March 22, 2017 | Written by: Rav Ahuja
Categorized: Data Analytics
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- Do you want to leverage the power of R to unlock the value of data in relational databases?
- Are you a database professional and looking to get skilled in data science?
- Are you a data scientist and hitting the limits of R while trying to analyze very large data sets?
If you answered yes to any of these questions, do read on…
Originally developed for statistical programming, R is now one of the most popular languages in data science. The R programming language is widely used for data analysis, data visualization, and machine learning. It works with a variety of data sources, including relational databases (RDBMSes).
Whether you are a data scientist, or a database professional, we bring you a valuable resource to help you get started using R with databases – a free, self-paced, online course titled Using R with Databases.
(And if you are not yet familiar with R, there is also a free crash course in R to get you started: R 101.)
If you are a Data Scientist or a Data Analyst, chances are that you are already familiar with the richness of the R programming language and are already leveraging it for modeling, classification and clustering analysis, creating great graphs and visualizations, etc. But you may be hitting the memory limits of R when utilizing it for very large data sets.
Utilizing R with databases and data warehouses, such as IBM dashDB, that are known for scalability and performance with large amounts of data, is one mechanism to overcome the memory constraints of R. And this free course will show you how.
If you are a database professional (Data Engineer, DBA, Data Developer, etc.) and looking to leverage the power of R to analyze and visualize data in relational databases, this online course with hands-on labs will get you going quickly.
The course starts with a comparison of R and Databases and discusses the benefits of using R with databases. It teaches you how to setup R for accessing databases and demonstrates how to connect to databases from R, specifically using interfaces like RJDBC and RODBC.
The course then goes on to show you how to query data from databases, get the results and visualize the analysis. It also covers some advanced topics like modifying and saving saving data in databases from R, as well as using database stored procedures from R.
Some databases, like dashDB, and IBM DB2, also support in-database analytics with R, so you can benefit from the large amounts of memory and parallel processing features of databases while employing R for analysis. This course also helps you to learn about using in-database analytics with R.
Like other courses in BDU, each module in Using R with Databases, comes with hands-on labs so you can practice what you learn in the course and try out your own variations.
More over, the hands-on lab environment, called BDU Labs, is free, cloud-based, ready to use, and integrated within BDU so you don’t have to worry about installing software. The hands-on labs for this course consists of Jupyter notebooks, and dashDB database on Bluemix.
The course consists of 5 learning modules and after each module there are review questions. At the end of the course there is final exam.
Successfully passing the course (by proving your proficiency with review questions and final exam), marks your achievement with a a course completion certificate.
This course is part of Data Science with R learning path on BDU, and when you complete all courses in this learning path, you also earn an IBM badge that can be shared on your social profiles.
Enroll now for free and start Using R with Databases!