Q&A with Andy Kriebel from The Information Lab

Who are you and what do you do?

Andy Kriebel - Head Coach at The Information Lab. I run The Data School, a program that creates data analytics gurus.

What does a typical day involve at the Data School?

At the Data School, a typical day is 1/2 training and 1/2 project work. Half of the projects in their 16-week training come from me and the other half are projects we do for our clients for free. The client projects help them gain exposure to clients, experience working with clients, and teach them to work fast while having to learn an entirely new industry each week.

The Data School's approach to onboarding new analysts is relatively unusual (heavily training focused in early months which is a rare approach and discussed in more detail here by The Information Lab’s founder Tom Brown’s post), are you starting to find that some of the clients you work with are starting to take the same approach?

I don't know of any of our clients that are now hiring this way, but they should! As some of the Data Schoolers start rolling out of the program, it's been interesting to see that where they went to school became less important because employers see the value of their experience in The Data School as way more valuable.

I've often described the Tableau community as 'Evangelical', what is it about the product/community or the Data Viz discipline that's created that?

Wow! What a great question! When I started using Tableau and learning about data viz, I needed help along the way and guidance in my learning. Everyone I interacted with was so friendly. That led me to want to give back to the community in the same way. I imagine many people get excited about Tableau for these same reasons that I did.

Following on from the 'Evangelical' theme, your own involvement in all things Data Viz is 'committed' to say the least (Andy’s volume of data viz production is huge from his own site, Makeover Monday, Dear Data Two and elsewhere), what keeps that enthusiasm going?

Now this is an EASY question! The Community keeps me motivated. People intentionally seek me out to thank me. People appreciate it when I give them feedback. Really, it's people being nice to one another that drives me to continue to learn myself and to continue to want to help others.

How much do think Tableau's change in pricing (moving from perpetual to subscription style model) will impact things?

I'm not involved in sales, so it's hard for me to say. From my understanding, it will help companies roll out faster and at their own pace. that can only be good for adoption.

Although a lot of what you do is transferable to other tools, do you ever worry about over-committing to a single tool like Tableau, is there ever a worry you've 'backed the wrong horse'?

Never! Tableau is THE BEST data analysis tool available. I use Tableau every day as a hobbyist. You never hear of other people using other tools as hobbyists the way they talk about Tableau.

Although SAS/SQL are still popular, R (and Python) experience are becoming increasingly required skills. Do you see the future belonging more with these languages or will 'front end' tools like Alteryx remove the need for the deeper level coding understanding?

Before I started using Alteryx, I was learning R and Python working at Facebook. Once I used Alteryx, I was disappointed that I had wasted so much time learning when I could have been more productive. On the other hand, I appreciate that I have a better understand of what R and Python do from having used them, but I'm all for using tools that make the job easier, more intuitive and make me my trainees more productive.

Self-Service is a term often banded about within analytics. Personally, I think it can be dangerous to give people who may not fully understand the data too much control over what they can produce - where do you see the balance between execs being able to create their own views and the risk of them going off on an invalid tangent?

I'm not afraid of this. I believe every person is responsible for their own content. If they don't understand the numbers and can't explain them, then they shouldn't use them. Pretty plain and simple. Better yet, if you're unsure what something means, just ask. An exec shouldn't be too proud or egotistical to ask questions.

The audience for your work may have a range of analytical knowledge/degree of comfort with numbers, how do you tailor your output to ensue you get the message across?

I've taught thousands of people through the years and one thing that has always worked is breaking things down to their simplest form, then building up based on the knowledge of the group your training. Each group I train is different, you have to be confident as a trainer that you can adapt to each unique set of people you are training yet challenge them just beyond what they are learning.

Any recommended sites/books/podcasts to help someone be a better analyst? 

As a matter of fact, I wrote a blog post a year ago listing out 12 books I think any data analyst should read. http://www.vizwiz.com/2016/05/12-books-every-great-data-analyst.html