8 Tips to Make Your Data Visualization More Engaging & Effective

8 Tips to Make Your Data Visualization More Engaging & Effective

Instead of telling people about a story, data, or information, show them. Here are tips to make your data visualization more engaging and effective.

Create data visualizations: RAWGraphs in 8 minutes (Michele Mauri)

Video related to Polimi Open Knowledge (POK)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

How to Create Effective Data Visualizations – Quick Tutorial with Examples

Want to create better data visualizations and view all your metrics in a full story, in a shareable dashboard?

Check out this step-by-step tutorial in which we:

Address the basic terminology for data visualizations and their effectiveness

Talk about data storytelling and why it’s so beneficial for all businesses

Provide data visualization examples and easy-to-use steps you can make to start creating visualizations and sharing them with your team in minutes

Want to dig even deeper? Check out our blog on Data Visualization in R: https://www.slingshotapp.io/blog/data-visualization-in-r

For more specific tutorials and free insights from data experts, follow us on social media or check out our upcoming webinars here: https://www.slingshotapp.io/webinars  

Want to benefit from a free trial of Slingshot? Nothing easier than that – your journey starts here: https://www.slingshotapp.io/

Why Your Data Visualizations are Bad (and how to improve them!)

In this video we walk through some examples of what not to do when creating visualizations.

The themes that come out of the examples are:
– Avoid information overload
– Don’t be misleading
– Make your graphs easy to read

Next we address techniques to fix these common issues. Some strategies to implement include stepping your audience one-by-one through components of a graph, smartly using coloring & opacity to highlight what’s important, and maximizing your data-ink ratio.

Some other tips can be summarized as:
– Line charts are good for showing trends over time (but avoid spaghetti graphs!)
– Bar charts are best to highlight differences between categorical variables
– Generally avoid pie charts, donut charts, and 3d charts

In preparing for this lecture, a few different sources were consulted…

Storytelling with Data (Cole Nussbaumer Knaflic): https://www.storytellingwithdata.com/books
How to Speak (Professor Patrick Winston): https://youtu.be/Unzc731iCUY

Other resources:

Keith’s YouTube channel: https://www.youtube.com/@keithgalli
Reddit (Data is Beautiful): https://www.reddit.com/r/dataisbeautiful
Reddit (Data is Ugly): https://www.reddit.com/r/dataisugly

Video timeline:
0:00 – Introduction & video overview
1:24 – 1. Avoid Information Overload
4:42 – 2. Don’t be misleading
6:44 – 3. No hard-to-read graphs
8:15 – Fix information overload (step through components one-by-one)
10:30 – Strategic use of color & opacity
12:05 – Maximize the data-ink ratio
14:23 – Being honest with your visualizations
15:42 – Improving hard-to-read visuals (graph selection, z-pattern)
17:55 – Resources used to prepare this lecture
20:07 – Final thoughts!

Free Dataiku Learning Resource:

Twitter: https://twitter.com/dataiku
Instagram: https://www.instagram.com/dataiku/

From LEARN Media

Data Visualization: 9 Actionable Tips You Can Use Now

Want to create engaging reports and dashboards? Here are 9 data visualization tips you need to be using…
Tip #1: Consider the context
Tip #2: Use the right chart
Tip #3: Use the right ordering
Tip #4: Include comparisions
Tip #5: Keep it simple
Tip #6: Consider color
Tip #7: Explain the data
Tip #8: Tell a story
Tip #9: Choose the right tool


Create a social dashboard using Google Data Studio: https://www.youtube.com/watch?v=_OAgw3S4DPs
Google Data Studio tutorial: https://www.youtube.com/watch?v=zHpxMIiJrTA



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