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Data Visualization Technology

By Wayne Eckerson and Mark Hammond

There are two main categories of data visualization technology: visual reporting and visual analysis.

  • Visual reporting. Visual reporting uses charts and graphics to depict business performance, usually defined by metrics and time-series information. The primary type of visual report is a dashboard or scorecard, which gives users a visual snapshot of performance. The best dashboards and scorecards enable users to drill down one or more levels to view more detailed information about a metric. In essence, a dashboard is a visual exception report, highlighting performance anomalies using visualization techniques.
  • Visual analysis. Visual analysis, on the other hand, enables users to visually explore data to discover new insights. While visual reporting structures the navigation of data around predefined metrics, visual analysis provides a much higher degree of data interactivity. With visual analysis, users can visually filter, compare, and correlate data at the speed of thought. Visual analysis tools also often incorporate forecasting, modeling, and statistical, what-if, and predictive analytics.
Visual Reporting

Dashboards. By a sizable margin, dashboards are the preferred medium for data visualization. Nearly 85% of respondents ranked the importance of visualization as “high” in dashboards. On the other end, only 33% considered visualization to be highly important in an OLAP tool. (See Figure 1.)

There are a near-infinite number of ways to design the visual elements of a performance dashboard. Most dashboards arrange a series of related charts in a grid template, usually two-overtwo or three-over-three, and use multiple tabs or radio buttons to segment charts by category. They also usually display filters above or beside the charts they apply to, as well as links to related dashboards or reports. The best dashboards display summary data graphically so it can be consumed at a glance and then provide access to any detailed information a user might need within three clicks.

Sample Dashboard. For example, the dashboard from Rohm & Haas (now owned by Dow Chemical) is embedded in the company’s corporate portal, which has links (arrayed on top) to other enterprise content as well as other dashboards housed by the portal. (See Figure 2.) The dashboard itself consists of a table of 10 key performance indicators (established by top executives) that apply to every business unit and region in the company, along with pertinent targets (last year, variance, percentage change, and so on). Next to each metric are visual stoplights, which indicate the status of performance for the given metric against a selected target. Stoplights are perhaps the most common way to visually highlight exception conditions in a dashboard because they attract a user’s attention quickly.

Below the grid are two somewhat interactive charts that show a time-series trendline for the metric highlighted by the user’s cursor above. The left-hand panel contains the navigation path to the current view, and below that, a set of filters that users can use to change the alert in the grid and drill down to view performance along the same metrics at lower levels of the organization. (These filters are “universal” in that they apply to all objects on the screen instead of a single object.) The bottom of the panel contains hard-coded links to related dashboards and reports.

As you can see, the Rohm & Haas enterprise dashboard gives executives and managers a snapshot of performance for their domains with alerts to highlight exceptions and moderate levels of interactivity to drill into details and view related information. With a glance, executives and managers can see the status and trend of performance in their areas and how it compares to major benchmarks. Many companies are adopting this type of visualization to better monitor and manage performance.

Visual Analysis

Visual analysis tools enable power users and business analysts (such as financial, marketing, and sales analysts) to explore data sets visually and identify trends and anomalies. These tools usually work with data stored in memory and expose rich navigational features that let users explore data at the speed of thought. Many also incorporate some form of statistical or predictive analytics.

Visual analysis tools compress and store data in memory, providing sub-second response times for any action taken against the data (such as filtering, drilling, calculating, sorting, and ranking). Visually, analysts point and click to interact with charts, apply filters, and change views. For instance, analysts can use their mouse to “lasso” data points in a certain section of a scatter plot to create a new group and automatically filter other charts on the page. (See Figure 3.)

Compared to OLAP tools, visual analysis tools don’t require an IT person to design a dimensional data model. The tools use a “load-and-go” approach in which analysts load raw data from multiple sources and simply link tables along common keys to get a unified view of the data set. As a result, most visual analysis tools can be deployed in a few hours or a few days or weeks, depending on the number of data sources and their complexity and cleanliness.

Analysts or developers often use visual discovery tools to create and publish interactive, departmental dashboards for casual users. They often create the dashboards on desktop machines and then publish them to a departmental server for general consumption. When doing so, the developers generally strip out some analytical functionality and options that might overwhelm casual users.

Two Environments. It should be clear that visual reporting and visual analysis tools serve two different audiences and purposes. While visual reporting tools are designed to visualize performance against predefined metrics for executives and managers, visual analysis tools empower business analysts to explore trends and anomalies in data sets they create and publish views for others to consume.

Visualization Technology

Both types of visualization solutions leverage emerging technology to enhance the visual experience of BI users. Here are key technologies driving the adoption of visualization in corporate environments.

  • 64-bit systems and multi-core servers. Charting engines chew up a lot of CPU cycles, especially if the charts are interactive. Rendering charts, especially in serverbased environments, takes a lot of horsepower. Today’s 64-bit platforms and multi-core processors speed visual processing to give users more dynamic and interactive visual environments in which to view data.
  • RAM and compression. Many visualization tools work with in-memory data to ensure speed-of-thought interactivity. With prices for RAM dropping, it’s easier for power users to analyze large data sets (up to 50 million records) held in memory. New compression techniques increase the amount of data that can be held in memory—but be cautious of decompression performance penalties.
  • Java applets/Active X controls. These mini-applications run inside a Web browser and execute within a virtual machine or sandbox. Actions execute as fast as compiled code, making them an easy way to recreate full-featured applications on the Web. However, they raise security concerns, so many IT administrators prevent users from downloading such controls through corporate firewalls, which limits their pervasiveness.
  • DHTML and AJAX. A lighter-weight approach is to embed a scripting language inside HTML pages, such as JavaScript, that executes functions in the browser. Dynamic HTML (DHTML) uses scripting to animate a downloaded HTML page. For example, DHTML is often used to animate drop-down boxes, radio buttons, mouseovers, and tickers, as well as capture user inputs via forms. AJAX (asynchronous JavaScript and XML) takes this one step further and retrieves new content from the server in the background without interfering with the display and behavior of the page. Basically, AJAX enables users to add new data to the dashboard without having to reload the entire page. It can also be used to pre-fetch data, such as the next page of results.
  • Flash. Another popular approach is to use multimedia development platforms, such as Adobe Flash, Java applets, Microsoft Silverlight, and Mozilla Scalable Vector Graphics (SVG), which add animation and movies to Web pages. Compared to Java scripting, these plug-ins provide stunning graphics and animation for displaying quantitative information, which makes the user interfaces very appealing to business users. They load both visualizations and data simultaneously in a single file rather than dishing up dozens or hundreds of pages. Although this makes the initial load slower than a comparable DHTML or AJAX application, performance thereafter is exceptionally fast, since the data required to display all components on a page resides locally.

Vendor Advancements. BI vendors have been scrambling to meet increasing demand for visualization. For instance, Oracle’s release of Oracle Business Intelligence Enterprise Edition (OBIEE) 11g in mid-2010 addressed visualization weaknesses in earlier releases, Oracle officials said. Vendors such as MicroStrategy, ADVIZOR Solutions, and Tableau Software have recently emphasized new in-memory capacity for greater scalability. SAS (with its JMP visualization software) and DSPanel are among vendors incorporating the open-source R statistical programming language to mix visualization and data mining.

Corda and Dundas, which both provide charting components and dashboard tools, have expanded their tool sets to give developers greater flexibility. Microsoft is aiming to elevate Excel’s profile for BI visualization with the 2010 release of PowerPivot, an add-on that helps Excel accommodate large-scale data and extends its visualization capabilities, Microsoft officials said. Similarly, PowerPivot can leverage new visualization capabilities available through SharePoint 2010 integration with Visio, they said.

Many of these innovations are aimed at untethering business users from a reliance on IT so they can analyze data in a visual environment. “It’s an evolutionary thing,” said Doug Cogswell, president and CEO of ADVIZOR Solutions. “We’re used to using BI to view reports or KPIs, and now people want to move beyond reporting to visual analysis.”

Wayne Eckerson has been a thought leader in the data warehousing, business intelligence, and performance management fields since 1995. He is the author of the best-selling book Performance Dashboards: Measuring, Monitoring, and Managing Your Business, second edition (John Wiley & Sons, 2010). Wayne is the former director of education and research at TDWI, and currently director of research at TechTarget and president of BI Leader Consulting. He can be reached at

Mark Hammond is a veteran contributor to TDWI and TDWI Research, including a number of research reports, TDWI’s Business Intelligence Journal, and the TDWI Marketplace. He researched and co-wrote E-Business Intelligence: Turning Information into Knowledge into Profit (McGraw-Hill, 2000) with the former CEO of Business Objects. An award-winning journalist, Hammond’s work focuses on the use of data to improve business and organizational performance. You can reach him at or

This article was excerpted from the full, 20-page report, Visual Reporting and Analysis: Seeing Is Knowing. You can download this and other TDWI Research free at

The report was sponsored by ADVIZOR Solutions, Corda, DSPanel, Dundas, IBM, Microsoft, MicroStrategy, Oracle, SAS, and Tableau Software.

This article originally appeared in the issue of .

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