(For more resources related to this topic, see here.)

For constructing visualizations, technology matters

The importance of being able to rationalize options has been a central theme of this book. As we reach the final stage of this journey and we are faced with the challenge of building our visualization solution, the keyword is, once again, choice.

The intention of this book has been to focus on offering a handy strategy to help you work through the many design issues and decisions you’re faced with.

Up to now discussions about issues relating to technology and technical capability have been kept to a minimum in order to elevate the importance of the preparatory and conceptual stages. You have to work through these challenges regardless of what tools or skills you have.

However, it is fair to say that to truly master data visualization design, it is inevitable that you will need to achieve technical literacy across a number of different applications and environments.

All advanced designers need to be able to rely on a symphony of different tools and capabilities for gathering data, handling, and analyzing it before presenting, and launching the visual design. While we may have great concepts and impressively creative ideas, without the means to convert these into built solutions they will ultimately remain unrealized. The following example, tracking 61 years of tornado activity in the US, demonstrates a project that would have involved a great amount of different analytical and design-based technical skills and would not have been possible without these:

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In contrast to most of the steps that we have covered this far, the choices we make when it comes to producing the final data visualization design are more heavily influenced by capability and access to resources than necessarily the suitability of a given tool. This is something we covered earlier when identifying the key factors that shape what may or may not be possible to achieve.

To many, the technology side of data visualization can be quite an overwhelming prospect—trying to harness and master the many different options available, knowing each one’s relative strengths and weaknesses, identifying specific function and purpose, keeping on top of the latest developments and trends, and so on.

Acquiring a broad technical skillset is clearly not easily accomplished. We touched on the different capability requirements of data visualization in article 2, Setting the Purpose and Identifying Key Factors, in the The “eight hats” of data visualization design section. This highlighted the importance of recognizing your strengths and weaknesses and where your skillset marries up with the varied and numerous demands of visualization design. In order to accommodate the absence of technical skills, in particular, you may need to find a way to collaborate with others or possibly scale down the level of your ambition.

Visualization software, applications, and programs

The scope of this book does not lend itself to provide a detailed dissection and evaluation of the many different possible tools and resources available for data visualization design. There are so many to choose from and it is a constantly evolving landscape—it feels like each new month sees an additional resource entering the fray. To help, you can find an up-to-date, curated list of the many technology options in this field by visiting http://www.visualisingdata.com/ index.php/resources/.

Unlike other design disciplines, there is no single killer tool that does everything. To accommodate the agility of different technical solutions required in this field we have to be prepared to develop a portfolio of capabilities.

What follows is a selection of just some of the most common, most useful, and most accessible options for you to consider utilizing and developing experience with. The tools presented have been classified to help you understand their primary purpose or function.

Charting and statistical analysis tools

This category covers some of the main charting productivity tools and the more effective visual analytics or Business Intelligence (BI) applications that offer powerful visualization capabilities.

Microsoft Excel (http://office.microsoft.com/en-gb/excel/) is ubiquitous and has been a staple diet for many of us number crunchers for most of our working lives. Within the data visualization world, Excel’s charting capabilities are somewhat derided largely down to the terrible default settings and the range of bad-practice charting functions it enables. (3D cone charts, anyone? No, thank you.)

However, Excel does allow you to do much more than you would expect and, when fully exploited, it can prove to be quite a valuable ally. With experience and know-how, you can control and refine many chart properties and you will find that most of your basic charting requirements are met, certainly those that you might associate more with a pragmatic or analytical tone.

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Excel can also be used to serve up chart images for exporting to other applications (such as Illustrator, see later). Search online for the work of Jorge Camoes ( http://www.excelcharts.com/blog/), Jon Peltier (http://peltiertech.com/), and Chandoo (http://chandoo.org/) and you’ll find some excellent visualization examples produced in Excel.

Tableau (http://www.tableausoftware.com/) is a very powerful and rapid visual analytics application that allows you to potentially connect up millions of records from a range of origins and formats. From there you can quickly construct good practice charts and dashboards to visually explore and present your data. It is available as a licensed desktop or server version as well as a free-to-use public version.

Tableau is particularly valuable when it comes to the important stage of data familiarization. When you want to quickly discover the properties, the shapes and quality of your data, Tableau is a great solution. It also enables you to create embeddable interactive visualizations and, like Excel, lets you export charts as images for use in other applications.

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There are many excellent Tableau practitioners out there whose work you should check out, such as Craig Bloodworth (http://www.theinformationlab.co.uk/ blog/), Jérôme Cukier (http://www.jeromecukier.net/), and Ben Jones (http://dataremixed.com/), among many others.

While the overall landscape of BI is patchy in terms of its visualization quality, you will find some good additional solutions such as QlikView (http://www.qlikview.com/uk), TIBCO Spotfire (http://spotfire.tibco.com/), Grapheur (http://grapheur. com/), and Panopticon (http://www.panopticon.com/).

You will also find that there are many chart production tools available online. Google has created a number of different ways to create visualizations through its Chart Tools (https://developers.google.com/chart/) and Visualization API (https://developers.google.com/chart/interactive/docs/reference) environments. While you can exploit these tools without the need for programming skills, the API platforms do enable developers to enhance the functional and design options themselves.

Additionally, Google Fusion Tables (http://www.google.com/drive/start/ apps.html) offers a convenient method for publishing simple choropleth maps, timelines, and a variety of reasonably interactive charts.

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Other notable browser-based tools for analyzing data and creating embeddable or exportable data visualizations include DataWrapper (http://datawrapper.de/) and Polychart (http://polychart.com/).

One of the first online offerings was Many Eyes, created by the IBM Visual Communications Lab in 2007, though ongoing support and development has lapsed. Many Eyes introduced many to Wordle (http://www.wordle.net/) a popular tool for visualizing the frequency of words used in text via “word clouds”. Note, however, the novelty of this type of display has long since worn off for many people (especially please stop using it as your final PowerPoint slide in presentations!).

Programming environments

The ultimate capability in visualization design is to have complete control over the characteristics and behavior of every mark, property, and user-driven event on a chart or graph. The only way to fundamentally achieve this level of creative control is through the command of one or a range of programming languages.

Until recent times one of the most important and popular options was Adobe Flash (http://www.adobe.com/uk/products/flash.html), a powerful and creative environment for animated and multimedia designs. Flash was behind many prominent interactive visualization designs in the field. However, Apple’s decision to not support Flash on its mobile platforms effectively signaled the beginning of the end. Subsequently, most contemporary visualization programmers are focusing their developments on a range of powerful JavaScript environments and libraries.

D3.js (http://d3js.org/) is the newest and coolest kid in town. Launched in 2011 from the Stanford Visualization Group that previously brought us Protovis (no longer in active development) this is a JavaScript library that has rapidly evolved into to the major player in interactive visualization terms.

D3 enables you to take full creative control over your entire visualization design (all data representation and presentation features) to create incredibly smooth, expressive, and immersive interactive visualizations. Mike Bostock, the key creative force behind D3 and who now works at the New York Times, has an incredible portfolio of examples (http://bost.ocks.org/mike/) and you should also take a look at the work and tutorials provided by another D3 “hero”, Scott Murray (http://alignedleft.com/).

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D3 and Flash are particularly popular (or have been popular, in the latter’s case) because they are suitable for creating interactive projects to work in the browser.

Over the past decade, Processing (http://processing.org/) has reigned as one of the most important solutions for creating powerful, generative, and animated visualizations that sit outside the browser, either as video, a separate application, or an installation. As an open source language it has built a huge following of creative programmers, designers, and artists look to optimize the potential of data representation and expression. There is a large and dynamic community of experts, authors, and tutorial writers that provide wonderful resources for anyone interested in picking up capabilities in this environment.

There are countless additional JavaScript libraries and plugins that offer specialist capability, such as Paper.js (http://paperjs.org/) and Raphaël (http:// raphaeljs.com/), to really maximize your programming opportunities.