Data Storytelling & Data Visualization · Self-study guide

From Showing Data to Telling a Story

Confused about what to put on a dashboard, which chart to pick, or why nobody acts on your reports? This page walks you from the basics to hands-on practice: six lessons, nine bad dashboards to fix, a what-if lab and seven exercises on choosing the right data.

Inside: 6 lessons · 9 makeovers · 6 labs · 7 exercises Data: all examples are fictional
The whole method on one screen

Six lessons turn a chart into a decision

Your tools do not know your story. The analyst does. Follow the six lessons in order, because each one builds on the last.

1Understand the context

Who decides? What should they do? Which data proves it?

2Choose the right visual

A dozen visuals cover nearly everything. Retire pies, 3D and dual axes.

3Eliminate clutter

Every element costs attention. Delete what carries no information.

4Focus attention

Grey for context, one accent colour for the point.

5Think like a designer

Make it obvious how to read it. Use words, align, leave white space.

6Tell a story

Setup, conflict, resolution, then a clear call to action.

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Start here

How to use this page

Read a lesson, check yourself, fix real bad dashboards, then practise choosing data under realistic constraints.
6lessons with rules of thumb and logistics examples
9bad dashboards to diagnose and rebuild, before and after
6what-if labs: change an input, watch the story change
7scenarios on picking data, visual and title, with scoring

Pick a learning path

20 minutes

Quick start

90 minutes

Standard

  • Read Lessons 1–6 and take each quiz
  • Diagnose 4 Clinic cases before revealing
  • Complete 3 exercises in the Studio
Half a day

Full course

  • Everything above, plus all 9 cases
  • All six labs and all seven exercises
  • Redesign one of your own dashboards with the Toolkit
1
Lesson 1 · Context

Understand the context before you touch a chart

Success starts before the visualization. Know who decides, what you want them to do, and which data proves it.

Exploratory vs. explanatory analysis

Exploratory work is how you find out what is interesting. Explanatory work is how you help someone else understand one thing you already know. The book's image: open 100 oysters to find two pearls, then show your audience the pearls, not the oysters.

ExploratoryExplanatory
GoalFind out what might be interestingExplain one specific point
AudienceYou and fellow analystsA named decision maker
OutputMany quick, rough viewsOne or two polished views with a message
Typical mistakeSending the rough views to the bossHiding the conclusion and making them re-discover it
In logisticsA pivot table with 40 filtersA weekly page that opens with "what changed, what to do"

Who, What and How

1

Who

Be specific about the audience. "Internal and external stakeholders" is not an audience; "the Operations Director who signs the lease" is. Name the decision maker, and think about whether they already trust you as an expert.

2

What

State what they should know or do: approve, fund, stop, escalate, change. If you cannot name an action, ask whether you need to communicate at all. If you present only data, people say "interesting" and move on.

3

How

Only now ask which data supports the point. The data is evidence for the story, not the story. Do not hide evidence that cuts the other way; a sharp reader will find it and doubt everything else.

Mechanism and tone

Live talk

You control pace and attention, and you are there to answer questions. Keep slides sparse and do not use them as a teleprompter.

Slideument

One file serving both a talk and a read-alone document. It satisfies neither fully; later lessons show ways around it.

Written / dashboard

The reader controls pace and nobody is there to explain, so titles, labels and notes must do the talking.

Also decide the tone: celebrating a win, lighting a fire, or reporting calmly. Tone drives later choices such as colour and layout.

Application note

A self-serve dashboard sits at the "written" end. Nobody is in the room, so each page needs a headline that says what to conclude, not just a topic label.

The Big Idea and the 3-minute story

The 3-minute story is what you would say if you only had three minutes. The Big Idea shrinks it to one sentence. Being short is harder than being long, and it frees you from depending on slides.

A Big Idea must (1) state your unique point of view, (2) say what is at stake, and (3) be a complete sentence.

Example (fictional)

"Storage demand will outgrow our current warehouse by year 3. We recommend securing additional space now, because waiting puts projects at risk; please approve the lease study."

Point of view: lease now. Stake: projects at risk. Complete sentence with an ask.

Questions to ask whoever requested the work

Storyboard on paper first

Do not start in presentation software; it pulls you into slide-making mode and makes you attached to what you built. Use sticky notes or paper so ideas are cheap to move or bin. Here is a storyboard for the fictional warehouse case.

1 · ContextWhy we forecast space: build or lease decisions are costly and hard to reverse.
2 · ProblemForecast demand crosses current capacity in year 3.
3 · EvidenceOne line chart: forecast vs capacity, gap shaded.
4 · OptionsLease now, build later, or raise utilization.
5 · AskApprove a lease study this quarter.

Busy audience that already trusts you? Move note 5 to the front and lead with the ask.

Try it: Context Canvas

Fill in what you know. The canvas drafts a Big Idea and a 3-minute story skeleton and tells you what is still missing. Nothing leaves your browser.

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Lesson 2 · Choose a visual

Pick the chart your audience can read fastest

A dozen visual types cover nearly every business need. The right one is whichever is easiest for your audience to read.

Tables interact with our verbal system: we read them. Graphs interact with our visual system, which is faster. That one idea explains most of the advice below.

Choose by the message, not by the tool

Try it: Chart Picker

Choose what you want to say. The picker recommends a visual and tells you what to avoid.

Four visuals to retire

Pie chart

Eyes cannot judge angles and areas well. When slices are close, you cannot rank them at all.

Swap: sorted horizontal bars. Try it in Lab B.

Donut chart

It asks readers to compare arc lengths, which is harder still than a pie.

Swap: a bar, or just the number.

3D

Use 3D only if you truly plot a third dimension. Otherwise it skews values; in the book a bar of 1 reads as about 0.8.

Swap: flat 2D.

Secondary y-axis

Readers must work out which axis each series uses, and the pairing implies a relationship that may not exist.

Swap: direct labels or two panels sharing the x-axis. Try Lab C.

If you still want a pie

Pause and ask why. If you can answer, label the values and keep it flat. It should never be the first chart you reach for.

Rules for the two workhorses

Bar charts

  • Zero baseline, always. Eyes compare bar ends, so a truncated axis fakes a difference. Test it in Lab A.
  • Bars wider than the gap between them, but not so wide that readers compare areas.
  • Natural order if one exists (age bands, months); otherwise sort, biggest or most important first.
  • Horizontal bars when labels are long: text reads left to right and the label comes before the data.
  • Stacked bars: only the bottom segment shares a baseline, so put the series you care about there.

Line charts

  • Use for continuous data, usually time. The line implies the points are connected.
  • Keep time steps even. Mixing decades and single years distorts the shape.
  • A non-zero baseline is allowed, but say so and avoid over-zooming tiny changes.
  • Show forecast as a thinner dotted line with light shading, never as the same solid line as actuals.
  • Label lines directly instead of using a legend.

Tables

Great for mixed audiences who each look up their own row, or when units differ. Let the data lead: light or no borders, right-aligned numbers, consistent decimals. In live talks, a table pulls attention away from you.

Axis or data labels?

If the big-picture trend matters, keep a light grey axis. If exact values matter, label the data points and drop the axis, because showing both is redundant.

Ethics

Manipulating a scale because it supports your point is not acceptable, and it is risky: one discerning reader spots it and your credibility goes with it.

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Lesson 3 · Clutter

Clutter is your enemy

Every element you add costs your audience brain power. Keep what carries information; delete what does not.

Cognitive load

The mental effort needed to take in new information. Extraneous load is effort that does not help understanding.

Perceived load

What matters most is how hard your audience believes it will be. Decided in a glance, often unconsciously. If it looks hard, many will not try.

Signal vs. noise

Signal is the message; noise is anything that does not add to it, or detracts. Maximize the share of ink spent on data.

Gestalt principles: how people group what they see

These six principles tell you what viewers will group together, and therefore which extra elements you can safely remove.

Proximity

Things close together belong together. Use: group related KPIs; put labels next to the data they describe.

Similarity

Same colour, shape or size means related. Use: colour a label like its line; no borders needed to show rows.

Enclosure

Things inside a boundary form a group, even a faint one. Use: light shading to separate forecast from actuals.

Closure

We fill gaps to see a whole shape. Use: delete chart borders and background fills; the chart still looks complete.

Continuity

Eyes follow the smoothest path. Use: drop the vertical axis line; aligned labels and bars imply it.

Connection

Connected things are grouped, even across colours. Use: lines in a line chart link points into a series.

Visual order: alignment, white space, contrast

Alignment

Create clean lines. Left-align text; centre-aligned blocks leave ragged edges and look sloppy. Put the title, axis title and legend top-left so readers learn how to read before they see data. Avoid diagonal text: one study the book cites found 45° text about 52% slower to read and 90° text about 205% slower.

White space

People fear empty space, but it works like a pause in a talk. Keep margins clear, do not stretch charts to fill the page, and never add data just because there is room. If one thing matters most, make it the only thing on the page.

Contrast

It is easy to spot a hawk in a sky of pigeons, and hard when there are many kinds of birds. The more things you make different, the less any one stands out. Use contrast only for the point.

Declutter in six moves

1

Remove the chart border

Closure: the chart still reads as a whole.

Deleteborder
2

Remove gridlines

Or make them thin and light grey so they never compete.

Deletegridlines
3

Remove data markers

The line already shows the data; use markers on purpose, not by default.

Deletemarkers
4

Clean up axis labels

Trim trailing zeros, abbreviate months, keep text horizontal.

Trimlabels
5

Label data directly

Proximity: put the name next to the line and drop the legend.

Labeldirectly
6

Use consistent colour

Similarity: colour the label like its data.

Matchcolours
Exception: redundancy that helps

Keep $, % and thousands separators on the numbers themselves. A chart titled "$ millions" with bare axis numbers forces the reader to remember the unit.

Play with all six moves in the Declutter lab →

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Lesson 4 · Focus

Focus your audience's attention

Use size, colour and position sparingly so people look at what matters before they know they are looking.

How people see and remember

Iconic memory

Lasts a fraction of a second and is tuned to differences. This is where preattentive attributes act.

Short-term memory

Holds about four chunks at once. Ten coloured series plus a legend overload it. Label directly and group information into larger chunks.

Long-term memory

Pictures help recall words, and repetition helps things stick. Pair visuals with words.

Preattentive attributes

These are features the brain notices without effort. Some can encode quantity; others only separate categories.

AttributeQuantity or category?Dashboard use
Position, line lengthQuantity can encode valueWhy bars and lines are easy to read.
Line width, size, colour intensityQuantity to a limited extentSize signals importance; saturation makes a heatmap.
Colour hue, shape, orientation, curvature, enclosureCategorySeparate series or highlight one; "which is greater, red or blue?" is meaningless.
Added marks (labels, markers, underline)Category"Look here" signals, for example a marker and label on the last point.
Bold, italics, underline (text)CategoryBold is the cleanest; italics are mild; underline adds noise.
Motion, blinkingAvoidFlashing is more annoying than helpful. In a live talk, a simple appear/disappear build can guide attention; avoid fly-ins and fades.

The recipe: everything grey, then one accent

  1. Push everything to the background. Grey axes, grey labels, grey context series.
  2. Make the data stand out. Data bolder and larger than axes and labels.
  3. Choose the one thing. One series, one bar or one quadrant carries the accent colour.
  4. Add marks sparingly. Label only the points that tell the story; labelling all of them creates a cluttered mess.
  5. Say it in words. Make the title name what to look at, and match its colour to the data it describes.
The "where are your eyes drawn?" test

Finish the visual, look away, look back, and note where your eyes land first. Ask a colleague to talk you through it. If they land elsewhere, change the emphasis.

Highlighting has a cost

Highlighting one point makes the others harder to see, so avoid it during exploration. Also keep highlighted elements to a small fraction of the design; the book cites a guideline of at most about 10%.

Colour rules

Use sparingly and consistently

A rainbow means nothing stands out. Keep one scheme across the whole communication so readers learn that, say, copper means "look here". Change colour only to signal a real change. If regions have colours, keep them the same everywhere.

Grey base
Accent
Positive / info
Problem

Design for colour blindness

Roughly 8% of men and 0.5% of women have trouble with red and green. Avoid putting them side by side, or add a second cue such as bold, saturation, or a + / − sign. Blue and orange are a safe positive/negative pair.

Mind the tone

Colour sets the mood. A clinical report and a light feature need different palettes. Check cultural meanings of colours for international audiences.

Brand colours

Pick one or two brand colours as your "look here" cues and keep the rest grey. If the brand colour is too pale to stand out, use bold black or another colour that does not clash.

Size and position

Size = importance

Give equal-importance items equal size. The book recounts a dashboard where the data that happened to be available took about 60% of the space and nearly steered the decision. Make design a decision, not an accident.

Position = reading order

Without cues, readers start top-left and zigzag in a "Z". Put the most important thing top-left, and do not fight habits such as negative on the left, positive on the right.

Feel preattentive attributes yourself in the Count-the-3s lab →

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Lesson 5 · Think like a designer

Make it obvious how to read it

Form follows function: decide what the audience must do with the data, then design so they can do it with ease.

Affordances: the visual says how to use it

A door handle shows you to pull. A good visual shows you where to look. Three moves create that.

1

Highlight the important stuff

Layer size, colour and bold on the one thing that matters. Keep the highlighted share small.

2

Eliminate distractions

Ask of every item: would removing this change anything? If not, remove it. Summarize detail the audience does not need; move the rest to an appendix.

3

Create a visual hierarchy

Order things by importance with size, colour and position. Super-categories (for example Age / Region / Income) give readers a frame.

Accessibility: usable by people with different skills

Do not overcomplicate

Research the book cites found that instructions in a fussy font were judged harder, and people were less likely to try them. The more complicated it looks, the less likely people are to spend time on it.

  • Use one legible font and size.
  • Prefer simple words; spell out acronyms on first use.
  • When unsure, choose the simpler option.
  • If readers struggle, the design is at fault, not the reader.

Text is your friend

Every chart needs a title and every axis needs a title. State the conclusion in words, because two people can read the same chart and conclude differently. Annotate to explain a spike, a policy change or an outage.

Rare exception: when you want readers to focus on peaks and valleys rather than the exact metric, you may drop the vertical axis labels deliberately.

Action titles beat topic labels

The title is prime real estate. Use it for the conclusion or the ask.

Descriptive (topic label)Action title (conclusion)
Inbound OTIF by weekInbound OTIF fell below the 90% target in 3 of the last 4 weeks
Warehouse utilizationZones A and C exceed the 85% planning ceiling; B and D have room
Vessel waiting time, Q3Vessel waiting time doubled in Q3, mostly because the berth was occupied
Spend by vendorThree vendors take 60% of spend: consolidate before contracts renew
Incident trendIncidents in Area 3 rose for four straight months; other areas are flat
Receiving team capacityReceiving has trailed inbound volume since June; two backfills would close the gap

Try it: Action Title Checker

Teaching heuristic

These checks are my own rules of thumb for practice. They cannot judge whether your title is true or useful.

Aesthetics: pretty is functional

People rate attractive designs as easier to use, accept them more readily and tolerate their flaws. Three habits create it without being a designer: use colour deliberately, align elements on clean lines, and use white space on purpose. When you meet a chart you like, ask why, and keep a library to borrow from.

Winning acceptance for a new design

Familiarity breeds comfort, so even better designs meet resistance. Four tactics help.

Explain the benefit

Say why it will look different and what readers gain.

Show side by side

A before and after makes the improvement visible.

Offer options

Create two or three versions and ask for input.

Recruit an ally

Win over an influential reader one to one.

If resistance persists, test with someone neutral: the problem may be your design, not their habits.

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Lesson 6 · Tell a story

Give the data a beginning, a middle and an end

Stories stick in ways facts alone do not. Build tension between what is and what could be, then end with a clear call to action.

The three-act structure applied to a data story

Beginning · Plot

Set the stage and answer "why should I care?" Five questions help:

  • Setting: when and where?
  • Main character: your audience
  • Imbalance: what changed?
  • Balance: what should happen?
  • Solution: how do we get there?
Middle · Twists

Build the case for "what could be":

  • Background and external comparisons
  • Examples and data that show the problem
  • What happens if nothing changes
  • Options and the benefits of your pick
  • Why they are the right people to act
End · Call to action

Say exactly what you want them to do. A classic close ties back to the opening problem and restates the urgency.

Why bullets alone fail

A deck of bulleted facts persuades only intellectually, and the audience argues with you in their heads. A story joins an idea to an emotion and gives people a reason to act. If you think "I have no problem to frame", look again: conflict is what holds attention, and a story where all is well rarely moves anyone.

Narrative flow: choose the order

OrderWorks best when…How
ChronologicalYou must build credibility, or the audience cares about your methodProblem → data → analysis → finding → recommendation
Lead with the endingThe audience already trusts you, is busy, or wants the "so what"Start with the ask, then back up with the strongest evidence

Tell a live audience which structure you are using ("I will start with what I need from you"). In a written report, the words on each page must make the point on their own.

Four tactics to check the story is clear

Horizontal logic

Read only the slide or section titles. Together they should tell the whole story. This needs action titles. An executive summary up front, mirrored by the titles that follow, makes the path visible.

Vertical logic

Everything on one page reinforces everything else: title supports visual, words support chart, nothing unrelated. Cutting or moving to an appendix is as important as adding.

Reverse storyboarding

Flip through the finished deck and write the main point of each page. The list should look like your original storyboard. If not, move, add or remove pages.

A fresh perspective

Give it to someone with no context and ask what they notice, what matters and what is unclear. You are too close to see it as your audience does.

Repetition: Bing, Bang, Bongo

1

Bing

Tell them what you are about to tell them: an executive summary.

2

Bang

Tell them: the detailed content.

3

Bongo

Tell them what you told them: recap, with the action you need.

Short, repeatable sound bites help your message travel without you.

Try it: Story Sequencer

These six headlines belong to one deck, but they are shuffled. Click them in the order that makes the best story. Reading only the headlines is the horizontal-logic test.

Your sequence

    Application note · dashboards are stories told in layers

    A good dashboard page works like a short story you can read at three depths: a headline that states the conclusion, a few supporting visuals that show why, and detail on demand for those who want to check. The Toolkit shows a page layout built this way.

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    Practice · Bad Dashboard Clinic

    Nine bad dashboards, diagnosed and rebuilt

    Bad visuals are everywhere, and nobody sets out to make one. Learn to spot the flaw, then fix it with the six lessons.
    1

    Diagnose first

    Study the "before". Tick every flaw you can see. Be careful: some listed flaws are decoys.

    2

    Check your diagnosis

    Correct ticks go green, wrong ticks red, and missed flaws amber, each with a reason.

    3

    Reveal the makeover

    Switch to "After" and read what changed. Each flaw is tagged with the lesson that fixes it.

    Reminder

    All data in the cases is fictional. Titles in the "after" views are computed from the data shown, so the claims match the chart.

    Nine patterns, one pattern language

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    Practice · What-if Lab

    Change one thing and watch the story change

    The data stays the same in every lab. Only the design choices move, which shows how much power the designer holds, and the responsibility that comes with it.

    Lab A · Where does the axis start? Lesson 2

    Five hubs hit between 93.8% and 96.1% on-time delivery. Slide the baseline of the bar chart and compare what the eye sees with what the numbers say.

    Lab B · Pie or bar? Lesson 2

    Enter the share of delays by cause (any numbers; they are converted to percentages). Try to rank the pie slices, then look at the bars.

    Lab C · Same data, two stories on a dual axis Lessons 2, 4

    Monthly volume (bars, left axis) and on-time departures (line, right axis). Move the right axis range and the relationship appears to change. The numbers never do.

    Lab D · Declutter and focus Lessons 3, 4, 5

    Inbound pallets received vs. processed per day, by month. Toggle clutter on and off, then add focus aids. Notice when the story becomes visible.

    Clutter

    Focus aids

    Lab E · Count the 3s Lesson 4

    Two rounds, same task: count how many times the digit 3 appears. In round 2 one visual cue is added. Your own time is the data. Results vary by person and screen; this is a demonstration, not a study.

    Lab F · One dataset, three audiences Lessons 1, 5, 6

    Late deliveries by hub over the last four weeks. Pick the audience: the data stays put, but the headline, the highlight and the ask change with the decision maker.

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    Practice · Exercise Studio

    Which data actually belongs on the dashboard?

    For each scenario, choose what to show, pick the main visual, and pick the headline. The hardest part of a good dashboard is leaving things out.
    How scoring works

    Each exercise scores 100 points: 50 for the data you pick, 25 for the visual and 25 for the title. For data, each core item you include earns full credit, supporting items earn half credit, and noise or misleading items cost points. Missing a core item costs you the points that item would have earned.

    Teaching heuristic This is my own scoring scheme for practice. In real projects, the right answer depends on your audience and decision, so use the explanations, not the number.

    0 / 7exercises scored
    –average score
    –best score
    10
    Apply · Toolkit

    Take it back to your own dashboards

    Use a layout that tells the story in layers, run the pre-flight checklist, then storyboard on paper before you open your tool.

    Anatomy of a story-first dashboard page

    Action title: the conclusion in one sentence, with a number Subtitle: scope, period, definition 1 KPI that missed target82%vs target 85% Supporting KPI92%vs target 90% Supporting KPI96%vs target 95% 2 Main visual: shows WHY (one accent, grey context) Annotation explains the cause 3 Secondary visual: where 4 Detail on demand: drill-through table, definitions, data source and refresh time 5
    1. Headline. The conclusion or the ask, top-left, where eyes land first.
    2. One to three KPIs with a target and a trend. Only the one needing attention gets the accent colour.
    3. Main visual. Answers "why", with grey context and one highlighted series.
    4. Secondary visual. Answers "where" or "who".
    5. Detail on demand. Definitions, tables and filters for people who want to verify.

    Application note This layout is my application of the book's lessons to dashboards, not a template from the book.

    Pre-flight checklist

    0 of 0 checks done

    Blank storyboard (print this)

    Audience


    Big Idea (one sentence)


    Setup


    Conflict / evidence


    Resolution / options


    Call to action


    Glossary

    TermMeaning
    Explanatory analysisCommunicating one specific message to a specific audience.
    Big IdeaOne complete sentence with your point of view and what is at stake.
    3-minute storyWhat you would say if you had three minutes.
    StoryboardA visual outline of the communication, made on paper first.
    SlideumentOne file that tries to be both a presentation and a document.
    Cognitive loadMental effort needed to take in information.
    Signal-to-noiseShare of what you show that carries the message.
    Gestalt principlesHow people group things: proximity, similarity, enclosure, closure, continuity, connection.
    Preattentive attributesFeatures noticed before conscious thought, such as colour, size and position.
    Visual hierarchyOrdering elements by importance so readers know where to look first.
    AffordanceA cue that shows how something is meant to be used.
    Action titleA title that states the conclusion or ask rather than the topic.
    SlopegraphA line chart of two time points that shows direction and rate of change across categories.
    Small multiplesSeveral small charts with identical axes, placed side by side.
    Horizontal logicReading only the titles tells the story.
    Vertical logicEverything on one page supports its title.
    Reverse storyboardingSummarizing each page of the finished piece to compare with the plan.

    Where to go next

    Books the author recommends

    • Resonate, Nancy Duarte
    • Show Me the Numbers, Stephen Few
    • The Visual Display of Quantitative Information, Edward Tufte
    • Beyond Bullet Points, Cliff Atkinson
    • The Functional Art, Alberto Cairo
    • Data Points, Nathan Yau

    Blogs and sites the author lists

    • storytellingwithdata.com
    • Eager Eyes · Flowing Data · The Functional Art
    • Junk Charts · Perceptual Edge · Visualising Data · VizWiz
    • HelpMeViz · Make a Powerful Point
    • FiveThirtyEight Data Lab · The Guardian Data Blog
    Final challenge

    Pick one dashboard you own. Write its Big Idea, run the checklist, rebuild the top page with a headline, one accent colour and no legend, then show it to someone who has never seen it. Where their eyes go first tells you whether it works.