According to McKinsey Consulting, the US companies are facing an imminent shortage of analytical talent.

The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.

Full Article: Big data: The next frontier for competition

Mckinsey _ analyst shortage

Looks like a call to serve and I’m game to “Do my bit”!  My chosen vocation, Digital Marketing is heavily driven by analytics to drive the development and refinement of campaigns. Therefore, I’ve recently enrolled in Johns Hopkins University’s excellent Data Analytics program (available via Coursera here).

Do Your Bit - Data Analytics

I’ve always had a fascination with tools that enable the tabulation and analysis of data, beginning with Excel, then Access and Filemaker Pro, and most recently R, which is an absolutely amazing, free, open-source tool for data analysis.

The JHU program includes an extremely challenging but excellent R Programming course, which I highly recommend. Though at times I felt like putting my head in a blender trying to figure out the programming assignments in the course, that is part of the education, and I was able to succeed by collaborating with peers in the course discussion boards and using online resources like StackOverflow.

I am very proud to have their R Programming certificate, and look forward to using R as a power-tool in my future career as a digital marketing analytics ninja.

R Programming_nickakrueger

For those of you wanting to do your bit and learn R, I also highly recommend the following resources for getting off the ground.


SWIRL (SoftWare Interactive R Learning) – This is a ridiculously awesome and amazing learning tool for R. You install R Studio (available here), install and load SWIRL, and off you go. SWIRL teaches you through interactive text-based lessons within the R console iteself, and feels more like a game than anything. The lessons fly by and are incredibly informative. I would work through them all once or twice before beginning the Johns Hopkins course, which will make the assignments much easier.


I also highly recommend working through Bucky Robert’s series of YouTube videos on R, hosted by The New Boston, a great, free, learning resource site. Bucky is great at explaining the basics in easy-to-understand terms, with a sense of humor to boot. I watched these while on the treadmill in the morning and found they really lubricated the learning process.

R for Marketing Research and Analytics

Lastly I recommend the book, “R for Marketing Research and Analytics” by Chapman and Feit, available on Amazon (here). Unlike the Johns Hopkins course, this book is focused on the use of R in a marketing context, with relevant exercises. My personal goal is to work through the entire text by 01/01/2016.

Ready to “Do your bit”? Good luck to you, and have fun!