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.
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.
Course Overview Hi everyone. My name is Dan Tofan, and welcome to my course, Importing Data from Relational Databases in R. I'm a senior software engineer, and I enjoy helping people get things done. Your R code works well locally with some test data. How can you make it also work with data from a database? A database has much more data than you can store locally, and you need to use some of that data in your R code. This course gives you three concrete steps to get the data you need from a relational database into your R code. The first step is connecting to a database since no connection means no data. Therefore, you need to know how to connect, then how to troubleshoot connection issues, and also how to secure credentials. Once connected, the next step is to freshen up your SQL skills so that you gain confidence to query the database and get the data you need into your R code. Additionally, we'll look into how to get a lot of data and how to use parameters for queries. The final step is getting data using the dplyr package, which is a very powerful tool for data manipulation. Dplyr works with various data sources, including relational databases, and it generates automatically SQL code for you so that you can focus on data manipulation. Take this course now, and learn how to put together the capabilities of databases to handle large data with the power of R for making the most out of your data.