It has been almost ten years since the release of Windows 95. Hidden in Windows 95 was a library containing functionality never before seen on the desktop - Open GL. Open GL, a standards-based enabling technology, made creating interactive 3-D graphics faster, easier and more dependable than before.

Now, 10 years later, where have these 3-D graphics gone to provide business advantage to those working with data? Instead of the virtual reality interfaces postulated in 1992, interactive desktop 3-D has become much more effective at solving specific business needs in monitoring, analysis and reporting and is now broadly referred to as information visualization and visual analytics.

Business systems are generating ever-increasing amounts of data, and more and more of this data is moving in real time. Data mining is a standard feature in some databases. Automatic analytic modeling engines are found in many applications. However, there remain many applications where human judgment is required, including: management reporting, risk management, model exploration and validation, real-time operations and information security. With all this rich information, the challenge remains to derive the most business value from the ever-increasing amount of available information.

Visual information can significantly improve productivity. Users can explore large amounts of data, rapidly assimilate information from many sources, reason with it, understand it and create new knowledge based on it. With the right visual picture, people can make better decisions, faster, backed with more information.

The last ten years has witnessed an explosion of graphics in reporting and analysis software - dashboards, scorecarding and rich charting techniques - which have significantly enhanced information presentation. Interactive features, such as linking and drill-through, are becoming commonplace. Visual techniques using maps, gauges, stoplights, radar charts are now widely available for reporting applications. Techniques such as zooming and integrated correlations (where all charts are synchronized so that selecting one bar in a chart updates all active charts to highlight the selected subset) are becoming more widespread.

This first generation of visualization has familiarized the corporate world with using and interacting with business graphics. Now, some corporations are looking to harness visualization for strategic advantages in their core competencies, adding advanced visualization to key monitoring, analysis and client-facing processes.


One of the most obvious benefits of visualization is helping people see trends and anomalies in data, which can be particularly valuable in real-time environments. Visual techniques such as heat maps and tree maps, which help reveal patterns in homogenous data, were virtually unknown 10 years ago, but are used today in many places ranging from public Web sites to advanced trading applications.

Real-time environments require rapid comprehension of a dynamically changing situation - whether in the stock market, an emergency response center or an operations control center. Visualization can also help reveal patterns in complex, heterogeneous, rapidly updating data.

With a technique called visual fusion, visualization can bring together loosely related pieces of historical, real-time and planning data into a common visual framework making otherwise hard-to-detect patterns visible. An infrastructure operations visualization can depict schedules, alerts, status, performance metrics, plans and errors all within a common visual framework. Adoption of "sensors" (RFID tags, remote cameras, GPS and other monitoring devices) further increases the data volume. An operations manager has simply articulated the information overload problem: alerts and icons out of context are useless.

Even when the data is highly heterogeneous, it can still be brought together in a single visual interface based on common underlying attributes such as location, time, relationships and classifications. Interactive techniques such as selection, filtering, associations, search and aggregation can help operations staff understand and assimilate groups of events and isolate the root causes of those events. The solution can be used on a video wall, on a desktop or even on a laptop in the field. The resulting visualization provides for faster situational awareness, better management of multiple ongoing events, reduces decision latency, and fosters participation among more people in the organization. The organization has better coordination of limited resources and can stay on top of critical situations when they occur, resulting in significant cost savings.


Visualization is extremely powerful for analysis. For example, a simple scatterplot can easily reveal patterns as a related string of dots and anomalies as clusters or outliers.

Scatterplots currently appear in many analytic visualization tools. Thanks to multitier architectures, scatterplot capacities can now display tens of millions of unique simultaneous data points, helping analysts identify opportunities, isolate risk, or find the fraudsters and the hackers. As one security administrator said, "Visualization saves me time when I review this data and helps me spot the most dangerous activities."

Powerful simulation models used in everything from risk forecasting to supply chain optimization empower businesses to create more accurate forecasts and perform what-if analysis. However, given the complexity and sheer volumes of data associated with many models, developing, understanding and communicating about the model can be difficult. With interactive visual representations of these models, not only are the results of the model more explicit, but both the modeler and the audience can interactively adjust, learn and explore the model. "Using visualization, we immediately saw that there was more basis risk than we had captured and it was shifting," said the CRO at a European bank. With visualization, the bank was able to produce higher quality data and models, with faster analysis and fewer errors helping them to reduce capital allocations by more than ten million dollars.

Visualization of non-numerical data - such as business processes, entity relationships, text, geographic data, imagery and video - represents another major opportunity. The primary challenge is to find meaningful representations that meet the users' needs. Complex tasks such as searching for a specific document, understanding relationships and sequences in a group of people or investigating a competitor's activities over time can be approached with the right visual representations. These visual representations are, in turn, dependent on the underlying algorithms (e.g., cluster analysis, automated taxonomies, extracted meta data, relevancy scoring, concept maps). The correct visual interface fits the underlying problem, as well as user skills and data models. With the correct approach, the end user benefits with a tool that can navigate through a rich, complex data set, with faster access and utilization of the data available and a higher degree of confidence in the analysis.

Broad Dissemination

Online applications that have standard charting elements are now broadly accessible - whether for banking, investment, bill payment or CRM. However, dry data presentment does not build loyalty, nor does it entice customers to derive value and insight from their data. Visualization is now starting to appear in these broad, customer-facing deployments because visualization can bring unique strategic advantages. No longer is visualization the domain of high-end graphics workstations. Thanks to the Internet and Web-based programming environments, it is now possible for wide deployment across corporate intranets or to the general Web-browsing population.

One financial data company has adopted visualization to provide competitive advantage by delivering high value and building brand identity. Using visual fusion, they have created an integrated display of disparate market data elements into a single real-time picture. This new representation is highly unique to their company and has been enhanced with a look and feel that matches their corporate image. They gain advantage by providing a solution uniquely tailored to their specific customer's task - which results in a better user experience than possible with a prepackaged solution. They also differentiate themselves from their competition, increase their visibility and provide a tangible vision of value-added services. Overall, the unique visualization helps the company build direct relationships with new customers increasing their revenue.

Figure 1: Table Versus Visualization Scatterplot. The table shows only 50 rows x 9 columns out of 80,000 rows of data. The visualization scatterplot shows 80,000 points with 5 attributes (x position, y position, height, size, color) - more than one hundred times what is visible in the table. Patterns invisible in the table are immediately obvious in the scatterplot.


There are many factors to evaluate when considering visualization for a new application. Visuali-zation can encompass everything from charting to highly unique representations, from low interaction to highly interactive applications. Some useful criteria to consider before choosing a visualization solution are:

Application: What is the broad nature of the task?

  • Is this for real-time monitoring or casual analysis, detailed quantitative analysis or a tool for reporting to a broad audience?

Tasks and Workflow: What are the specific tasks that the users need to accomplish with the visualization?

  • Is this analysis for detecting anomalies (e.g., credit card fraud detection) or looking for broad patterns in heterogeneous data (e.g., credit card marketing)?
  • Does it need to fit into a broader workflow, for example, as part of a fraud case management system or in a trading execution environment, or directly interacting with models and systems?

Users: Whether a simple dashboard or unique and highly interactive analytical visualization, having the wrong level of detail that doesn't solve the users' problems can make the end result ineffectual.

  • Are the users a small group of quantitative analysts or high-stressed operations staff? Are they familiar with the subject matter? Are they familiar with a wide variety of interfaces or most comfortable with Excel?

Data Volume: Many visual techniques do not scale to large volumes of data, loosely formatted, or poorly structured data. For example, some OLAP visualizations do not work on wide hierarchies.

  • How many data sources are there? What is the scale of the data - 50M rows? 100,000 summarized rows? 100,000 rows?

Data Complexity: Many visual techniques are limited to a single snapshot of data, such as the result of a single query or single cube.

  • What are the data relationships? Do the data sources match the analytic tasks (e.g., OLAP cubes do not have transactions nor relationships and thus would not be applicable for a clickstream analysis application).
  • Does the data need to be aggregated, sampled, sorted or summarized?

Data Types: One visualization failed because the data type was primarily categorical data, while the off-the-shelf visual tool was primarily organized for numeric data.

  • Different data types (e.g., text, categorical, numeric, geographical, image, relationships, models, etc.) require different solutions.

Data Source: The source data must be accessible to the visualization application. Whether stored in a data warehouse, an Excel spreadsheet or flat file, how the data is currently being managed will have an impact on how the visualization accesses the data.

  • Will additional data or queries need to be optimized in order to access the data in an efficient way?

Technology and Architecture: What is your environment?

  • Visualization solutions can be developed so that they run in an Internet browser, on the client or as a full n-tier solution. Visualizations exist not only as native Windows applications, but new technologies can also support some forms of visualization, including .NET, pure Java, Flash and SVG.

Figure 2: Strategic Plan (top) - interactive adjustment of project timelines updates key financial and performance metric projections. Portfolio Risk Model (bottom) - interactive adjustment of commodity forward curves updates the projected profit and loss.

Communication: Visualization fosters communication. As a bank CRO said, "Visualization focuses attention on data issues in a way that is impossible to achieve with PowerPoint."

  • * Is the visual to be used for decision making by a single user, or viewed by a group for collaborative decision making? Will it be disseminated to the general public? Does it help communicate to senior decision-makers and investors?

Visual Quality: The overall quality of the visualization is extremely important for forming positive perceptions.

  • Is the visual seen by anyone external to the company or used directly by customers? Does it have the potential to positively assist the company's marketing efforts?

We've come a long way since Windows 95 and OpenGL. Corporate users have become increasingly familiar with visual interfaces and interacting with business graphics. The growth of PC processing power and an expanding array of development and deployment options create potential for new classes of applications. The opportunities for competitively harnessing information visualization to drive strategic business advantage are much bigger today than ten years ago. Choose your visualization solutions carefully. Fit is extremely important, and with visualization, a poor fit will show!

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