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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

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Subject: ERETAILER/FAASend to: analyticsgermany@adbirds.global

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