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“Careers in Computer Games“
University of Edinburgh / 1st of February 2017
Thomas Hulvershorn
Operations and Analytics Man...
Working in Game Analytics
Typical Tasks for Analytics:
Determine the Difficulty in Level
Progression. Where do Players
get stuck, how often do they
...
https://www.youtube.com/watch?v=XDW5Bp90z0M
Dynamic Presentation of Level
Progression: Brighter Areas indicate
harder Leve...
Established 2011 in Dundee
Outplay Entertainment is the largest
independent Mobile Games Developer in the UK
Sample Group A Sample Group B Control Group
Project StakeholdersReal Time Analytics
ETL
Layer
Analysts
Tracker
Store Data
...
How to make sense of vast
amounts of Data?
Game Design influences Performance
• Two Factors
– FUN
– Difficulty
Game Analytics
• Collecting 8 Millions Data events per...
What skills are needed
to work in Analytics?
Inspired by http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram
Coder
 
Scientist
Designer
Typical Background for people working in Analytics*
>Examples
>MSc, BSc Mathematics and Statistics
>Ph.D. e.g. Geoscience
...
Statistical evaluation of Experiments
Skills and Preparation
• Learn a Scripting Language, e.g. “R” or Python
• Learn / Understand SQL
• Excellent knowledge of ...
> Outplay.com
> Twitter @DerHUL
> Further Reading
> ‘The Lean Startup’, Eric Ries
> ‘Data Analysis with Open Source Tools’...
Thanks
Thomas.Hulvershorn@outplay.com
@DerHul
Careers in Computer Games: Game Analytics
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Careers in Computer Games: Game Analytics

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This talk at the University of Edinburgh outlines the opportunities and skills required for working in the Games industry as Data Analyst.

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Careers in Computer Games: Game Analytics

  1. 1. “Careers in Computer Games“ University of Edinburgh / 1st of February 2017 Thomas Hulvershorn Operations and Analytics Manager Outplay Entertainment
  2. 2. Working in Game Analytics
  3. 3. Typical Tasks for Analytics: Determine the Difficulty in Level Progression. Where do Players get stuck, how often do they attempt a level?
  4. 4. https://www.youtube.com/watch?v=XDW5Bp90z0M Dynamic Presentation of Level Progression: Brighter Areas indicate harder Levels. Green indicates Levels where players have passed and won the level. Example: Dynamic Data Visualisation
  5. 5. Established 2011 in Dundee Outplay Entertainment is the largest independent Mobile Games Developer in the UK
  6. 6. Sample Group A Sample Group B Control Group Project StakeholdersReal Time Analytics ETL Layer Analysts Tracker Store Data Analytics Events Game on Store Download Deploy new VersionF2P Data Feedback Driven Deployment Game Life cycle Player Launch Amazon Cloud Game SettingsOutplay Server ModifySettings SetupExperiments Game Settings Producer Feature Backlog (Jira) Targets Designer Game in Vault Product Team New Version Sign off and Store Submission Game Development Client Update
  7. 7. How to make sense of vast amounts of Data?
  8. 8. Game Design influences Performance • Two Factors – FUN – Difficulty Game Analytics • Collecting 8 Millions Data events per day (already sampled) • Data stored in AWS / Redshift • Accessed with SQl • Analysed with ‘R’
  9. 9. What skills are needed to work in Analytics?
  10. 10. Inspired by http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram Coder   Scientist Designer
  11. 11. Typical Background for people working in Analytics* >Examples >MSc, BSc Mathematics and Statistics >Ph.D. e.g. Geoscience (and other with Background in Computing, Mathematics, Science) >MSc, BSc Physics >MSc International Business >MSc Artificial Intelligence >BSc Applied Computing >… *(not considering technical Analytics, e.g. Database Management…)
  12. 12. Statistical evaluation of Experiments
  13. 13. Skills and Preparation • Learn a Scripting Language, e.g. “R” or Python • Learn / Understand SQL • Excellent knowledge of applied Statistics and Visualisation • Know the products of the company you’re applying at • Passion for Games!
  14. 14. > Outplay.com > Twitter @DerHUL > Further Reading > ‘The Lean Startup’, Eric Ries > ‘Data Analysis with Open Source Tools’, P. Janert > ‘Data Analysis’, Phillip K. Janert > ‘Impact Mapping’, Gojko Adzic > ‘Freemium Economics’, Eric B. Seufert > ‘Data Visualisation with D3.js Cookbook’, N.Q Zhu > Coursera: Data Science, ‘R’
  15. 15. Thanks Thomas.Hulvershorn@outplay.com @DerHul

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