Top 5 Data Visualization Tools


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.

7 Comments

  1. Hi! What do you think is the best library for visualization in python (plotly and seaborn are good for me haha)?

  2. Analyst here, good list but I am missing Domo. The strength of that tool specifically is the ease of use if you work in a company where many different data sources need to be combined. Like a de-centralized corporate organization with several CRM and ERP tools. Good video! I would put Power BI on 1, due to the complete set of data tools. I'm not that familiar with Tableau, does that tool also have professional data scrubbing and modeling capabilities?

  3. One of the best videos I have seen on the topic. Its so clear well explained. No nonsense or beating around. Excellent video.

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