1) The document discusses data science and data products at NZZ, a Swiss media company. 2) NZZ uses data science to build data products like article recommendations and the NZZ News Companion app to address challenges from declining newspaper revenues and readership. 3) Key aspects of NZZ's data stack include REST APIs, Spark for scalable data processing, and deploying products on-premise, in the cloud, or with microservices.

1. Data Science
&
Data Products
at
René Pfitzner, Lead Data Scientist
19th Swiss Big Data User Group Meeting
Zürich, 23rd January 2017

2. I. Introduction
NZZ, media challenges, trends
II. Data Science @NZZ
Goals, principles, approaches
III. Data Products @NZZ
Our “stack” & insights & demo
IV. NZZ Companion
Individual news fueled by data science
Outline

3. I. Introduction
Myself, NZZ, media challenges, trends

4. ● Lead Data Scientist at NZZ
● media innovation
● algorithmic approaches for
news media
● background in StatPhys
● python, scala, spark, R
Self-Intro
www.renepfitzner.net
@RenePfitznerZH

6. Newspaper Revenue: the reality
US newspaper advertising revenue,
corrected for inflation
Data:
Newspaper Association of
America
Graphics:
https://commons.wikimedi
a.org/wiki/File:Naa_newsp
aper_ad_revenue.svg

7. Newspaper Decline
Number of newspapers in the
United States
-25%
Data:
www.census.gov
Graphics:
https://commons.wikimedi
a.org/wiki/File:Number_of
_newspaper_firms.png

8. Well, it should be!
Media = Fourth Estate!
Is this something to worry about?

9. Wikipedia:
Decline of Newspapers
https://en.wikipedia.org/wiki/Decline_o
f_newspapers

10. II. Data Science @NZZ
Goals, principles, approaches

11. Data Science: Goals
Data Science at NZZ
DecisionMaking
DataProducts
MarketingOptimization

12. Data Science: Data Products
Attempt of a definition:
A data product is a digital product that provides
some benefit to a downstream consuming
application, incorporating data and data-based
methods (e.g. ML).

13. Data Science: Data Products
What good is Data Science, if you cannot put
it into production?

14. Data Science: Data Products
Provision &
Integration
?
https://blog.treasuredata.com/blog/2016/03/15/self-study-list-for-data-engin
eers-and-aspiring-data-architects/

15. Data Science: Data Products
?Provision &
Integration
Data Product

16. III. Data Products @NZZ
Our “stack” & insights & demo

17. Data Products: Our stack
REST API’s

18. Data Products: What is Spark?
● “General engine for fast big
data processing”
● it’s more: parallel computing
framework
● “hadoop on steroids”
→ in-memory!

19. Data Products: How and where?
REST API’s
- on-premise / hosted
- gcloud -- dataproc
- gcloud
- in parts dockerized
- kubernetes
- gcloud & hosted
- dockerized; kubernetes
- microservice approach

20. Data Products: Article Recomm
- recommendations
based on current article
- mixed with
advertisement
- article click rate x3
- ad conversion rate x3

21. Data Products: Article Recomm
Network-based
- weighted
co-reading net
Trending articles
- clicks
- click trend
Topic detection
- word2vec

22. Data Products: Learnings?
● Spark is great for general purpose
● … easily maintained
● … go fast from dev to prod
● Scala forces you to think more & structure better
● cons: development notebooks
● more technical? Talk to me later ...

23. IV. NZZ Companion
Individual news fueled by data science

24. NZZ News Companion: Facts
● changing news consumption behavior
● vast majority of article clicks emerges from
startpage
● highly volatile startpage
data-enhanced content delivery

25. NZZ News Companion: Prototype

26. NZZ News Companion: DNI
https://www.digitalnewsinitiative.com/

27. Be a news-innovation
beta tester!
companion@nzz.ch

28. Be a news-innovation beta tester!
companion@nzz.ch
rene.pfitzner@nzz.ch
@RenePfitznerZH
www.renepfitzner.net