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Vincent von BürenHead of DataViz Squad @ Adbirds
ERETAIL Europe 5th October 2016
Use Data Visualisation to Unleash the ”Force” of your Data
Preparation is everything!
CHRISTMAS TIME, yeah!
Shit…
Challenge I
Region Jan Feb Mar Apr May Jun Jul Aug Sep Okt Nov Dec
Domestic 1985 2084.3 2188.52 2297.95 2412.85 2533.49 2660.16 2793.17 2932.83 3079.47 3233.44 3395.11
International 572.15 583.6 595.27 607.18 619.32 631.71 644.34 657.23 670.37 683.78 697.46 711.41
Total 2557.15 2667.9 2783.79 2905.13 3032.17 3165.2 3304.5 3450.4 3603.2 3763.25 3930.9 4106.52
https://docs.google.com/spreadsheets/d/1x5t7GukZavCMo7306kzVb8cwZrNxfaG5HqoKccWcp0M/edit?ts=57f2d7f7#gid=0
Challenge II
The more “sophisticated” approach:
Challenge…accepted!
What is Data Visualisation?
Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. With interactive visualization, you can take the concept a step further by using technology to drill down into charts and graphs for more detail, interactively changing what data you see and how it’s processed.
Source: wiki.com
A “brief” definition…
René Descartes, the godfather of Data Visualisation
William Playfair, the founder of Data Visualisation
Thanks, guys!
Why is Data Visualisation so important?
Digital World = A lot of Data
Visual Cortex“Seeing”
Cerebral Cortex“Thinking”
HOMINES SUMUS NUN DEINumber
523122555355
Explore YOUR Data!
Tell your Story!
How to do Data Visualisation?
GARBAGE IN –GARBAGE OUT
No CHART CHUNK!
1. Understand your audience
2. Think about the goal of your visualisation
3. Make your story/explanation
4. Select the right visualisation type
5. Simplify large data sets and make them coherent
6. Play with your data
7. Combine data sets and examine your data
The „Rules” of Data Visualisation
Visualize, you must!
Pre-process data
What type of data do I have?
What do I want from my data?
Pick appropriate technique/tools
See Results
Unsatisfied
Change goals
Change perspective
Data is dirty!
FOR DEVELOPERS
= D3.js
= Chart.js
= Google Charts
= Tableau
= BIME
= Microsoft Power BI
= Sisense
FOR NON-DEVELOPERS
Collaborative sense-making
Improved human-computer interface devices
More & powerful data visualisation tools
Interactive predictive visual models
Tighter integration of data mining algorithms
More data, more fun
http://twitter.github.io/interactive/sotu2014/#p1
http://www.informationisbeautiful.net/visualizations/gender-pay-gap/
Summary
THANK YOU VERY MUCH!