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. Hi, I'm Jen. Welcome to the channel! 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 I think are more important for you to learn first before
learning others. The first criteria is 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 is how easy is it to learn and combine with that 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 to
be able to use. I think that's an important criteria 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 tableau, you're
probably very new to visualizations. tableau has in excess of 57,000
customers worldwide. I would say they're the biggest specific visualization tool
that's out there. So in terms of a lot of job opportunities, yeah, there are a lot of
companies that are going to use tableau. tableau is also really simple to learn,
to use. There's a pretty good resource base online both from the company and
from other users because there's just so many people using it. That
makes it pretty simple to use. It's a pretty intuitive system to learn
especially if you've got analytics experience or analytic skills already.
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. I think that eventually we're
going to move away from so many standard, 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 is
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 there are
servers in the background that are structured and feeding into or that
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. The next product that
we'll talk about is QlikView. This is really tableau's main competitor right
now. They're at a little over 40,000 different customers using their
installation. This is something that I actually learned by myself and I was
shocked at how quick it was to learn. There are a lot of things that are
specific to how QlikView works that do take a little bit of time to figure out,
but there's again a lot of resources online to help you.
And once you figure it out, it's really straightforward. I would say in well
under a week I was pretty familiar with building dynamic reports, importing lots
of different data sources. It was pretty straightforward to get set up with. You
may also find that a lot of companies that have another software also use
QlikView because it's pretty cheap to install and it gives so much flexibility.
QlikView is one of the few tools that I think is fantastic for both big data
visualization and small data visualization. If you want to go big, you
can go massive. You can have all of those data warehouses. You can have all of the
IT structure that QlikView is drawing from, but if you want to go small, you can
import Excel files as your data sources. This is one of the ways that I've
used it in the past is taking a lot of Excel sources where I couldn't fit all
of the information into one excel and have it function with any amount of
speed, but I could take them into QlikView. Take ten
different things that I wouldn't want to cram into one excel sheet and work
instantaneously with in QlikView just working on my desktop. In terms of cost
and ease of setup ,this really goes back to how the company wants to set it up.
Like I said, you can get started the day you get the software. They do offer some
free options for download and use that limit how much you can share the
information and the files you create, but are a fantastic way for you to be able
to learn QlikView for free. The third tool we're going to look at and I
recommend using is Power BI. This is really widely available. Again, you can
get your hands on a copy that has some limits, but that'll let you learn it for
no cost and if you're familiar with other Microsoft products - and let's be
honest, if you don't know Excel you're probably not getting into an analyst job -
you'll probably find power bi very easy to use. It's very similar to the
rest of their setup. They have great visualizations, a great database of
content there to be able to use. Power BI doesn't have the variety of
visualizations that tableau and QlikView offer,
but for most people, it's going to be more than sufficient for what you need. If
you're getting into more advanced things, you might need to look at a different
system, but 90% of the time, Power BI is going to have you covered. Power BI is a tool
that I recommend more for small to medium sized amounts of data. It, right
now, doesn't function really well with big datasets. That's something that
they're working on and I expect in the future will be solved, but right now it's
really better for smaller volumes of information. Because of that, the cost and
ease of setup is also pretty low if you're using small amounts of data.
I recommend using the desktop version. It just seems to function better.
If you're watching this a month or a year from now,
I'm sure it will have changed - I hope it will have changed because they are
constantly working on improving it. But right now it's really more of a small
data, a small to medium size company sort of program to look at. The fourth type of
data visualization program is really as several options and that's Python, R, and
SAS. If you already know these languages then you can create fantastic
visualizations within the tools. If you don't know these languages, this is going
to be the hardest of the options I'm talking about today to learn because
there is a lot of information to learn out there. On the plus side, there are
fantastic resources online you can find the answer to most questions and if you
can't find the answer there's a wealth of different people using it that will
probably help you solve the problem. In terms of the quality of visualizations,
it's usually pretty good. You can make really complex visualizations, but where
I would dock a few points on all of the programming visualizations is the more
complex of visualization the more complex the programming is going to have
to be to pull it off. So it can be more time-consuming than using one of the
more data visualization geared programs. If you already know the skills for these,
you could use them for small data, specifically Python and R, but in the
vast majority of cases this only makes sense for big data because you're going
to have data warehouses set up and a lot of data structure behind the scenes for
this. You can do some small data, but it's these options are massive
overkill for small data. It's probably going to be 1) really
expensive if you get SAS. I love SAS. I think it's a fantastic
program, but it comes with a price tag that matches the flexibility and options
that they have. And the same with Python and R - not that they're expensive to
install and to do the software because we're talking about mostly open source
options, but it can be really expensive to set up the background. 2) That also
means a lot of time to set up the background. If you know how to use
these tools already then learn the visualisation aspect of them beyond just
the analytics, a more analysis side of using this coding. Fifth, how could I
leave out Excel? This is so basic and I think a lot of analysts - it just kind
of makes them shudder when they hear "I need you to know Excel" because we know
that there are so many more powerful tools. All of these other options that I
talked about can do more than what Excel can do. But if you're working as an analyst and
you're doing ad hoc analysis or working with small amounts of data, it's really
hard to beat Excel. It's really quick to set up. They have a good variety of
simple visualizations. You are going to be limited, but it really does offer a
lot of options especially for small companies and small amounts of data that
even if you know how to use all the other tools it still may be quicker to
do it in Excel for some of the smaller ad hoc, simple reporting that you need to
do. Those are my recommendations for the five to eight, depending on how you
define my programming languages, tools to learn for data visualization. Which ones
do you know? I personally haven't worked very much with tableau, but I love
QlikView. I've worked with, of course, Excel and dabbled in Power BI.
I'm really interested to learn more on each of these, but let me know - which
one are you working on learning or do you already know? Do you agree with what
I picked? Do you think I missed something major that's another system people
should be using? In the next few weeks, I'll also be talking about what
programming languages you should learn and other data analytics tools you
should know how to use. So be sure to come back or subscribe and turn on
notifications to find out when those videos go up.