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The Best of Business Intelligence: Innovation at the Fringe
Enough complaining about the broken bits of Business Intelligence; it’s time to highlight the things that are good and right in the industry. Like most industries, the renewal and innovation occurs at the fringe, beyond the comfort zone of established vendors.
I’ve created five categories and a catch-all to capture the solutions and companies (not so much technologies) that are leading the next generation of Business Intelligence. The categories are:
- Analyst tools
- Dashboards
- Targeted solutions
- Open-source and free
- Advanced visualizations
- Other stuff
Naturally I’ve focused on areas of Juice expertise and focus — not coincidentally, the places where we feel BI has neglected end-users. According to a study by the Business Application Research Center, BI end-user adoption sits at a lowly 8%.
I’m happy to take your suggestions (and update the post) for things I’ve missed in these categories or for entirely new categories.
Analyst tools
Tools that make it easy for analysts to pull data from multiple sources, analyze, visualize and share it.
Winner: Tableau, the reigning king of visual analytics tools, has added more web-based functionality to allow for online sharing and collaboration.
Runner-up: Good Data has arrived on the market with a web-first platform designed to democratize analytics. I had a chance to get a demo from the management team and was impressed with the ease of use and high-quality data presentation.
Dashboards
“A frequently updated analytical display that is clear and concise” (via a recent post)…and not likely to draw the rage of Stephen Few.
Winner: BonaVista Systems wants to make Excel a “first choice dashboard tool.” From the humble position of sparkline plug-in vendor, BonaVista has taken a leadership role in encouraging more effective dashboard design.
Runner-up (tie): Two BI companies, Qlikview and Microstrategy, seem to be following BonaVista’s lead. Unfortunately, they may only be dipping in a toe as I found just a couple examples that break from the traditional over-glossy, gauge-riddled dashboard interface.
Targeted solutions
Companies that serve a narrow slice of the BI world extremely well. The desire to be all things to all people has been an Achilles Heel of the BI industry. The general purpose BI platforms often prove too broad and too generic to serve the unique problems of specific industries or functional areas.
Winner: Wall Street on Demand is a brilliant, below-the-radar provider of information solutions to the financial sector. Their sparse, articulate marketing text and few screenshots hint at a company that knows exactly what they do and deliver high-quality BI solutions. I wish I knew more.
Runner-up (multiple): The following are just a few companies that have focused on an industry or functional segment to deliver targeted BI solutions:
- Quantivo for customer behavior analytics
- Visual I|O for pharmaceuticals
- LucidEra for sale pipeline reporting and analytics
Open-source and free
(I know there is a difference.)
Winner: Pentaho offers an open-source end-to-end BI suite that is a competitive alternative to the big-guys. Of course, the implementation it isn’t necessarily cheap or easy.
Runner-up: If anything should scare the BI industry, it is the possibility of a Google Analytics model extended into more general data analysis and visualization tools. Google Fusion Tables may just be the tip of the iceberg.
Advanced visualizations
Bringing leading-edge visualization techniques out of academia and into the business world.
Winner: Many Eyes continues to impress with high-quality visualizations. They are easy to create and clean in design and usability. Impress your boss with a slick visualization in your next presentation.
Runner-up (tie): Openviz / Advanced Visual Systems and Panopticon appear to be the two BI vendors battling it out for leadership in advanced visualization solutions. Unlike Many Eyes, these guys lack Tufte-esque sophistication in infoviz design. That said, there is a big difference between creating a one-off New York Times-quality visualization and delivering a toolset that is re-usable in many different situations.
Other stuff to be admired
Free charts with good default design. InetSoft’s Style Chart and Google Charts offer free, embeddable charts.
Jargon-free BI marketing. With few exceptions, BI web sites are densely populated with those awful stock-photography people sitting around conference tables (or worse, the ethnically-diverse V-formation marching at you) and meaningless business jargon and techno-babble. I really appreciate Blink Logic’s web site with its straight talk and clean, readable design.
Beyond the desktop. RoamBI has a great-looking iPhone application that is designed to “transform your data into insightful, interactive visualizations delivered to the iPhone.” It makes the Oracle and Qlikview iPhone apps look old-school.
Five Features of Effective Filters
I’ve developed a bit of a penchant (obsession?) for decomposing the pieces of analytical applications and framing the good and the bad characteristics. So far I’ve taken on treemaps, real-time dashboards, alerts, composite measures, success metrics.
Next up the poor, neglected, and taken-for-granted filter. For such a common and essential component, it seems rare that designers take a moment to consider how to make the best possible filtering mechanism. Here are the five elements I consider critical to a good filter selector along with examples from exemplary interface designs.
- Selections
- Impact
- Context
- Persistence
- Short-cuts
Selections
Good filters make it obvious to users what has been selected. That might seem like an obvious necessity but consider what happens when you filter in an Excel list. The filter section, even if it is a single item, is immediately hidden from view.
Jonathan Harris’ frequently referenced We Feel Fine visualization offers one of my favorite filtering examples. Notice how the selected items are highlighted and the non-selected items are de-emphasized. The bar at the top clearly shows what has been selected, even after the filter selector is “put away.”
Impact
The best filtering mechanisms also give instant feedback about the impact of your filters. This can be as simple as a subtle indicator that the filters are being applied. Even better, as demonstrated in the The New York Times’ Rent or Buy site, the graph animates in real-time as filters are applied. This creates a very tangible connection that helps the user understand the impact of the filtering choices.
Context
Filters should provide information around the items being selected. What does it look like? How many are there? Take the simple font selector in Office applications: Isn’t it a no brainer that the names of the options are shown in the actual typeface? Here are a couple other fine examples of context:
Click shirt is Bret Victor’s brilliant t-shirt design interface. In it, he offers an elegant filter implementation where all the selections show images of what you are about to select.
Elastic lists is one of the most innovative approaches to filtering. The height of individual blocks in the selectable stack shows the frequency of the items, an embedded sparkline shows the trend, and brightness indicates “weight of the metadata value compared to the overall distribution” (a bit too ambitious/confusing, in my view).
Persistence
Given the importance of filters to most information applications, it is surprising how often the interface makes them hard to find. As I mentioned in an earlier post, the failure of many analytical and reporting applications is that “they assume users know precisely what they need before they’ve begun the analysis.” Filtering shouldn’t be a one shot deal; the functionality should always be accessible.
Kayak, a travel site, integrated the selection filters into the results so users can easily change their trip criteria without having to start a new search.
Short-cuts
Finally, filters should make it easy to apply common selections (All, None) or complex sets (My Saved Filters, Northwest Region).
Moodstream by Getty Images recognizes that users aren’t always going to want to configure a bunch of filters individually. The presets wheel solves this problem by offering a series of pre-defined “filter sets.”
Finally, I’d be remiss if I didn’t mention the sophisticated and powerful filtering functionality delivered in Tableau. In addition to providing filtering by selecting graphs (i.e. in context filtering), the application allows for multiple selector types, wild-carding, conditional filters, top/bottom filters, and on and on. If you want a comprehensive catalog of potential ways to offer filtering, watch the Filter Data video here.
Wordtree for Visual Text Exploration
Analytics can be all about having the right tool for the job. When your data is text, traditional analysis tools (e.g. Excel, OLAP tools) are like peeling a mango with a chainsaw.
There are a number of visual exploration tools specifically designed for text data, including:
- Word clouds like Wordle (fun but superficial);
- Network diagrams like Visual Thesaurus (good for individual words, not text);
- Trend graphs like Baby Name Voyager or Google Trends;
- Granular presentations for interacting and exploring individual phrases, e.g. We Feel Fine and Twistori
- “Word trees” that let you navigate through lines of text to understand the most frequent words, relationships between words, and common phase and sentence structures.
It is quite difficult to find a Word Tree in the wild. The brilliant team at IBM’s Many Eyes were the first to make Word Tree’s generally available. The same ManyEyes team have also created an alternative approach for visual text exploration with a tool called Phrase Net.
Recently, we built a slightly different take on the Word Tree in Concentrate, our tool which allows users to explore huge search query lists to see how people use search keywords. For geeky entertainment, we created a special Concentrate demo account with the lyrics of songs from Rolling Stone’s 500 Greatest Songs of All Time. Click here to sign-in to the demo (Press submit and then choose WordTree at the top).
Here’s how our Word Tree works:
- The box at the center is your starting point. When you open a Word Tree, it will contain the most common word in the text data. You can edit this box to “re-center” the wordtree (name that tune):
- Stretched out on either side are words and phrases that are tied to that center word. The size of the words represents their relative frequency.
- Rolling over the words/phrases will highlight the connections to your center word and on the other side. You’ll also see a pop-up box with examples of the phrases containing selected words.
- You can open or close branches by clicking on a word. Words with hidden branches are highlighted in orange. We also have an ability colorize the words based on a metric in your text data.
While these more advanced visualizations are a start, I suspect there is a lot of room for other tools and techniques to visually explore text data. I’d be curious to hear about other tools you’ve seen along these lines.
11 Parallels Between Architecture and Interface Design
I had a fascinating discussion with my sister-in-law, a real-life professional Architect, about the parallels between her work and the type of interface design we do at Juice. In both cases, design requires looking at the problem from many perspectives, blending art and science, creativity and time-tested principles. Sure, she had to go to graduate school for three years and is part of a rigorous apprenticeship system. But when you consider the ways we approach and solve problems, there are a number of common threads:
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Start with the context. For Architects, a project begins with a site analysis to evaluate the available space, direction of the sun and wind, characteristics of surrounding buildings, street patterns and other environmental factors that need to co-exist with the building. The parallel in interface design is considering the context of users: What is their typical workflow? What other data and reporting are they working with? What decisions will be made from viewing the data? What is their skill level?
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Decipher client needs The ultimate job of the architect and interface designer is to translate vague but strongly-held desires of the client into a practical reality. There are straightforward functional requirements: “I need a house with three bedrooms upstairs.” And there are more subtle demands: “The application needs to be simple enough for anyone to use.”
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Evolved toward reality. It wasn’t hard to find parallels in the ways that we approach the process of designing. Like interface design, the architectural design process evolves from the most abstract (blocks of wood) to more realistic representations (drawings and models). The more realistic the format, the more time intensive and the more clearly the concept and details can be communicated. At Juice, we are particularly fond of prototyping analytical applications because it gives our clients an opportunity to engage with the interface and data directly.
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Build a narrative. Like any piece of art, a building needs a core story that characterizes its essential qualities. In our interface designs, we call these design principles. These are the basic truths that we want to permeate the application. Here’s an example of design principles for a reporting application design:
a) You’re one click away from what you need; b) Allow lightweight, temporary ways of paying attention to something; c) Alerts are so important that they are always visible
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Connected whole. I shared with my sister-in-law a description of how many dashboard vendors are essentially selling functional pieces without offering guidance on how they fit together. She remarked: “if you designed a building that way, you’d end up entering into the bathroom.” I’ve seen dashboards that feel about like that. Architecture has had many decades to recognize the primacy of the cohesive whole. Interface design, particularly when it comes to the presentation of data, hasn’t come nearly so far.
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Multiple relationships. Designing a building requires thinking about the problem from many different perspectives, and ensuring that the answers work together. Architects need to consider how functional spaces relate to each, how the spaces flow together, and how the spaces relate to the site. Interface design requires thinking about how the presentation of information links together, how users navigate between this information, and how the results fit into the broader user workflow.
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Multiple scales. Architectural and interface design requires viewing the problem at multiple scales. There is the high-level view of how a building fits into its site locations all the way down to the design of specific rooms and spaces. Each of these scales needs to be in harmony.
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Facilitate flow. A good design supports intuitive pathways within the structure. The design accounts for the most common use cases and makes solving these use cases obvious. In our work, we always want users to have a sense of where they are and where they can go.
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Iconic elements. My sister-in-law described iconic elements as the center-point of the building design and narrative. They encapsulates the personality and essence of the design. I hadn’t previously thought of interface design in this respect, but I will in the future. In our work, there is frequently a single element, whether it is a data visualization or navigational structure, that is the core of the application.
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Visual vocabulary. The “vocabulary” of the building represents the materials (e.g. wood, metal, glass) and other visual elements that compose the common aesthetic for the design. The analogy for us is the UI style guide where we define the color palette, typography, and other treatments that make up the look-and-feel of the interface. An effective UI style needs to align with the narrative and design principles described above.
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Upholding and breaking rules. There are many conventions and expectations that shape the design of a building or an interface. These rules exist for many valid reasons, and we agreed that it is important to acknowledge and respect them. However, my sister-in-law noted that her professors would often challenge students to “break the rules to make them stronger.” There are times to challenge convention, in particular with your iconic elements, to push the design beyond the ordinary and formulaic.
At the beginning of our discussion, I was surprised to learn that a few of my sister-in-law’s Architecture classmates had gone on to do interface design. Given the similarities in the thought process, it may not have been a big transition.
Thrown to the Ad-Wolves… or, Learn from My AdWords Mistakes
Here at top-secret Juice headquarters, some major new products are in the works, and we want to promote them with Google’s revenue powerhouse (also known as Google AdWords). Thus, after three weeks of self-imposed AdWords boot camp, I have emerged with a few scrapes and burns, along with some tips that I wish I had been armed with since the beginning.
The natural place to start learning about Google AdWords is the official Help Center, an expansive and neatly categorized resource. But what happens if your inhuman schedule or dwindling coffee supplies don’t allow you the luxury of navigating through the help center hierarchy or sifting through its search results? While you might be able to maintain a semblance of a campaign without answering those lingering questions, you run a high risk of letting potential viewers slip away, never seeing your ad, and wasting money on high CPCs (cost-per-click).
You are hereby invited to learn from my mistakes. I am forgoing the usual basic topics in favor of questions whose answers are more time-consuming and tedious to find. It took me a few weeks to get comfortable with AdWords and figure out these answers myself, but it will only take you a few minutes!
Read on to learn the answers to:
- How creative should I be with my ad text?
- How do I find out what keywords my competitors are using?
- Why has Google’s heartless algorithm condemned my keyword as inactive?
- How do I get bolded words in my ad?
- What is dynamic keyword insertion, and how do I use it?
- What is the difference between a campaign and an ad group?
- What is the difference between keywords and placements?
1. How creative should I be with my ad text?
When I was but an AdWords newbie, I held the misconception that creative ads were all that I needed to pull in clicks. Pop psychologists might credit my right brain, starved for attention in the left brain’s home turf (programming! algorithms! programming these algorithms!), for seizing upon the opportunity to design some artistic and imaginative ad copy:
The “Viva la Revolucion” ad was my baby. But it turned out to have a face only a mother could love, as evidenced by the zero people who clicked on it. To the stunned disappointment of my right brain, Google AdWords is just as algorithm-fueled as any of Google’s other products. In fact, Google AdWords runs much like the ubiquitous search engine does, treating your keywords, ads, and landing page similar to the way it treats the 1 trillion pages it crawls while looking for content.
2. How do I find out what keywords my competitors are using?
Google won’t tell you—it’s in their privacy policy. But services such as KeywordSpy will. KeywordSpy not only gives you lists of your competitors’ (and your potential) keywords, but provides data for each keyword about other metrics, including as ROI, price per click, and number of competitors.
3. Why has Google’s heartless algorithm condemned my keyword as inactive?
Sometimes, Google will refuse to show ads for certain keywords unless you pay an absurdly large CPC. The large CPC is meant to discourage you from following any of these bad habits:
- You dumped a lot of unrelated (or weakly related) keywords into one gigantic ad group.
- Your keyword, ads, and landing page aren’t “relevant” enough to each other.
- The cost per click you set for that keyword falls below the minimum.
Try making many smaller ad groups, each with its own tightly-connected set of keywords. Ideally, every keyword in a given ad group is a synonym for all the other keywords in the ad group. This also helps tremendously with writing ads that use dynamic keyword insertion (see question #5), since forcing ads to accommodate keywords covering a wide range of topics and/or parts of speech makes the ads vague and unspecific. To find keywords that deserve synonym status, use Google Sets. It’s like a thesaurus on steroids.
All members of the Holy Trinity of content (keywords, ads, and landing page) need to draw from the same words to be considered related. Try making sure that they line up.
This is the nicer way of saying that you have to spend more money.
4. How do I get bolded words in my ad?
You can’t designate specific words to be bolded (or formatted in any way, for that matter). You can, however, make sure to include keywords (words the user types in that you have selected for your ads) in your ad title and/or body. Just as it bolds keywords in search results, Google bolds keywords in ads. Your keywords do not have to be exact matches with the words in your ad. In the example below, a search for the keyword phrase “report automation” produces an ad that not only bolds “report” and “automation,” but also their variants “reports” and “automating.”
5. What is dynamic keyword insertion, and how do I use it?
This technique (sometimes known as “wildcards”) is how eBay and Target can pull off “Buy _____ now” for every conceivable adjective-noun combination. It allows you to make the same ad apply to multiple keywords. The format is:
The word immediately following the colon (no spaces) indicates the word you want to be shown when the keyword is too long to fit in the ad. Since I chose that word to be “executive dashboards,” the ad prompted by a too-long keyword would look like this:
Here is the same ad with other keywords swapped in, thanks to dynamic keyword insertion:
You can tweak the capitalization of the keyword with Google’s guidance, in the form of this handy table and more.
6. What is the difference between a campaign and an ad group?
A campaign is made up of one or more ad groups. Each campaign has one budget (i.e., $10/day) that is shared between all of its ad groups. Each ad group can be customized with different ad variations, keywords, placements, days and times the ad is shown, etc. Therefore, most modifying and experimenting happens on the ad group level.
7. What is the difference between keywords and placements?
Keywords produce what people usually think of when they think of Google AdWords. When a user performs a Google search for a keyword you have selected, your ad appears on the side (or top, if your budget is very generous) of the results page. Placements occur in the “content network,” which is made of individual sites that get paid to show Google ads. If you sign up for a lot of placements, you’ll get a lot of clicks—but only because of the sheer volume of people seeing your ad. In some ways, placements are less targeted than keywords because people who clicked on your ad in the content network aren’t actively searching, as they are when they find your ad through natural searches. There are two types of placements:
- Placements You Select
- Placements Google Selects
Google’s Placement Tool allows you to browse a gigantic list of sites organized by topic. Any of these sites could have your ad on it. The Placement Tool will also suggest sites and break down your potential audience by demographic.
Google will select sites in the content network based on information from your current campaign. These sites may make up the bulk of your impressions and clicks on the content network and in general (in other words, clicks from the Google’s selected placements may outnumber both clicks from your selected placements and clicks from organic searches).
This list is by no means a comprehensive examination of AdWords, but at least now you can consider yourself three weeks wiser and three weeks closer to writing one that is.
Analyticstime!
If you struggle to legitimize analytics within your organization, you can’t touch this video for a powerful explanation of the impact of analytics:
MC Hammer at the AlwaysOn/STVP Summit at Stanford, “Music Artists Go Entrepreneurial.” Around minute 24:00.
Review: 5 Options for Embedding Charts in a Web Page
A few weeks ago, I received an e-mail from the folks at Widgenie asking for a blog review of their newly launched service. Widgenie targets non-technical people looking for an easy way to create and publish charts or data visualizations on the web. As I began looking it over, I wondered whether this problem had been solved elsewhere. It has. I’ve summarized my experiences with five services that can help you go from data table to web chart with ease.
I evaluated the services across three criteria:
- Data upload: simple process, options for file types, control after loading data, ease of updating data.
- Chart options: different chart types, control of labels, axes, ordering data, and formatting.
- Chart design: effective data presentation, absence of chart junk.
A few things I didn’t worry about, but might be worth considering:
- Managing charts that you have created
- Animation or interactivity of charts (usually this is more distracting than useful)
- Easy registration process
- Performance across all the chart types
I gave each service a score of 1 (poor) to 3 (great) for each criteria. Top performers are highlighted in green.
Unlike some of the other solutions, Google Spreadsheet with charts/gadgets isn’t primarily about creating data visualizations. Nevertheless, in a few simple steps, you can upload data, create a good looking chart, and publish for the web.
One key advantage to Google Spreadsheets is that you can easily change and manipulate the data online. The chart output is clean and practical. The chart options are basic, but when you select gadgets rather than charts, you have a lot more visualization options. I was disappointed that it didn’t offer many options for formatting, which is frustrating in an application that is beginning to feel like Excel.
Widgenie is exclusively targeted at the problem of embedding web charts. Overall, I found Widgenie easy to use. The process for loading data and creating “widgets” was straightforward and obvious, if a bit linear (e.g. once you create a widget, you can’t go back to change the chart type). Widgenie offers an above-average number of publishing options, including embedding your charts in iGoogle, Blogger, and Facebook.
Unfortunately, Widgenie offers a lot more sizzle than steak. Its bold marketing statements include:
“the all-powerful data visualizer”
“Take your data and transform it into visual information that can be shared with anyone, anywhere. Your wish is our command!”
“We combine all the power of an enterprise-level business intelligence platform and provide it in a convenient Web 2.0 widget.”
A few of the issues I ran into:
- Relentless use of “animated” 3D charts—where animated means it moves as it is drawn on the screen, not that it shows changes over time in movie format (now that could be powerful).
- The tag cloud visualization, the lone advanced widget option, colors the text rather than sizing it. That isn’t the way tag clouds typically work.
- Finally, as you can see from the image below, I wasn’t able to present my data in order of months (though I loaded it that way). When the data is labeled as text, it automatically gets sorted alphabetically. Changing it to date/time made things even worse.
Editors note: We can’t even embed the widgenie widget in the page because a coding problem with the widget caused all the links on this page to turn red. This problem only occurs with certain browsers.
Swivel isn’t directly aimed at the embedding charts market, but still does a competent job of delivering this capability when you select the “post to blog” option. Swivel offers a beautiful data upload process, but failed in its attempted to auto-define the chart type. Like Widgenie, Swivel struggled with ordering my data the way I wanted it, and somehow lost the order of my original data load.
The charts are generally clean and easy to read, but they’ve made a strange commitment to vertical grid background which doesn’t work for a column chart.
Many Eyes is brought to us by the big-time data visualization thinkers at IBM. They know the right way to present data and it shows.
Unlike the other services, the only way to get data into Many Eyes is by pasting into a text box. When it comes to visualizing the data, however, Many Eyes offers a myriad of options. Using it to create a simple column chart feels like taking a Ferrari to the grocery store. It is worth checking out the word tree, treemap, network diagram, and proper tag cloud.
Like Swivel, Many Eyes was designed as an online community for the visualization of public data sets, yet it pulls of web chart publishing with ease. The one negative is the “click to interact” feature on the chart.
Zoho Sheet is an online spreadsheet like Google Spreadsheets.
I was ready to fall for this one. Like Google Spreadsheet, I simply dropped in my data and selected the create chart button. You’d swear you were in Excel as it walks through the steps to selecting and customizing a chart. But then this came out…
Fortunately, a Zoho’r explained in the comments how to change from this default view.
Godin Dumps on Bar Charts; Data Visualization Record Falls to 1 and 1
Seth Godin, well-known marketing guru, took a strong and misguided stand against bar charts1 in a recent blog post entitled “The three laws of great graphs”
Godin suggests that bar charts (and presumably other chart types like scatterplots, bubble charts, bullet charts, treemaps, etc.) give too much latitude for data confusion and ambiguity when used in presentations. In Godin’s view, a chart should make a single, clear point and leave no room for alternative conclusions.
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Why Analytical Applications Fail
Many analytical applications fail for a simple reason: they assume users know precisely what they need before they’ve begun the analysis. There are cases where this assumption holds and the user has a specific end-point in mind. But more often, users depend on the tool to track down an answer with only a vague idea of where to start. The exploratory analysis that follows can feel like swimming upstream when the application isn’t designed to facilitate the journey.
The source of this mismatch is partly rooted in the technical perspective of database developers. The simplest path to providing data access is to let users fill out a form to define a SQL query. It is a linear mindset that isn’t well suited to ambiguous problems.
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Real-World Tufte Graphics in 11 Lines of Code
One of the troubles with Tufte is the frustrating infeasability of his approach to design for real people in business. One of his recommendations is to use Adobe Illustrator.
Adobe Illustrator is a big serious program that can do almost anything on the visual field (other than Photoshop an image). Most of my sparkline work was done in Illustrator. Fortunately all graphic designers and graphic design students have the program and know how to use it, so find a colleague who knows about graphic design.
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