R Programming in Data Science: High Velocity Data

R Programming in Data Science Video Course

High-velocity data—such as the information that springs from Twitter and IoT devices—comes barreling in at a speed beyond normal comprehension, demanding high-performance from both hardware and software. While it might not initially appear up to the challenge, the R programming language can be revved up to operate with high-velocity data. Written close to the metal by sitting directly on top of the C programming language, R provides a rich set of data structures and concepts. This course drills down into efficient R programming, providing practical strategies that can help you work your mojo on high-velocity data.

Instructor Mark Niemann-Ross begins by sharing a framework for understanding the different types of high-velocity data. He then covers how to use R to acquire high-velocity data, as well as how to leverage profiling tools and optimize R code for use with high-velocity data. He wraps up by exploring how to use R to present data, including how to use Shiny—an R package that allows you to build web apps straight from R—for interactive dashboards.

Topics include:

  • Problems and opportunities with high-velocity data
  • Characteristics of high-velocity data
  • Real-time processing of high-velocity data with R
  • Using R to acquire high-velocity data
  • Polling for data with an R program
  • Using Profvis, Rprof, and microbenchmark
  • Optimizing R code for use with high-velocity data
  • Using R to present high-velocity data
  • Using R Markdown for static dashboards

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