The Data Science Day is the annual in-person gathering of the Data Science Expert Group, WAN-IFRA’s international community of practice for ​ data practitioners in digital news: data analysts, scientists, engineers and chief data officers.  

LINKS TO THE PRESENTATIONS (Le Figaro – Paris, 21 October 2022)

09:30 Semantic content analysis at Le Figaro: a human / machine collaboration. Quentin Barigault, Senior Data Analyst, Le Figaro, France

10:10 Scenarios on data privacy and future governance. A strategic outlook on addressability and technology in a privacy-by-design environment. Emanuel Jonas, Senior Consultant Digital Advertising Technology, nxt statista, Germany. Jana Stapelbroek, Consultant, nxt statista, Germany

11:00 Coffee Break

11:20 The set-up of data architecture to support the newsroom’s transformation (data collection, processing, visualization). Mariot Chauvin, Director of Engineering, The Guardian, UK.

11:50 Identify and maintain subscribers likely to leave – The F.A.Z. Churn Prevention Model. Fabian Wörz, Senior Data Scientist – Frankfurter Allgemeine Zeitung GmbH, Frankfurt am Main, Germany.

12:30 Price elasticity. Predicting the maximum price somebody is willing to pay for a subscription. Liesbeth Nizet, Managing Director Europe, Mather Economics, Belgium.

13:00 Networking Lunch

14:30 Roundtables Breakout Session #1
1. Communicating with the newsroom: dashboarding, real-time restitution of sales and traffic data.
2. Industrializing data collection & reconciliation (incl data warehouses for business analytics and data lakes for machine learning on one data lakehouse platform.
3. KPIs: What analytics, for what purpose.
4. Information about content: tags, categories, NLP, NLU, image/video recognition, Names Entity Recognition NER.

15:30 Roundtables Breakout Session #2
5. User Modeling, Engagement & Personalisation: with emphasis on audience understanding and activation
6. KPIs: Defining meaningful and purposeful KPIs and Customer Value Management metrics to drive your content and lead your business. The optimal churn rate, lifetime value metric, etc.
7. Data governance, quality & compliance (including topics like the igration from GA 360 to GA4,…)
8. Team structures, skills, capabilities and resources. Your data as a product. How do you apply product management best practices to your data projects in order to make them more tailored to operational needs (advertising, sales, newsroom)

16:30 Break

16:45 Roundtables Breakout Session #3
1. Communicating with the newsroom: dashboarding, real-time restitution of sales and traffic data.
2. Industrializing data collection & reconciliation (incl data warehouses for business analytics and data lakes for machine learning on one data lakehouse platform.
3. KPIs: What analytics, for what purpose
4. Information about content: tags, categories, NLP, NLU, image/video recognition, Names Entity Recognition NER.

17:45 Roundtables Breakout Session #4
5. User Modeling, Personalisation & Engagement: with emphasis on audience & content segmentation
6. KPis: Defining meaningful and purposeful KPIs and Customer Value Management metrics to drive your content and lead your business. The optimal churn rate, lifetime value metric, etc.
7. Data governance, quality & compliance (including topics like the igration from GA 360 to GA4,…)
8. Team structures, skills, capabilities and resources. Your data as a product. How do you apply product management best practices to your data projects in order to make them more tailored to operational needs (advertising, sales, newsroom).

18:45 Wrap up – Roundtables Breakout Sessions