7 tips for more effective data visualization

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7

Tips for Effective Data Visualization


In today’s data-driven world, how data is shown and shared determines its impact and effectiveness. Plotting data into charts and graphs isn’t enough. Effective data visualization takes skill and storytelling, an eye for detail, and an understanding of your audience. Use these 7 tips for great data visualizations and no other set of charts.

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1

Determine the story you want your data to tell Understand the data you’re working with and determine what story you want to tell. Ask a few questions - if required. Don’t forget your visual story will drive understanding, discussions and decision-making. WHAT STORY DO YOU WANT TO TELL? Use Outliers to illuminate deviators from others

Highlight Trends to indicate changes over a period

Showcase Patterns for repeated consistent characters

Portray Correlations for establishing relationship between 2 or more variables

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2

Choose the right kind of visualization to represent data Choose one or more or a combination of the four fundamental types of data visualizations. Each of it delivers specific insights. FREQUENTLY USED FOR

Spot trends COMPARISON VISUALIZATIONS

Classifying curtrent versus old Values Seeing highest versus older values

COMPOSITION VISUALIZATIONS

DISTRIBUTION VISUALIZATIONS

RELATIONSHIP VISUALIZATIONS

Classifying the relationship between data points that change over time Seeing the relative difference between parts of a whole

ANSWERS QUESTIONS LIKE

Which products / services sell the best?

EXAMPLES

Line chart

Circular area chart

Bar chart

Pie chart

Stacked area chart

Stacked bar chart

Bar histogram

Line histogram

Scatter plot

How is sales, if compared to previous years?

How big is our market share & what is the total market size? What percentage of the budget is dedicated to A, B and C?

Classifying commanalities and outliers

Total how many customers exist in a demographic range?

Seeing the general shape of a range

How many customers are late by how many days in making payments?

Portraying correlations and clusters

What is the correlation between advertising spend and sales?

Identifying outliers

Does expences and revenue have variances across regions?

Scatter plot

Scatter plot bubble size

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3

Use colors as powerful tools to enhance the visuals With help of colors, give clear cues about relative values, points of emphasis, and differentiation amongst data sets. Use colors carefully and sparingly, as inappropriate colors used can increase the confusion instead of clearing it up. DO

DON’T

USE DISTINCT COLORS FOR EACH SEGMENT OF A PIE CHART

COLOR SEGMENTS USING DIFFERENT SHADES OF THE SAME COLOR

USE DIFFERENT SHADES OF THE SAME COLOR TO DESIGNATE NUMEROUS VISUAL ELEMENTS

USE DIFFERENT COLORS WHEN DEALING WITH NUMEROUS GRAPHICAL ELEMENTS

USE THE SAME COLOR FOR EACH BAR OF A BAR CHART

USE A DIFFERENT COLOR FOR EACH BAR

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4

Avoid chartjunk situation For every visual that you create, ask “Which elements are the most important to the story that your data is trying to tell”. To adhere to this thought process: • Limit the number of visualization in a dashboard to 9 or may be less – unless the client requires it otherwise. • Add callouts to emphasize on the information critical to convey the message. • Use lot of trend lines to highlight important correlations between variables. Also ensure that the graphs are more scannable. • Use a wide plethora of size and colors to define unique data variables. • Avoid excess use of decorative fonts, text treatments such as underline, italics, and visual embellishments such as drop shadows.

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5

Adhere to design principles Bring clarity and avoid confusions while assessing complex datasets.

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DO

DON’T

ORDER SLICES FROM LARGEST TO SMALLEST for easier comparison

RANDOMLY ORDER THE SLICES

USE TRANSPARENT COLORS so each element remains visible

USE SOLID COLOR WITH OVERLAPPING DATA

USE 2D LINES to clearly convey priority and ranking

USE 3D LINES


6

Showcase data at the right scale, to make visuals correct - not attractive Improper scales can make major insights seem mediocre and minor deviations feel massive. For correct representation of the story, show data as: • Ensure that the scale of axes accurately reflects the size of data • Select the axes that best represent the trend in the data • Take care that absolute numbers or percentage makes the data clearer • Don’t use cropped axis and start the Y axis at 0

DO 300 250 200

350 300 250 200

150 100 50

150 100 50 0

0

400

TRUNCATE THE SCALE

DON’T 300

300

350 300

250

250

200

200

150 100

150

50 0

START Y-AXIS VALUE AT 0

350

350

PRO TIP: Vertical type can be difficult to read, so use horizontal labels whenever possible.

350

JAN

FEB

100

250 200 150 100 50 0

50

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7

Create visualizations keeping target audience in mind Know the audience for whom you are putting together the data in form of visualizations and what are they interested in. Clearest and best looking visuals can turn turtle, if audience does not find it interesting and engaging. Deliver persuasive story by: • Highlight & order the information, purely based on audience interest and trends. • Visualize data sets in intuitive & conventional manner as per everyone’s understanding. • Conduct dry runs to test the visuals with experienced colleagues to ensure you convey the story they are interested in.

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