Saturday, August 13, 2016

Big Data Education . . . Microsoft Style

Big Data is coming. It's coming fast. And there's a shortage of technical people who understand it and can turn it into usable information.

And since I don't want to get bored, I decided to dive in. The truth is, I have several years of graduate school statistics under my belt. In fact, I met my wife of 20 years at what we call "Nerd Summer School." It's the University of Michigan Inter-University Consortium for Political and Social Research (ICPSR) summer program. I was helping to run the program and she was a student . . . about 30 years ago.

Anyway, I have been training myself on Big Data and modern data analysis techniques. In fact, I recently finished writing a white paper on Big Data for LogicNow. So keep an eye out for that.

Last month Microsoft announced that they are offering a new "degree program" in Data Science. Jessica Davis has a great article on this at InformationWeek:

The curriculum includes the following courses, which will be taken one at a time:

- Data Science Orientation
- Query Relational Data
- Analyze and Visualize Data
- Understand Statistics
- Explore Data with Code
- Understand Core Data Science Concepts
- Understand Machine Learning
- Use Code to Manipulate and Model Data
- Develop Intelligent Solutions
- Final Project

For FAQs on the Data Science program, go to

I've signed up! 

The official site for the announcement is here:

Right now the only thing you can officially do toward the degree is to sign up and get on their list. BUT you can also start taking the classes and ask for them to be applied to the degree when you're finished with each one. That's what I've done.

I just started the first course over at edX - See It's supposed to last 4-5 weeks but I'm going to Colombia in three weeks, so my plan is to cram through this one since it's an orientation class.

So far, there are PowerPoints and recorded video lectures. You can download the PPTX files and the lecture transcripts. That's pretty nice. I paid $49 for the class with credits. You can audit the course for free, I believe. But of course you won't get a degree at the end.

Supplemental Material: Amazon

The primary tool family used for Big Data analysis is call Hadoop. The most common language used to perform the analysis is called R.

Of course I'm a book kind of guy, so I also decided to get a book on learning R. I went to Amazon and Searched for Learning R. I bought the book from O'Reilly called Learning R.

But wait! It gets better.

Supplemental Goodness: Microsoft Action Pack

Then I remembered that I'd seen some Hadoop and R references my Microsoft Action Pack.

[ Side track: If you're a technology professional and not a Microsoft Action Pack subscriber, you should be. You get lots of great internal-use software for running your company and educating yourself. Head over to to sign up. ]

Sure enough. The downloads include R Server for Hadoop, R Server for Linux, and R Server for Teradata DB. All of these are on-premise installations. Since I already know we'll be using R in the courses I'm taking, I'll plan to download these once I have some idea which I need.

The intro course already promises to help me get set up with using R in the Windows Azure platform. Since I have an Azure account already, that should be easy.

Join Me!

The best way to get ahead and stay ahead in the world of technology is continuous education. Right now there isn't a lot of attention being paid to Big Data in small business. But that will change. LogicNow's LogicCards are a great (and powerful) example of what can be done with Big Data in small business. And while none of the other RMM vendors have made serious attempts to match them, they will have to eventually.

If it's been a long time since you tackled a new technology - especially one that looks difficult - I think you'll find the Microsoft program very manageable. It's one class at a time. If you don't pass you can take it again. And at $49 per course, the price is too cheap not to try.

You may also find yourself tempted out of the world of SMB. If it's true that there will be 1.5 million jobs with no takers in the next few years, we may all get swept into the Big Data world.

I plan to blog about this from time to time, so you're welcome to follow along. But I'd much rather you joined me. Then we can compare notes on Facebook, LinkedIn, and at live conferences over the next year.


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