October 24, 2019

307 words 2 mins read

How to use your data science team: Becoming a data-driven organization

How to use your data science team: Becoming a data-driven organization

Youve decided you need data scientists. You know who to hire. Now, what do you do with them? Yael Garten offers examples of how companies like LinkedIn use data to make business and product decisions. Yael reviews the spectrum of data science, and discusses the culture, process and tools needed to transform companies into data-driven organizations.

Talk Title How to use your data science team: Becoming a data-driven organization
Speakers Yael Garten (LinkedIn)
Conference Strata + Hadoop World
Conf Tag Big Data Expo
Location San Jose, California
Date March 29-31, 2016
URL Talk Page
Slides Talk Slides
Video

So you’ve decided that your organization needs data scientists (whether to determine which metrics to optimize for, to employ data to suggest new innovations or addressable markets, or to develop machine-learning models and implement predictive analytics). You’ve created scaleable infrastructure and distributed systems to process data. You’ve figured out who to hire and how. Now, what do you do with them? Yael Garten offers examples of how companies like LinkedIn use data to make business decisions, and describes the process, culture and tools needed to run a data driven organization. Yael reviews the spectrum of data science used within an organization and explores organizational needs, such as the democratization of data via self-serve data platforms for experimentation, monitoring, and data exploration, as well as the challenges that come with such systems. Yael covers important foundations such as data quality and tracking and merging disparate data sources. Yael also presents examples of how data scientists can promote the art, science, and politics of defining which performance measurement metrics should be used to drive the business. Participants will leave this session with the ability to identify opportunities for data scientists to contribute within their organization and with an understanding of what investments are needed to drive transformation into a data-driven organization.

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