Building data science infrastructure

"Presented by Caitlin Hudon, Lead Data Scientist at OnlineMedEd. Before AI, before machine learning and pipelines, and before dashboards and BI, an organization starts with a pile of data, some business questions, and a few ideas on how to connect the two -- a greenfield, and an entry point for...

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Bibliographic Details
Format: eBook
Language:English
Published: [Austin, Texas] Data Science Salon 2020
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:"Presented by Caitlin Hudon, Lead Data Scientist at OnlineMedEd. Before AI, before machine learning and pipelines, and before dashboards and BI, an organization starts with a pile of data, some business questions, and a few ideas on how to connect the two -- a greenfield, and an entry point for data science. Answering business questions and turning raw data into insights, models, and products means more than just writing code and doing analysis. A successful data science team needs tools, a communication strategy, thoughtful infrastructure, and a plan to deliver on their goals. This talk will cover how to tackle greenfield data science challenges from the perspective of the first data science hire in an organization, and how to build data science infrastructure from the ground up."--Resource description page
Item Description:Title from resource description page (Safari, viewed October 6, 2020). - Place of publication from title screen
Physical Description:1 streaming video file (22 min., 28 sec.)