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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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Chapter 4. Big Data – Advanced Analytics

In this chapter, we will deal with one of the biggest challenges of high-performance financial analytics and data management; that is, how to handle large datasets efficiently and flawlessly in R.

Our main objective is to give a practical introduction on how to access and manage large datasets in R. This chapter does not focus on any particular financial theorem, but it aims to give practical, hands-on examples to researchers and professionals on how to implement computationally - intensive analyses and models that leverage large datasets in the R environment.

In the first part of this chapter, we explained how to access data directly for multiple open sources. R offers various tools and options to load data ...

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