It won't have escaped the attention of many DBAs and database developers that their once-familiar landscape of is changing rapidly. Of course, you need to keep up with what's happening with the core database engine, and the imminent release of SQL 2016. However, many DBAs also feel pressure to find time to learn completely new skills in order to remain 'relevant', be it data science technologies, the Azure cloud, Polybase, or DocumentDB.
For the data professional, there has never been a bigger impetus to learn something new. Fortunately, there's also never been more opportunities to learn new data skills. Here are some of my personal favorite online video training sites and what's on my current learning list at each. A lot of what I'm learning right now is about expanding my data analysis skills, but there's plenty of core SQL Server learning on offer on these sites, plus some topics that I want to dip into purely to satisfy intellectual curiosity. As I said, there has never been a better time to learn!
Let's start with the one most will probably know of by now, Pluralsight. It offers technical training on a vast array of IT-related subjects. Windows Administration? Absolutely. Learning Python? They have you covered. Want to know what the deal with Angular is? No problem. After a trial period, you'll need to pay a fixed monthly fee for access to their entire library of courses (lowest subscription is $30 at time of writing). Want to binge-watch your way through 200 hours of material in a single month? Good luck pulling it off, but you can try it if you wish.
My current Pluralsight playlist:
- Understanding Machine Learning with R
- Azure Websites and WebJobs
- SQL Server: Building Simple Asynchronous Applications
Hidden away in Apple's iTunes app is their collection of recorded lectures from universities and other educational institutes. They have a huge number of courses from top universities including MIT, UC Berkley, Oxford and Cambridge. These are recording of normal university lectures, so the quality varies and there's often no accompanying work, like problem sets, extra reading or exams. Nevertheless, it's a formidable collection and some of the courses are perfect for providing a foundation in the 'academic' topics, such as statistics and algebra, which you'll need if you're serious about a new career in data analytics. The best part? They're all free.
My iTunesU playlist includes:
- Linear Algebra (MIT)
- Multi-variable calculus (MIT)
- Statistics (Harvard)
- Astrobiology and Space exploration (Stanford)
- Turing Centenary Lectures (Oxford)
This site also offers academic courses from many top universities, but recorded specifically for Coursara. Many but not all of the courses are free if you just want to watch the lectures and do the problem sets, but if you want the certificates for the course, you have to pay, and they're not particularly cheap.
My playlist here includes:
- Data Science (John Hopkins)
- Machine Learning (Stanford)
- Introduction to Logic (Stanford)
There are substantial benefits to self-study, from opening new job opportunities to satisfying curiosity. So what's on your study list, and why? And what are the biggest challenges? There's no one who will advise about pre-reqs or assumed knowledge, which can sometimes prove painful, and no deadlines, or at least no-one to keep you to them. How do you maintain self-discipline?
Gail Shaw (Guest Editor).