One of the hardest things about learning anything new is finding resources that are worth your time, don’t cost thousands of dollars, and don’t suck. One of the things i have not done and will not do is teach base R. I will do demos, i will explain some packages and functions along the way, but the basics of R are all free, and all range form pretty good to excellent. When you are in the early stages of learning anything, anyone that knows more than you is a resource for you. Just make sure they know wtf they are talking about, that part is harder. The next hardest part is use it everyday!
In my head there is always a competition for which post is next and sometimes if there will be a post at all. ODBC and RevoScaleR have been arguing and its super annoying. ODBC was the last post, how you can connect to any version of SQL using just ODBC. If you did not go to the link I published, you can connect to Oracle, MySQL, PostgreSQL, SQLite too. The point of that will become much more clear when you start querying MSDB Job History so you can write your own R ggplot reports on job length and overlapping jobs (spoilers…). I will give you the code to get you started, later, maybe tomorrow, I don’t know yet depends on who wins the next argument. For now it is connect to SQL Server using RevoScaleR package…
So here you are, you know SQL or you at least do something with it everyday and are wondering what all the hoopla is about R and data science. Lets break down the first barrier, R and data science actually have little to do with each other, R is a language, data science is an abstract field of work, sort of like saying I am a computer scientist, that will narrow it down but not by much. What is your industry, what languages do you use, what is your education, hacker, bachelors, masters, phd…? You can be a Data Scientist and never use R.
But we are going to use R, today, right now, get ready.