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Importing Data from Relational Databases in R 3

This course shows how R’s capabilities can help you retrieve data from relational databases and make it available to R for adding value with other operations, such as analysis and visualization.

Dan Tofan - Pluralsight course - Importing Data from Relational Databases in R 3
by Dan Tofan

What you'll learn

Data is very often stored in relational databases, which are a well-established technology for the last several decades. Your organization might use various relational databases, such as Microsoft SQL Server, Oracle, PostgreSQL, MySQL/MariaDB, or SQLite. In this course, Importing Data from Relational Databases in R, you will learn how R's capabilities can help you retrieve data from relational databases and make it available to R for adding value with other operations, such as analysis and visualization.

First, you will learn about connecting to relational databases. You will discover the possible options for connecting, including the pros and cons of each option. Sometimes things can go wrong, so you will learn some basic connection troubleshooting steps. Then you will explore how to make various SQL queries to a relational database: SELECT statements, filtering data, ordering data, grouping data, inner joins, as well as inserting and deleting values from a table. Additionally, you'll learn how to give parameters to a query and how to fix the security issues around this. Finally, you will determine how to query the database with dplyr, a very popular package for working with data frames that has capabilities of generating SQL queries for you.

Finishing this course will give you the confidence to import precisely the data you need from various relational databases into your R code.

Table of contents

About the author

Dan Tofan - Pluralsight course - Importing Data from Relational Databases in R 3
Dan Tofan

As a software engineer and lifelong learner, Dan wrote a PhD thesis and many highly-cited publications on decision making and knowledge acquisition in software architecture. Dan used Microsoft technologies for many years, but moved gradually to Python, Linux and AWS to gain different perspectives of the computing world.

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