Data visualization is one of the most critical skills for any analyst and really most business people to know. No matter how good you are at analyzing data if you can't package it in a way that communicates what you've learned and is easy for other people to understand then a lot of that analysis gets lost.
Let's look at the top five data visualization tools that you should learn. I've gone through a few different criteria in deciding which products to include because there are a lot of options out there. It's really hard to go wrong with any of them, but there are some that are more important for you to learn first before learning others.
The first criteria are availability and usage - so how many customers do they have? Meaning how many potential employers do you have that are going to want you to have the skill as your visualization tool? I think this is really key when deciding which tool to use or which skill-set to build for a job.
The second criteria are how easy is it to learn and combine with how easy is it to use? There are some products that offer fantastic options if you know a lot of coding and there are others that you need to know no coding whatsoever t to be able to use. I think that's an important criterion because it can also mean how long does it take you to be somewhat proficient with using that tool.
Third: quality of data visualizations. Let's be honest. If it looks like crap or like you hand drew the visualization, it does not belong in your list of skill sets to learn unless you're in a company or want to get into a company that uses a legacy system. And even in those cases, I still recommend learning one of these newer tools. You want to learn a tool that has great visualizations - a quality that reflects the quality of the inputs that you're giving it.
Fourth, I'll talk a little bit with each of these products on whether they're better suited for big data or smaller amounts of data. Because I think this does make a difference which one you should learn depending on industry and company that you're getting into. Many of them translate well one to another, but most programs are set up that they're either really geared towards lots of information and a heavy IT setup or they're geared towards user entered data - whether it's spreadsheets or the like - that make them much more flexible with small amounts of data, but can sometimes make connecting vast amounts of data very difficult or bog the system down. We'll look at that a little bit.
My fifth criteria: cost and ease of setup. This again talks a little bit about big data versus small data which also gets into what size company or industry are you getting into. If you're getting into a company that's a start-up or a smaller company, small to mid-size, they're probably going to be going with a cheaper solution because they just can't afford the investment of some of the more expensive tools that are out there. Even if in some cases the more expensive tools are better tools.
Really, at the end of the day, there are so many tools that are equivalent and it's really just a matter of the application that you have. Some are more suited to certain companies or certain industries than others and that's not a bad thing. That customization makes it really nice for companies to pick what they need and also for you to know what type of program that you should learn to boost your data visualization skills. The first product we're gonna look at is tableau. If you haven't heard of the tableau, you're probably very new to visualizations. tableau has in excess of 57,000 customers worldwide.
You're going to find it pretty straightforward. The vast usage of tableau carries over into their visualization quality. They have great visualizations and the ability to do interactive reports which I think are going to become more and more the standard. It can make us we're going to move away from so many standards, static reports maybe in PowerPoint that get circulated in companies and more towards the dashboard interactive setup that makes it easy to get information on demand and it doesn't become obsolete the moment that it gets published. Now we're on to the fourth criteria which are big data or small data. tableau is really better suited for big data than small data and part of that's because of the setup. It really works best when the tableau is sitting on top of. They have a ton of integrations with things like Hadoop, Amazon Web Services (AWS), MySQL, SAP...tons of other connections that they have.
This, again, gets back into big data where there needs to be more structure. There's probably an internal IT department or at least an on-call IT department that does a lot of work with the company that's managing all of these integrations. In terms of cost, because of this tableau can sometimes be more expensive. Not so much for the software itself, but for all of the other integration and the background structure that needs to be in place to be able to use it. Still, it's so widely used - almost 60,000 different companies using it - that it is a fantastic option to learn and I think it's a tool that's really interesting to learn, gives great visualizations.