Three Strategies to Tackle Big Data in R

Dec 14, 2021 · København, Denmark

** Please ALSO register here to secure your spot **
https://gotopia.tech/events/94/sign_up

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Speaker: Rasmus Bååth
Date: December 14, 2021
Time: 5.30pm - 6.45pm
Location: Trifork, Borgergade 24B, 1300 Copenhagen

AGENDA

5:30pm - Doors open
5:45pm - Welcome by GOTO
5:50pm - Three Strategies to Tackle Big Data in R with Rasmus Bååth
6:30pm - Q&A
6:45pm - Thank you for today

ABSTRACT

Big data might not be the buzzword it was five years ago, but it's more prevalent than ever. Even if you aren't currently dealing with big data, chances are that sooner or later you'll find yourself with a dataset that is just too big for your normal R setup to handle.

At this meetup in collaboration with CopenhagenR, Rasmus Bååth, data science lead at Castle.io, will share three strategies that can be used to tackle big data in R (and python if that's your cup of tea). Three big data tools will be briefly introduced: duckDB, Spark and SnowflakeDB.

The CopenhagenR meetup is ramping up again and invites you to join this event aimed at everybody working with or interested in data science.

ABOUT THE SPEAKERS

Rasmus Bååth - Rasmus is a data science lead at Castle.io, a Y combinator-backed startup building an AI-based security and fraud detection service. He's worked with big data in many different forms and knows that, while it can be a pain to handle big data, there can be great business value (and good career opportunities) knowing how to do so.

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** Please ALSO register here to secure your spot **
https://gotopia.tech/events/94/sign_up

Event organizers
  • CopenhagenR - useR Group

    Do you have friends in Århus.. Tell them about Rhus.club This is a useR group for people near or far from Copenhagen. Everybody is welcome no matter your level or specific interests in the R language. We hope to create a group where people can share knowledge, learn and hopefully inspire and get inspired using R. According to KDNuggets R is the most popular language for analytics, data mining and data science. There are several reasons for this! R has a package for just about everything, you can create bea

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