Finding new insights (or sometimes just making your point) can be one of the most satisfying exchanges in business. But when that point is based on ever-growing Big Data sets, often the best way of presenting it is through a sexy-yet-meaningful data visualization. But most folks, even power users, consider data visualizations as being out of their technical reach or even as the exclusive province of data scientists or at least database administrators (DBAs). Fortunately, with self-service business intelligence (BI) becoming increasingly popular in even small to midsize business (SMB) scenarios, many users have highly capable data visualization tools at their fingertips and don't even realize it.
Continue Reading Below
And, before we go any further, let's understand what we're talking about here. The term "data visualization" doesn't necessarily refer to an arcane melding of SQL and PC graphics modeling. It's really just a general term that applies to any graphic that explains the significance of a new insight or data set visually rather than simply numerically. Technically, that simple pie chart you can one-click using Microsoft Excel is a data visualization. But, as technology has suddenly begun evolving in leaps and bounds over the traditional databases and spreadsheets to which we're accustomed, new kinds of data visualizations have become possible using a host of new tools and tech. And that's created a mystique around them that's kept many users from trying them, even though the basic tools to do so are already in their hands.
Even if you don't have access to one of the new breed of self-service BI tools that have fairly advanced data visualization baked in, you can still experiment with the concept because there are a host of third-party visualization tools available to anyone with a web browser. I've listed 10 of them below.
1. Tableau Public. This is right at the top because it's essentially the same platform as our self-service BI tool Editors' Choice winner Tableau Desktop. The company chose not to make its free version feature-poor. Instead, this is the full version of Tableau that's available for free download, with only one caveat: Everything you create with it is public, which means you'll automatically be making it available on the web via Tableau's visualization gallery.
2. Tableau Gallery. Tableau's gallery is cool enough to warrant a mention all its own because you don't need to download the tool nor use it to benefit from the gallery. Every visualization here can be downloaded into documents and email, or embedded into webpages with code snippets provided by Tableau. Other folks have done tremendous work on some truly impressive data visualizations and Tableau has curated that content and made it available for download. This is a great resource, not only for business people but also for researchers, students, and journalists looking for ways not just to flesh out and beautify their content but to keep it current, too.
Continue Reading Below
3. Microsoft Power BI. This is the last shameless plug for one of our reviews but I have to include it because, just like Tableau, Microsoft Power BI can be downloaded for free. And also just like Tableau, Microsoft has a visualization gallery that can be accessed by both Power BI users and folks simply looking for freely available visualizations.
4. Openheatmap. This one purports to transform your spreadsheet, presumably encumbered with some kind of geographical data, into a functioning heat map with just one click. It works with Google Spreadsheets so you'll have to import your Microsoft Excel spreadsheet there if you want to use Openheatmap. But that's a relatively trivial requirement considering the possible results.
5. Weave. This is a full-fledged data visualization and analysis tool that's distributed on the donation model rather than simply charging for seats. It's not as beginner-friendly as some of the self-service BI tools we've reviewed, and a lot of it is catered towards developers. But, if you're willing to wade through some small-font documentation, then the tool is capable of some impressive visualization results.
7. Silk. This is another data visualization tool that's entirely free just for signing up. It's also very easy to use, which makes it a great place for beginners to start. Just like Openheatmap, Silk wants your basic data in a spreadsheet uploaded first. Then, you can hop into Silk's drag-and-drop visualization environment and both explore your data as well as build visualizations around it. Gaining expertise is easy as it's got solid online documentation and a library of instructional videos. And, if you want to see what other users have done with Silk, then there's a publicly available gallery, too.
8. Chartbuilder. This is a well-known chart-creation tool that was made publicly available by financial news website Quartz in 2013. Quartz had developed the tool in-house so its journalists could quickly render numerical data visually to make their stories stand out. Ironically, Chartbuilder isn't very pretty itself and also is not the easiest tool for rank beginners to use. You'll need to understand how to download the tool and activate a Python script to get it running.
But after that, it's simply a matter of cutting and pasting data into the tool (also not pretty but very easy), and then generating a graphic that you can tweak via the tool or via style sheets. The only downside to the tool (aside from a little upfront complexity) is that it doesn't generate interactive visualizations like most of the other tools on this list do. Chartbuilder creates only static charts, though these are very polished, as befits something intended to go from numbers to slick published content in just a few steps.
9. Information is beautiful. This is simply a growing library of striking, prebuilt visualizations that other people have created by using a variety of tools. The gallery is fun and everything is downloadable, though you'll need to pay attention to the licensing agreements. These agreements give free access to individuals (especially students and academics) but, if you're looking to use these visualizations for commercial work, you'll need to fork over some dough. Exactly how much depends on who you are and on an email exchange with the website's owner. Just to warn you: We asked to pay for a visualization for this story two weeks ago and still haven't heard back so, if fast turnaround is part of your agenda, look elsewhere.
10. Open Refine. There's an oft-overlooked underpinning to a successful data visualization: data transformation. That's especially true today when Big Data is trying to provide insights across different data sources, maybe a spreadsheet, maybe a long transaction log gleaned from a machine learning (ML) algorithm.
Transforming data generally refers to the painful (for normal people) process of taking a whole bunch of disparate numbers and turning them into a sleek set of relatable data. That means cleaning data (formatting and error checking), transforming it (changing from one format such as native Microsoft Excel to another, such as XML), and then making it available to external services such as webpages and those BI tools you're using. If you're thinking this can be a painstaking, eye-watering, brain-bending task, then you'd be right…unless you use a data transformation tool such as Open Refine. This tool began life under Google's flag but was rebranded to stand on its own. It's still both free and easy to use so, if you're banging your head against a mountain of mismatched data, check it out.