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Overcoming Challenges at Yahoo! JAPAN & LINE Data Analysis Organizations

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

Tech-Verse2022
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November 17, 2022
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Transcript

  1. None
  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