Product(ive) Data Science

• Verfasst von: Salon, Data [VerfasserIn]
• Titel: Product(ive) Data Science
• Institutionen: Safari, an O’Reilly Media Company. [MitwirkendeR]
• Verf.angabe: Salon, Data
• Ausgabe: 1st edition
• Verlagsort: [Erscheinungsort nicht ermittelbar]
• Verlag: Data Science Salon
• Jahr: 2019
• Umfang: 1 online resource (1 video file, approximately 26 min.)
• Fussnoten: Online resource; Title from title screen (viewed February 21, 2019)
• ComputerInfo: Mode of access: World Wide Web.
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Electronic videos ; local
• K10plus-PPN: 1733129863
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m3755946459
• Lokale URL Inst.: Zum Volltext

Abstract

Presented by Julie Hollek, Sr Data Scientist at Twitter Data scientists are the people behind the scenes, helping others deliver better, smarter results in their daily work. This is especially true for product data scientists who must hone their craft to determine what things are working for a given product, where do we want to take it next, and how can we make product decisions aligned with company is trying to build? Cross-functional communications are critical to success in this role; you need to be able to craft a message that is born out of math to make compelling arguments that are digestible by stakeholders across the business. In this session, we’ll define Product Data Science and discuss contributing factors to success.