The document discusses the intersection of data science and creativity, emphasizing how data can enhance rather than diminish creative endeavors in various fields like marketing and sports. It provides examples of data applications in areas such as predictive maintenance, customer engagement, and fraud detection. The author represents a community in Thailand focused on learning and sharing knowledge about data science.

1. Data (Science) fuels Creativity
โกเมษ จันทวิมล
Komes Chandavimol
Data Scientist
Data Science Thailand,
A Community to learn and share Data Science in Thailand
komes@datascienceth.com

3. Komes Profile
Komes Chandavimol
Data Scientist
Data Science Lab, Thailand

4. Data vs Creativity

5. http://which-50.com/data-isnt-killing-creativity-killing-creative-ego/
https://wpengine.com/blog/science-vs-art-is-data-killing-creativity-in-marketing/
http://smactalklive.libsyn.com/smactalk-ep-54-does-more-data-and-access-equal-less-
creativity?utm_content=buffer7dd9b&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

6. http://thenextweb.com/insider/2016/05/11/machine-learning-will-enhance-not-replace-human-creativity/#gref
https://www.washingtonpost.com/news/innovations/wp/2016/06/06/googles-computers-are-creating-songs-making-music-may-
never-be-the-same/

7. Big Data
http://www.adweek.com/prnewser/how-many-times-do-the-worlds-social-media-users-click-every-minute/117427
https://www.domo.com/learn/data-never-sleeps-3-0

8. Internet of Things
http://topmanagement.com.mx/innovacion-social-y-empresarial-objetivo-de-hitachi/

9. 9
http://www.adweek.com/prnewser/how-many-times-do-the-worlds-social-media-users-click-every-minute/117427
https://www.domo.com/learn/data-never-sleeps-3-0
The Growth of Data

10. 10
http://www.adweek.com/prnewser/how-many-times-do-the-worlds-social-media-users-click-every-minute/117427
https://www.domo.com/learn/data-never-sleeps-3-0
What is 3 Vs in Big Data?

11. 11
Why We need more Data?
https://www.digitalnewsasia.com/business/forget-data-warehousing-its-data-lakes-now

12. 12
Why We need more Data?
https://www.digitalnewsasia.com/business/forget-data-warehousing-its-data-lakes-now
Volume? Variety? Velocity?

13. 13
Why We need more Data?
https://www.digitalnewsasia.com/business/forget-data-warehousing-its-data-lakes-now
Volume? Variety? Velocity?
Value

14. 14
Big Data + Analytics = Values
https://www.digitalnewsasia.com/business/forget-data-warehousing-its-data-lakes-now
+ Analytics

15. Value vs Data
15
http://dataofthings.blogspot.com/2014/04/the-bbbt-sessions-hortonworks-big-data.html

16. Analytics
16http://www.gartner.com/it-glossary/predictive-analytics

17. Data
New Analytic Insights
(Information, knowledge, data story)
Data Product
+ VisualizationMass Analytic Tools
Machine Learning
Recommender systems
Complex Event Processing Data Science Team
Data ScientistPicture:http://www.clipartpanda.com/categories/scientist-clip-art
The Roles of Data Science
Doing Data Science by O'Neil et al (2013)
DatascienceTh.com
Datafication

18. 18

19. 19DataInquest – Predictive Analytics and Data Science Bootcamp

20. Data Science Use Cases

21. The XYZ of Data Science
• Smart X
– Smart Factory
– Smart Supply Chain
• Precision Y
– Precision Pricing
– Precision Bidding
• Personalize Z
– Personalized shopping/coupon
– Personalized Campaign
– Personalized Learning
21
KirkBorne-workshop-ODSC2016.pdf

22. Monitoring and Maintenance
Data sources: IoT Sensors in factory
Data products: predictive maintenance models
http://www.electrex.it/en/news/600-automated-energy-management-system-a-enms-for-cement-production-plants.ht
http://www.digitalistmag.com/digital-economy/2015/12/01/iot-digitization-reinforce-cement-industry-03814141
Credit: Jarun Ngamvirojcharoen

23. Customer Engagement + Location
Data sources: Mobile App, Loyalty Program, GIS
Data products: Buying behavior analysis, coupon-response model , location visualization
http://www.fastcompany.com/3020859/most-creative-people/how-chinas-one-child-policy-forced-starbucks-to-rethink-its-beijing-sto
https://digit.hbs.org/submission/starbucks-driving-customer-engagement-via-digital-innovation/
Credit: Jarun Ngamvirojcharoen

24. Fuel Saving
Data sources: Telematics (sensor), GPS
Data products: Prescriptive analytics – route
optimization, predictive maintenance
(parts/malfunction)
http://www.cnet.com/news/ups-turns-data-analysis-into-big-savings/
http://www.cnet.com/news/ups-turns-data-analysis-into-big-savings/ Credit: Jarun Ngamvirojcharoen

25. Fraud Detection
Data sources: historical pattern of transaction data
Data products: predictive models – fraud/non-fraudhttps://bluefishway.com/2013/09/13/panic-oh-no-not-again/
http://blogs.wsj.com/cio/2015/08/25/paypal-fights-fraud-with-machine-learning-and-human-detectives/
Credit: Jarun Ngamvirojcharoen

26. HR Analytics – Google Hiring
Data sources: Historical hiring attributes
Data products: Predictive model – recruiting
high performer
Behavioral Test
Situational Test
GPA
Brain Teaser
Good School
http://www.kornferryinstitute.com/briefings-magazine/summer-2014/big-data-predictive-analytics-and-hiring
Credit: Jarun Ngamvirojcharoen

27. Data (Science) for Sport
http://www.ibmbigdatahub.com/blog/why-data-science-team-sport

28. Data (Science) for Pokémon?
https://www.reddit.com/r/pokemongo/comments/4rwhma/
i_made_a_rarity_chart_based_on_my_findings

29. http://jkunst.com/r/pokemon-visualize-em-all/

30. Data Creativity
Q & A