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R Programming in Data Science

High Volume Data

Data fills all available space, and now that storage is cheap, the amount of data has exploded. However, all that information is useless without analysis and context. The R programming language is designed to make it easier to analyze and visualize massive amounts of data. For example, R provides the ability to multiply one block of variables by another—an assumption that provides inherent advantages over other languages. This course shows why R is ideal for high volumes of data, introduces more efficient ways to use the language, and explains how to avoid the problems and capitalize on the opportunities of big data. Learn how to determine if you have enough memory and processing power, produce visualizations of big data, optimize your R code, and use advanced techniques such as parallel processing to speed up your computations. Plus, discover how to integrate R with big-data solutions such as SQL databases and Apache Spark.

Contents:

  • Introduction
  • 1. Problems and Opportunities with High-Volume Data
  • 2. Visualizing High-Volume Data
  • 3. Working within the R Programming Language
  • 4. Advanced High-Volume Techniques
  • 5. Use R with External Big Data Solutions
  • Conclusion

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Rating Not enough ratings
Length 1h 25m
Starts On Demand (Start anytime)
Cost $29/month (Access to entire library- free trial available)
From LinkedIn Learning
Instructor Mark Niemann-Ross
Download Videos Only via the LinkedIn Learning mobile app
Language English
Subjects IT & Networking Data Science Programming
Tags IT Big Data R RStudio

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LinkedIn Learning

Rating Not enough ratings
Length 1h 25m
Starts On Demand (Start anytime)
Cost $29/month (Access to entire library- free trial available)
From LinkedIn Learning
Instructor Mark Niemann-Ross
Download Videos Only via the LinkedIn Learning mobile app
Language English
Subjects IT & Networking Data Science Programming
Tags IT Big Data R RStudio

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