing

We don’t ask you to trust us blindly. We leave the kitchen door open: sources, assumptions, and limitations are part of the work.

Chalkboard
Living reference pages and dashboards we update dynamically as data changes.
Recipe
Our methodology notes—assumptions, tools, and analytical choices so you can audit the work.
Pantry
The raw ingredients: datasets, data dictionaries, and source links for power users who want to run the numbers themselves.
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