Overcoming Challenges at Yahoo! JAPAN & LINE Data Analysis Organizations

Taro Takaguchi (LINE / Data Science Department1 / Senior Manager)
Eri Sakaue (Yahoo! JAPAN / Data Strategy Division, CDO / Senior Manager)
Yuki Sekiguchi (Yahoo! JAPAN / Analysis Department, Science Division 2, Science Group / Senior Manager)

https://tech-verse.me/ja/sessions/308
https://tech-verse.me/en/sessions/308
https://tech-verse.me/ko/sessions/308

Transcript

2. Introduction of Panelists
3. Eri Sakaue / 阪上恵理 Yahoo! JAPAN, Data Strategy Division, CDO Senior Manager Eri Sakaue joined Yahoo! JAPAN in 2005 after spending some time working for a credit card company, and is currently in charge of functions such as service analysis as a data analyst. Eri is currently based in Kansai and involved in operations such as company-wide data governance, data utilization promotion, and training of data personnel. Coauthor of “Big Data Detective Team” (Kodansha's new library of knowledge, 2019) Moderator/Panelist
4. Yuki Sekiguchi / 関口優希 Yahoo! JAPAN, Analysis Department, Science Division 2, Science Group Senior Manager Yuki Sekiguchi joined Yahoo! JAPAN as a new graduate in April 2017 and began working data analysis for Yahoo! JAPAN Shopping. Starting in 2018, Yuki was involved with the development and analysis of a data pipeline for management of KPI for projects crossing over Yahoo! JAPAN’s media and commerce fields. Carried out analysis for a variety of group services since 2020. In 2022, Yuki was appointed the head of the Analysis Department in the Science Group. Has 12th generation data analysis area KURO-OBI (Black Belt) and Ph.D. (science). Panelist
5. Taro Takaguchi / 高口太朗 LINE, Data Science Department1, Senior Manager Taro Takaguchi joined LINE in 2017 and currently serves as a senior manager leading a department of data scientists who provide data analysis focused on the LINE app's functionality as a cross-service platform. Panelist
6. Introduction to the data analysis organizations of Yahoo! JAPAN & LINE 両社のデータ分析組織について紹介
7. Yahoo! JAPAN
8. CEO Media Services Group Shopping Services Group Marketing Solutions Group Analysis Division Analysis Division Analysis Division ・・・ Science Group Analysis Division * This diagram is schematic, not accurate. • Each service group has analysis divisions. • The Science Group supports each service, but not responsible for specific services. • Why do we receive analysis requests from service groups, which have their OWN analysis divisions? I’m here!
9. Typical analysis cases in the Science Group. • Difficult in many ways. - spanning multiple services, especially media, ads and commerce. - estimation in complex scenarios. • Medium-to-long term / investment cases. - do not necessarily lead to KPI improvement in a short term. • Less human resources for data analyses in service groups. - small services. - eventually, increase the number of data analysts.
10. LINE
11. Data Science Department 1&2 Data Science 1 Data Science 2 LINE app B2B Family service Financial
12. Mission as a cross-functional department Do what a single service cannot do LINE app x Family service › Multiple stakeholders › Complex combination of data › Cross-domain knowledge › Long analysis cycle LINE app x LINE Ads LINE Official Account x LINE Ads Company-wide data analysis
13. Discussion
14. What are your efforts in terms of systems and methods for cross-sectional data analysis? 横断的なデータ分析のために、体制や手法などで 工夫していることはありますか？ Topic-1
15. How do you share analysis cases and knowledge within your organization? 組織内での分析事例・知見の共有ってどうやっていますか？ Topic-2
16. How do you acquire the knowledge to support the various domains of service? 様々なサービスのドメイン知識の取得はどうしていますか？ Topic-3
17. What are some typical mistakes or pitfalls when analyzing data? データ分析において陥りがちな判断、 落とし穴はありますか？ Topic-4
18. What experience and mindset is required for a DA/DS to grow? データアナリスト/データサイエンティストが 成長するために必要な経験・マインドは？ Topic-5
19. Thank you