Data Architectures for Data Science Using Data Virtualization

Free On-Demand Webinar

Data scientists are confronted with some major challenges: a fast-changing data storage technology landscape, new restrictive regulations for data privacy, and time-consuming data preparation tasks. In fact, studies have shown that data scientists spend only 20% of their time on real analytical work and as much as 80% of their time on data preparation tasks.

Rick van der Lans

CEO & Founder R20/Consultancy

Dr. Nick Golovin

CEO & Founder Data Virtuality

Sue Raiber

Head of Marketing

Data Virtuality

Webinar Presenter

Webinar Presenter

Webinar Host

In this webinar, we look at how a modern data architecture can help data scientists to be faster and to work more efficiently.

Detailed explanation of the major challenges that are the reason why data scientists spend so much time on searching, accessing, and querying the data.

Will cloud platforms and data lake solutions possibly solve these challenges?

The webinar is structured in three parts:

How data virtualization features can speed up the work of data scientists, and how it helps to deal with all the challenges. More specifically, a flexible data architecture, called the logical data lake, is described in which data virtualization acts as the general entry point for data scientists to access data.

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