Abstract: Data Visualization describes the process of transferring data into images on the computer. Only using images, humans are able to get insights into large amounts of data - which makes data visualization a very important part of data analytics. However, there are a lot of techniques and tools available - and which ones are suited best for which tasks? Also, the process of creating a data visualization, selecting the right visual mappings, colors, chart types, etc, is very complex and can also confuse viewers, if not done properly. In this talk, I will reflect on current developments in data visualization research and how data visualization can be used in a data science workflow. Speaker Bio: Dr. Johanna Schmidt is head of the research unit “Visual Analytics” at VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH in Vienna. She received her Master’s degree in Computer Science and afterward continued with a Ph.D. in data visualization at TU Vienna, Austria. Her current research focuses on the visual analysis of large datasets, mainly manufacturing data originating from industry companies and time series data. Additionally, she is a lecturer at the TU Vienna and at the FH Salzburg. https://www.meetup.com/de-DE/predictive-analytics-for-industry-4-0/

1. What is data visualization, and how to
integrate it in a data science workflow?
Johanna Schmidt
VRVis Research Center
Vienna, Austria

2. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
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http://vda-lab.github.io/2019/12/vegalite

3. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
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https://powerbi.microsoft.com/en-za/blog/power-bi-on-the-go/

4. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
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https://blog.iao.fraunhofer.de/daten-retten-leben-corona-ausbreitung-endlich-verstaendlich-und-in-echtzeit/

5. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
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https://datavis-online.github.io/organisation.html

6. Johanna Schmidt Predictive Analytics for Industry 4.0
VRVis Fast Facts
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Research Center
 Founded in 2000 as Center
 Since 2010 financed by in
Mission: R&D in Visual Computing
 Data visualization, Visual Analytics, AI, Data Science
 Connection between Science and Industry
Legal organization: GmbH, Non-profit
 Ares Tower in Vienna, 1220 and TU-Graz, 8010 Graz
 Budget von ~7 M€ (2019), ~70 Employees

7. Johanna Schmidt Predictive Analytics for Industry 4.0
VRVis Solutions
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8. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
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https://de.wikipedia.org/wiki/Anscombe-Quartett

9. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
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https://de.wikipedia.org/wiki/Anscombe-Quartett

10. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
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https://de.wikipedia.org/wiki/Anscombe-Quartett

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Visual Data Analysis
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https://www.autodesk.com/research/publications/same-stats-different-graphs

12. Johanna Schmidt Predictive Analytics for Industry 4.0
Why Data Visualization?
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13. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Uni- to multivariate Data
 Complex datasets require complex representations
Data Visualization Research
 New data visualization techniques
 Interaction techniques
 Summarization/aggregation

14. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
https://upload.wikimedia.org/wikipedia/commons/1/1d/Example_histogram.png

15. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
 Bivariate Data
https://en.wikipedia.org/wiki/Scatter_plot

16. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
 Bivariate Data
 Trivariate Data
https://i.stack.imgur.com/6kFx8.png

17. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
 Bivariate Data
 Trivariate Data
 Multivariate Data
http://i.imgur.com/ggQMO8z.png

18. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
 Bivariate Data
 Trivariate Data
 Multivariate Data
http://www.unige.ch/ses/sococ/cl/r/scatmat.e.html

19. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
 Bivariate Data
 Trivariate Data
 Multivariate Data
https://harmoniccode.blogspot.com/2018/02/friday-fun-lix-parallel-coordinates.html

20. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
 Univariate Data
 Bivariate Data
 Trivariate Data
 Multivariate Data
http://www.corentindupont.info/blog/posts/Others/2015-09-18-no-spider.html

21. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Chart Suggestions
 From Data to Viz
https://www.data-to-viz.com/

22. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Chart Suggestions
 Data Visualization Catalogue
https://datavizcatalogue.com/search.html

23. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization in Predictive Analytics
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Analytics Workflow
 Several steps necessary
 How to integrate data visualization?

24. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization in Predictive Analytics
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Jeffrey Heer, Capstone Talk EuroVis 2019: http://eurovis2019.tecnico.ulisboa.pt/wp-content/uploads/2019/06/EuroVis2019-Capstone.pdf

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Data Visualization in Predictive Analytics
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26. Johanna Schmidt Predictive Analytics for Industry 4.0
Collect / Wrangle / Annotate
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Collect:

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Collect / Wrangle / Annotate
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Annotate:

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Data Visualization in Predictive Analytics
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29. Johanna Schmidt Predictive Analytics for Industry 4.0
Explore / Profile
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Explore / Profile
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31. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
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Data Exploration
 Understanding data structure
 Detect new patterns
-> DEMO

32. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization in Predictive Analytics
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33. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
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Regression Feature Evaluation
 Understand variable influence
 Evaluate model prediction results

34. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
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Regression Feature Evaluation
 Understand variable influence
 Evaluate model prediction results
-> DEMO

35. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
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Evaluation of AI Model Results
 Understand relation between input and parameters
 Avoid over/underfitting
 Study model bias
-> Explainable AI

36. Johanna Schmidt Predictive Analytics for Industry 4.0
Explainable AI
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https://distill.pub/2018/building-blocks/

37. Johanna Schmidt Predictive Analytics for Industry 4.0
Explainable AI
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http://playground.tensorflow.org

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Explainable AI
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“What-If Tool” by Google
https://ai.googleblog.com/2018/09/
the-what-if-tool-code-free-probing-of.html

39. Johanna Schmidt Predictive Analytics for Industry 4.0
Datenvisualisierung in Predictive Analytics
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40. Johanna Schmidt Predictive Analytics for Industry 4.0
Report
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https://hevodata.com/learn/top-10-best-power-bi-dashboard-examples-in-2021/

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Data Visualization in Predictive Analytics
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42. Johanna Schmidt Predictive Analytics for Industry 4.0
Tools
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Data Visualization Tools
 Programming libraries
 Standalone / web-based applications

43. Johanna Schmidt Predictive Analytics for Industry 4.0
Tools
https://source.opennews.org/articles/what-i-learned-recreating-one-chart-using-24-tools/

44. Johanna Schmidt Predictive Analytics for Industry 4.0
https://commercialtools.dbvis.de/home

45. Johanna Schmidt Predictive Analytics for Industry 4.0
https://www.cxtoday.com/data-analytics/gartner-magic-quadrant-for-analytics-and-business-intelligence-platforms-2022/

46. What is data visualization, and how to
integrate it in a data science workflow?
Johanna Schmidt
VRVis Research Center
Vienna, Austria