You Ask, I Answer: Data Visualization Courses?

In today's episode, Dasha asks, I want to take some classes on analytics and visualization skills. What would you recommend? So, really good question, a very common question. There's a learning path or progression I would suggest uh taking. Starting with uh let's go ahead and bring this up here.

Starting with Edward Tufti's uh classic textbook, the visual display of quantitative information. This is by one of the oldest textbooks in the field, and it's probably one of the best to get started in terms of how do we think about the information we want to convey. Uh how do we format, how do different charts and graphs and types uh communicate information visually to somebody else. A lot of the basic principles of data visualization are in this textbook. So I would start by getting this textbook.

I'll put a link in the show notes, um, which you can get uh just down here if you want to click on through and get that disclosure to uh Amazon Associates link. So that's the first place I would start because you want to get that basic uh knowledge, that foundational knowledge first. And Tufti's book is one of the best in the field. From there, uh start looking at some of the the courses that are available. So the first one I would start with, um, and I think is probably the most practical for the average marketer, is going to be the introduction to Data Studio.

So Google Analytics Academy has a number of courses for free. Well, Data Studio is a great basic course that teaches you the interface of Data Studio, but also applying some of those uh best practices for data visualization. Uh you'll see that in Unit 4, the data visualization basics. Also, bonus uh when you complete this course, you'll have the ability to use Data Studio well. And it's a very powerful free tool.

Plugs into Google Analytics, plugs into Google Search Console, a bunch of other things. Uh, and that really uh is is practical and applicable information right away. After that, take the data visualization practical approach for absolute beginners from Microsoft. So this is available on edX. It is free.

Uh you'll notice it's an archived course, which means that like the instructors are not online, uh, the discussion forums are closed and stuff. You you it's just a course by itself. But it's an excellent course, it's a uh about a four-week course uh that teaches you uh visual literacy, and uh again, applying a lot of those data visualization practices. Um I think what put the most important module in here is thinking about the things that you're gonna do wrong with data visualization. Uh if you've ever seen uh the average business dashboard, uh they're usually a hot mess, right?

There's stuff laying all over the place. Uh someone's tried to cram too much information on it. And this is a really good course for getting you to think about visual literacy, right? What needs to be communicated, what does not need to be communicated. After you've got this down, um, it's time to kick things up a level.

One of the challenges with data visualization is the data itself may or may not be any good. Um, and what data you want to communicate also may not be available outside the box uh out of the box. So, really good example, uh, Google Analytics uh has a ton of data in it, but virtually no transformations of any kind. So if you look at like your website traffic, there's no mean, there's no median, there's no basic statistical approaches to it. Uh, you get what you get in the tool itself, and that's fine to start.

Um, it's not fine if you want to add, you want to create value added insights. To do that, you need some statistical knowledge. So the next course I would recommend taking is over at IBM's cognitive class, go to cognitive class.ai, there's a stats 101 course. And this is uh an excellent course for teaching you the basics of statistics, right? So uh things like descriptive stats, uh variance, probability, correlation, the 101 stuff that frankly we should have all taken in college.

Um I did take a stats course in college, and I did not pass it because uh the teacher wasn't great. We now have the opportunity to go back and fix those mistakes of the past uh and taking stats one so that we learn how to think about the data that we're presenting and make sure it is valid and and clear and obvious what it is that we're doing before we slap it into into a visualization, right? Remember that visualization means nothing if the data that makes it up is wrong. So stats one on one is the is the I would say the fourth thing that you should take. The final thing that you should take, and this is now kicking things up a notch, is uh data visualization with R.

So the programming language R, again, this is a cognitive class uh IBM course to also free. Um this is on how to do the actual visualizations in the programming language R. So if you are doing any kind of really heavy uh statistical or data science work, including stuff like you know, pulling social media analytics and and Google analytics data into an environment that you can uh analyze it. R is the language to do that, it's one of the languages to do that. And it has a visualization library built in that is a little on the tricky side, but if you want to be able to uh programmatically do visualizations, meaning uh once you've done it once and you want to rerun that airport the next month or next week, whatever, uh you can literally hit you know execute code and it will redo everything for you so you don't have to do it again.

That's the value of programmatic uh visualization. This is the course to teach you how to do that. Now, you'll note that they want the prerequisites, there is a a an R101 course. If you have not taken that one, I would take that one as well. Uh because that will get you all the bare bones basics of how to use the R programming language.

Now, except for Tufty's book, all of these courses are free, right? So there's no financial cost in taking them. The only cost is your time and your effort, your willingness to study. If you take all four of these, five if you count the R1 R101 course, if you take all five of these and you are diligent about it, you'll have uh I would say a great working competency of data visualization and the ability to apply it to whatever marketing data you're looking at. This makes you something of a unicorn, because this is not a skill that a lot of marketers have, right?

Uh a lot of marketers kinda shy away from the math side of things, the quantitative side of things. But if you have these skills, then you can apply your creative uh abilities and your quantitative abilities and drastically increase the amount of uh value you bring to an organization, uh, drastically increase the amount of money you can earn. Uh and you might find that you really enjoy it. Uh, I certainly do, despite having a rough start in statistics. Um that's the order.

And I would I would do this these in that order so that you if you try and jump into R101 right away, it's not for everybody, right? And it it can be a little discouraging. So get the foundations down first and then elevate into the more technical stuff afterwards. Really good question. Um good luck with the courses.

I I find they're all very good. They're all taught by legitimate subject matter experts. Um I look for that in evaluating courses. Uh I look for people who are actually qualified to be teaching them. Um and remember that a good chunk of the education for this is going to be practice.

So once you've taken the courses, you then have to put it into practice and keep putting it into practice. It's like anything else, you know, uh working out, whatever. Uh, you gotta keep doing it to keep yourself strong. If you have follow up questions, leave them in the comments box below. Subscribe to the YouTube channel and the newsletter.

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