Communicating Data and Visualizations

Where do we spend the most time?

Traditional Data Visualization, number 2

Declarative and data driven

Where do we spend the second most time?

Idea illustration of processes or framework, number 1

Declarative and conceptual

Where do we spend the least time?

Idea Generation, number 3

Conceptual and exploratory

Qualitative data

Categorical

Qualitative measures

nominal, ordinal, proportion

Quantitative data examples

ratio, interval, discrete, continuous, distributions

Ratio

Defines 0 as the absence of something ex. cash

Interval data

where 0 is just another number ex. temperature

Discrete data

shows only whole numbers ex. points in a basketball game

Continuous data

shows numbers with decimals, ex. height

Distributions

describe the mean, median, and standard deviation of the data

Declarative visualizations

used to present findings, financial results

Exploratory visualizations

used to gain insights while you are interacting with data, ex. identifying good customers

Idea illustrations of processes or frameworks #1

-Processes diagrams and infographics

-Metaphorical

-Used in presentations

-Goal is for simplifying concepts and processes

Traditional data visualizations #2

-Conventional charts

-Static

-Used in formal presentations or reports

-Goal is too affirm concepts and set context

Idea Generation #3

-More complex, undefined visualizations

-Metaphorical and creative

-Used in working sessions for brainstorming

-Goal is for discovery, simplification, and learning

Visual Discovery #4

-More complex, unconventional visuals

-Dynamic and interactive

-Used in working sessions, testing, analysis

-Goal is for trend spotting, sense making, deep analysis

Qualitative Proportional Data Charts

-Bar

-Pie

-Stacked bar

-Tree maps

-Heat maps

-Symbol maps

-Word clouds

Quantitative data charts

-Line

-Box and whisker

-Scatter

-Filled geographic maps

Comparisons

bar chart, pie chart, stacked bar chart, tree map, heat map

Geographic data

Symbol map

Text data

Word cloud

Outlier detection

box and whisker plot

Relationship between two variables

Scatter plot

Trend over time

Line chart

Geogrpahic data

Filled map

Improving your charts comes down to choosing an appropriate ______ and ________ effectively

Scale, colors

Scale and increment considerations

How much data do you need to show?

What do you do with outliers?

What is the baseline? 0? Something else?

Would context or reference lines make the it more meaningful?

Color considerations

What do they mean?

What would help people with disabilities?

Should certain ones be used for positive outcomes?

Bad examples and bias

overemphasizing the better update with scaling issues

Interesting in business writing

pointing out what they need to focus on

Identifying the problem (I)

What is the purpose?

Master the data

Problems we hd, give enough information

Perform test plan, address and refine results

What type of analysis you did, be clear about the model you did

Communicate insights

Discuss what the visual is telling you, but it should explain itself, slicers are good for this. Describe items that are interesting

Trace outcomes

Whats next? (Sometimes)

Tips for effective writing

1. Know your audeince

2. Know your message

3. Think like a reporter

4. Banish buzzwords and cliches

5. Junk the jargon

6. Keep it tight

7. Keep it plain and simple

8. Leave the symbols and abbreviations on your phone

9. Get active, not passive

10. Proofread