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If you’ll be in Atlanta on Tuesday, January 25, we’ve got a special treat for you. Our own Jon Buffington, CTO of Juice, will be at the Atlanta Spring Users Group discussing how we use Spring Framework 3 and Adobe Flex 4 to build web-based data visualization applications. The meeting begins at 6:30 p.m. at One Alliance Center, Suite 630, 6th Floor Conference Room, and Jon’s presentation begins at 7:00 p.m.

The application features components from Juice Analytics JuiceKit™ visualization library http://www.juicekit.org, and Jon’s presentation will demonstrate the following.

  • Integrating Adobe Flex and Spring Framework using both Spring BlazeDS Integration and Spring Actionscript .
  • Accelerated data warehouse querying using Spring Framework’s JDBC support and Spring Contexts.
  • Multiple application modes using Spring Contexts (prior to more elegant support coming in Spring Framework 3.1).

You can find more details about the Atlanta Spring Users Group and Tuesday night’s event at http://www.meetup.com/AtlantaSpring/calendar/15896725/.

We hope to see you there.

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Strata 2011

We’ve had enough of the snow in Atlanta and D.C., so we’re off to warmer weather (for a few days, anyway)!

Please join us for the O’Reilly Strata “Making Data Work” Conference, February 1-3, 2011, taking place in beautiful Santa Clara, CA. (Can you say boondoggle?! Seriously — there’s a whole lot to gain from the entire conference which is why you’ll want to make as many of the sessions as you can, no matter how beautiful this place is!)

As a Juice fan, you qualify for a 25% discount on the registration fee for this event which will draw everyone from startups to Fortune 500 companies looking to learn more about “Turning Data into Decisions” — one of our favorite topics.

Zach Gemignani, founder of Juice Analytics, and Ken Hilburn, VP, Community Enablement, Juice Analytics, will be hosting the Tutorial, “Make People Fall in Love with Your Data: A Practical Tutorial for Data Visualization and UI Design” at 9:00 a.m. PST, Tuesday, February 2, 2011 in Mission City B1.

To register and receive the 25% Juice Fan discount, enter the code str11fsd. More information on the conference including other speakers, conference schedule and highlights is available at http://strataconf.com/strata2011. The Conference location, The Hyatt Regency Santa Clara, is booked for the event. However, accommodation information is available at the
Santa Clara Convention and Visitor’s Bureau. Feel free to reach out if you have questions, and we’ll steer you in the right direction.

We hope to see you in Santa Clara!

Visually,

Lisa

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The 12 Days of Christmas, as referenced in the song, starts in most traditions on Christmas Day and ends on January 6. Our version, the “12 Days of Data Visualization”, allows you to have all of your gifts in one day — bonus. Each “day” links to data visualization resources that we’ve shared with you over the years or find particularly enlightening, and are well worth repeating — the proverbial “gifts that keep on giving”.

On the first day of Christmas, my true love gave to me, a white paper to set my data free.

On the second day of Christmas, my true love gave to me, Two Hans
Rosling presentations.

On the third day of Christmas, my true love gave to me, Three tree-maps.

On the fourth day of Christmas, my true love gave to me, Four font rules.

On the fifth day of Christmas, my true love gave to me, Five filter features.

On the sixth day of Christmas, my true love gave to me, Six principles of context.

On the seventh day of Christmas, my true love gave to me, Seven data viz galleries for inspiration.

On the eighth day of Christmas, my true love gave to me, Eight better dashboards.

On the ninth day of Christmas, my true love gave to me, Nine online resources (and a great Stanford data viz video).

On the tenth day of Christmas, my true love gave to me, Ten metrics no-no’s.

On the eleventh day of Christmas, my true love gave to me, Eleven lines of code.

On the twelfth day of Christmas, my true love gave to me, “12-step” pie chart treatment.

From all of us to you and yours, have a merry Christmas, and a happy New Year! Wishing you many successful visualizations in 2011!

The Juice Analytics Team

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NFL Stats Visualization

David May

Geeking out on NFL data shouldn’t be left only to the stats junkies at Football Outsiders. Our NFL stats “spike chart” is an easy way to see who’s leading the league in passing, rushing, receiving, tackles, team offense, and team defense. By showing key metrics side by side, you get the full picture of a player or team performance–not just the highlights. Click on the image to see the live visualization.

NFL Stats Visualization

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This summer I had an opportunity to lunch with Fernanda Viegas and Martin Wattenberg, a couple of the brains behind ManyEyes–the brilliant data visualization tool that remains an IBM toy. When I met them, the pair had recently started Flowing Media, a start-up focused on visualization solutions for media data. It was a short-lived venture–Google came calling and Martinanda decided to take their talents to a newly-minted Google “Big Picture” data visualization group.

Before the move, Flowing Media released an open-source desktop visualization tool for event-based data. TimeFlow was created along with Sarah Cohen, a professor and journalist, as a tool for reporters to analyze historical data.

The motivation behind TimeFlow comes from Sarah’s realization that visual analytical tools for reporters are rare. There are good visual presentation tools out there, but those that allow journalists to mull over hundreds and thousands of data points, slicing and dicing the information as they go along are harder to come by. Given this mandate, we set out to rethink timelines, striving to always show as much textual detail about the data as possible (a goal dear to reporters that, interestingly, goes against the visualization impulse to always aggregate).

Timeline Application

Here’s what I like most: Flowing Media took a common analysis problem and built a focused solution to solve that specific problem. Most analytical solutions attempt to be all things to all people–and fail in the process. With about 1,000 downloads, I doubt TimeFlow has found its way to all the people who could benefit. In my non-exhaustive tour of the tool, I found that it does a bunch of things well:

  • Easy start-up. For a non-technical person, TimeFlow may seem a bit intimidating. It is hosted on Github and downloads as a .jar file. However, I had it up and running seconds on my Mac.
  • Uploading data. TimeFlow makes uploading a simple, flat file easy by letting you paste into a text box or selecting an existing CSV file.
  • Smart options for data views. It provides a variety of relevant ways to present this timeline based data, including a timeline visualization, calendar, list, table, and bar chart.

Timeline view

  • Data summary. An unexpected little feature is a summary of your data file (below). This is the type of useful view that only true data-lovers would think to include.

Timeline data summary

  • In-line data editing. I was pleased to see that you can edit your data as you go. If you see something in a chart that doesn’t make sense, simply right-click to change any of the fields on the fly.

Now that Fernanda and Martin have moved on to Google, we’ll be curious to see what project they take on. It is not hard to imagine an extension of this TimeFlow visualization tool applied to Google news search results.

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The Presentation by Andrew Abela

Last night I read Andrew Abela’s recently released e-book The Presentation: A Story About Communicating Successfully With Very Few Slides. Abela is a presentation guru (and friend of Juice) who travels the country fighting the good fight against “Death by PowerPoint.”

His focus is a little different than the Nancy Duarte (Slide:ology) and Garr Reynolds (Presentation Zen) who focus on conveying a message with images and minimal text. While that style has a place for “Ballroom Presentations”, Abela sees a need for a different type of presentation for “Conference room Presentations.”

The wise professor in his story (I prefer to describe myself as an Indiana Jones-style entrepreneur in my narratives), explains the important characteristics of conference room style presentations as the following:

“they have extensive—but always relevant—detail; they are printed, not projected; and every slide must pass the squint test.””

The story also outlines one of his core presentation principles, the SCoRE method, which involves repeating a pattern of Complication, Resolution, and Example. It is a story-telling technique that builds audience buy-in as you go along.

Abela has taken his own advice by persuading his audience using a compelling story filled with complications, resolutions, and examples. I really recommend this entertaining, quick read as a great refresher for the core concepts of his Extreme Presentation method. You can sign-up for Abela’s mailing list and to receive a free copy.

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SEA

We’re back from beautiful Seattle having immersed ourselves in the data visualization party known as the 2010 Tableau Customer Conference. It was a wonderfully planned and executed conference during which we met lots of great Tableau users, exchanged data visualization tips, and learned a bunch about what Tableau is up to in version 6.0 (the most highly anticipated enhancement is no doubt the 100x performance improvement of the data engine.) The folks at Tableau are definitely ramping up for some great things and it was a privilege to be part of it.

As most of you know our core business is about building custom information applications to make information accessible to everyone, not just analysts. But we do so love the work they’re doing over at Tableau and keep a close eye on them. As a result, when they extended an offer for us to speak, we were thrilled.

Following our sessions, I was all excited about the reaction we had gotten from our attendees when one of my coworkers pointed out that I had made a terrible mistake: I neglected to give proper credit to Stephen Few. Part of the content that we covered was about how to effectively position elements in an information display to make it easy for the brain to understand what it’s seeing. To do this we discussed “6 Principles of Visual Context”:

  • Principle of Proximity – Things that are visually close to each other are related
  • Principle of Similarity – Things that look like each other (size, color, shape) are related
  • Principle of Enclosure – Things that are enclosed by a shape are related
  • Principle of Closure – We see incomplete shapes as complete
  • Principle of Continuity – Things that are aligned are related
  • Principle of Connection – Things that are visually connected are related

A great set of guidelines that explain so much about why some things make visual sense and others don’t.

However, in the heat of the moment, I neglected to point out that these principles are based on some very nice work Stephen performed a while back. We’re big fans of his and want to make sure we give credit where credit’s due. So, if you you’re not familiar with these principles, or haven’t reviewed them recently, please check them out. Very powerful stuff.

As far as the conference goes, if you’re a Tableau user, you should plan on attending next year. At about 700 attendees, it was nearly twice as big as the 2009 conference, and if the passion and excitement of Christian Chabbot is any indication, next year will be even bigger and even better.

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So, to recap, we kicked off our Viva Visualization Tour in Atlanta in July to an eager and anxious crowd. In Boston, we were met by heavy downpours (of rain, that is), and some very dedicated data visualization fans who braved the weather, as their drought ended when we arrived in the Boston area. We were glad to be of service–and to bring lots of data visualization know-how with us, as well.

Now, it’s your turn, D.C. September 16th, rain or shine, we’re ready to make an even bigger showing in the Capital city and home to Juice Analytics.

If you’re in the D.C. or surrounding areas, come meet Juice and learn about communicating better with data.

What you’ll have when you leave:

  • visualization best practices training around information layout and workflow, information visualization, chart selection, and styling
  • networking within the D.C. visualization community
  • a full breakfast buffet
  • opportunity to pick the Juice collective for tidbits of vizo-knowledge
  • a few pieces of custom designed Juice schwag

What Juice gets out of this:

  • a much needed visit to one of the country’s greatest cities
  • a chance to meet D.C. folks who love making visual sense of data
  • opportunity to talk about the stuff we’re excited about with people who are actually willing to listen (besides our moms)
  • a big ol’ food bill

So, if this sounds like great fun to you (and who wouldn’t think so), register. We can’t wait to meet you.

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This is the third in our series of topical reviews of the Federal IT Dashboard. As Ken noted in his discussion of Flow, we see this publicly-available dashboard as an opportunity to share some thoughts on ways to evaluate and improve dashboard design, while acknowledging the hard-work and challenges that went into its development.

Today we’d like to take a quick tour of the charts in the Dashboard and ask three questions of each:

  1. Is it the right chart for the data being displayed?
  2. Is the chart designed to communicate effectively?
  3. How would we redesign the chart?

A column chart is used to display the top departments by IT spend.

Federal IT Dashboard column chart

They’ve chosen an appropriate chart for the job, though we often will go with a bar chart over a column chart. Bar charts tend to use space more effectively because the category labels can be wider. Notice how all the Federal Agency labels had to be compressed into an abbreviation (e.g. DOD, DOC, DOT, DOJ), almost requiring a beltway-insider to translate.

One quirky feature is that the y-axis is labeled “($) Billions” but there are no values on the bars (on rollover, a tooltip shows the values with “$B”).

Finally, the chart uses animation when it is first displayed to grow each of the bars from the baseline. This is a useful effect that emphasizes the largest values which keep growing after the others stop. Not as useful: the reflection effect under the chart doesn’t help with comparing column sizes.

Our redesign of the chart would include more explicit labeling and the total IT spending at the top.

Federal IT Dashboard bar chart


Pie charts are used to show the distribution of performance of IT projects.

Federal IT Dashboard pie chart 3

We’ve said a lot of mean things about pie charts over the years. We are not alone. Nevertheless, pie charts can have a legitimate place in presenting data. Here’s how these pie’s fall flat:

  • At their miniature size, the relatively proportions are hard to see.
  • On the summary page, there is no legend or labeling to provide any meaning. I appreciate that green is good and red is bad, but what are the definitions for those colors?
  • As always, a 3d pie chart distorts values by making the “closer” slices seem bigger.
  • Readers will find it difficult to compare across the three pie charts.

An alternative to multiple pie charts in this situation is a stacked bar chart:

Stacked bar chart


Line and area charts are used to display trends in project performance.

Federal IT Dashboard line and area charts

These charts are appropriate and reasonably well executed. Our concerns would be with the design: the labeling isn’t efficient for the limited space, the lines colors aren’t high contrast, and the entire chart feels like it was compressed into too small a space. Here’s our take on it:

Federal IT Dashboard line charts


A treemap is used to show the composition of projects and/or spend based on agency, functions, service groups, etc.

Federal IT Dashboard treemap

Is this the right chart for the job? Most definitely. Treemaps are awesome at displaying hierarchical data that can be summed at each level. It provides a comprehensive view of IT spending composition while allowing you to see changes and drill-down for more detail.

The design of this treemap needs refinement. The developers used the out-of-the-box version of our JuiceKit™ treemap, so we have room for improvements in our default settings. For example:

  • The borders on the boxes are clumsy and distracting. We’ve started to de-emphasize the border with white or light grey.
  • The label names provide very little value as most of them are a truncation of the word Department. A narrower font at normal weight would help. Creating an alternative label that leads with useful information would be better: “Commerce” rather than “Department of Commerce.”

Here’s a treemap demo that feels a lot cleaner from a design perspective:

Airline treemap


All in all, the Fed IT Dashboard does a fine job of choosing appropriate visuals and keeping the chartjunk low. Here are a couple good source to help with these decisions:

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This is the second part in a series about better dashboard design. This part, Flow, follows Message to highlight the importance of taking that message and making it easy to work through in light of the larger business process.

Having said that and before we continue, we wanted to reveal an internal conversation we’ve been having about the example (Federal IT Dashboard) that we’ve selected to demonstrate some of our thinking. We appreciate that it is hard to build dashboards that satisfy a broad audience. From initial conception to delivery, these forces, often at cross-purposes, can chip away at an intuitive and clear design. This series of posts isn’t meant to disparage the hard work and deep thinking that clearly went into the design of the Fed IT Dashboard; it is meant to offer some perspective and hopefully useful lessons for others in their dashboard design projects.


Part 2: Flow

In Part 1: Message, Zach introduced the results of some thinking we’ve been having about the Federal IT dashboard and how to continue to improve the effectiveness of its ability to communicate with data. This week, we’ll take a look at the next step in the process: Flow.

Simple

Communicating with data is like telling a story: there’s a beginning, a middle, and an end. When you grab that latest book from your favorite author, you know just where to get started, and (if that author is any good) you know exactly when it’s the end. Well, telling a story with a data application is just the same. The information designer needs to lay out the components of the story in a way that facilitates starting, learning, and finishing strong. We call this the workflow of the application. A great application workflow is not evidenced by easy-to-use software (although this might very well be a byproduct), but rather a great application workflow is about helping the user transparently achieve the objectives that make them successful at their job.

So let’s look at some of the principles that we at Juice would use to take the flow of the Fed IT dashboard to the next level.

Principle 1: Know what objectives people are trying to achieve

The first step to knowing the objectives of the users is to know who the users are. Because of the tremendous reach of the Federal IT Dashboard, this is a particularly difficult problem as the audience is so broad. Generally speaking, we think there are three types of users for this system:

  • Inquisitive masses – Scope: broad but shallow – These folks are the general public; those people who are most likely looking for high level information and are looking for answers to broadly curious questions.

  • Informed but distant 3rd parties – Scope: medium breadth, medium depth – This second group includes people who are looking for information on a specific program to compare to another program that they are more familiar with. In the case of the Federal IT Dashboard, this may include the CIO of a related project, or the chair of a Senate subcommittee, or a political watchdog group doing some research.

  • Involved 1st parties – Scope: narrow but deep – This third group represents those who are directly involved with a specific program and want to drill deep to learn as much as they can about a single specific program.

Principle 2: Know how the solution will fit into the broader workflow

Since most “normal” people are paid to get stuff done and not paid to use software, it’s important for the application designer to make sure the tools that they provide are, at a minimum, supporting the workflow, and preferably, transparent to the workflow. Questions that the designer wants to make sure the user doesn’t find themselves asking are “Where do I start?”, “What’s the next step through the app?”, “What’s the end point and how do I know I’m finished?”.

Looking at the Federal IT Dashboard homepage, it’s not clear to me that there’s actually a place to start. The very first image is the Performance summary on the left with the column chart on the right. But just as I’ve decided that I can click, the image changes. I find myself being confused by this almost every time I visit this site – especially since I can’t click on the other views in the image rotation. All of a sudden, I’ve gone from trying to complete my workflow to trying to figure out how to get back to the dashboard – not very transparent.

Using existing methods such as behavior diagrams (such as Interaction Diagrams, Event Diagrams, and Use Case Diagrams) can really help an application designer overcome these sorts of hurdles and define intuitive action flows.

Principle 3: Make navigating the application layout intuitive

When considering application navigation layout, use a single simple rule: start high and enable drill down.

Start with high level KPIs that indicate the overall performance with as few metrics as are possible so the first thing that the user sees on a dashboard is nearly instantly comprehensible. This sometimes requires the application designer to be ruthless about “who” makes the metric cut for the first view. The number should immediately indicate whether further investigation is required. In our mockup, the important numbers are just four: spending and change, and performance and change.

KPIS

The goal is that it’s simple enough that a first time user can quickly determine what’s next, but an experienced user can quickly determine if anything significant has changed since their last visit.

Once the high level “first view” is identified, enable the user to easily drill down for additional information and exploration. For example, as the user is investigating a particular number, clicking directly on that number should reveal the next layer of information. This is where the Federal IT Dashboard excels, by the way. Users can drill down by clicking on program names, or chart segments, and can navigate back up the crumb trail by clicking “clear” at the top of the data table or on the current view parent.

Filters

Finally, we need to address the main navigation. Navigation elements that are positioned such that they imply some sort of relationship, such as menu items, should either be siblings, or parent-child entities. In the case of the main navigation tabs on the Federal IT Dashboard, the items Home, Portfolio, Tools, and Data Feeds are distinct areas but all have different relationships to each other – or worse aren’t related. This makes navigation difficult because the user has to context shift to navigate. It’s a little like “Apples”, “Transportation”, “Monday”, and “Swimming” – they don’t have any thing to do with each other.

It’s OK to use tabs, but make sure they contain distinct and separate domains or views. For the Federal IT Dashboard, I think navigation would be more intuitive if the Home, Portfolio, and Tools tabs were merged. Start all the users with the overview, then allow them to navigate via the visualization to the Portfolio view. Then, toggle that view with the views that under the Tools tab based on the view the user needs to see.

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