You may not think you've got much in common with an investigative journalist or an academic medical researcher. But if you're trying to extract useful information from an ever-increasing inflow of data, you'll likely find visualization useful -- whether it's to show patterns or trends with graphics instead of mountains of text, or to try to explain complex issues to a nontechnical audience.
There are many tools around to help turn data into graphics, but they can carry hefty price tags. The cost can make sense for professionals whose primary job is to find meaning in mountains of information, but you might not be able to justify such an expense if you or your users only need a graphics application from time to time, or if your budget for new tools is somewhat limited. If one of the higher-priced options is out of your reach, there are a surprising number of highly robust tools for data visualization and analysis that are available at no charge.
Here's a rundown of some of the better-known options, many of which were demonstrated at the Computer-Assisted Reporting (CAR) conference last month. Others are not as well known but show great promise. They range from easy enough for a beginner (i.e., anyone who can do rudimentary spreadsheet data entry) to expert (requiring hands-on coding). But they all share one important characteristic: They're free. Your only investment: time.
Before you can analyze and visualize data, it often needs to be "cleaned." What does that mean? Perhaps some entries list "New York City" while others say "New York, NY" and you need to standardize them before you can see patterns. There might be some records with misspellings or numerical data-entry errors. The following two tools are designed to help get your data in tip-top shape to be analyzed.
What it does: This Web-based service from Stanford University's Visualization Group is designed for cleaning and rearranging data so it's in a form that other tools such as a spreadsheet app can use.
Click on a row or column, and DataWrangler will suggest changes. For example, if you click on a blank row, several suggestions pop up such as "delete row" or "delete empty rows."
There's also a history list that allows for easy undo -- a feature that's also available in Google Refine (reviewed next).
What's cool: Text editing is especially easy. For example, when I selected "Alabama" in one row of sample data headlined "Reported crime in Alabama" and then selected "Alaska" in the next group of data, it led to a suggestion to extract every state name. Hover your mouse over a suggestion, and you can see affected rows highlighted in red.
Drawbacks: I found that unexpected changes occurred as I attempted to explore DataWrangler's options; I constantly had to click "clear" to reset. And not all suggestions are useful ("promote row to header" seemed an odd suggestion when the row was blank) or easy to understand ("fold split 1 using 2 as key").
And while the fact that DataWrangler is a Web-based service makes it convenient to use, don't forget that it sends your data off to an external site -- which means it isn't an option for sensitive internal information. However, there are plans for a future release of a stand-alone desktop version. Another important thing to keep in mind is that DataWrangler is currently alpha code, and its creators say it's "still a work in progress."
Update, Jan. 9, 2014: An alpha project when this article published in 2011, Data Wrangler was subsequently completed but is no longer supported, as its team is now working on a commercial product. However, the service can still be used as is at the URL above.
Skill level: Advanced beginner.
Runs on: Any Web browser.