How can organizations use data visualization, visual analytics, and visual data discovery to improve decision-making, collaboration, and operational execution? We present three key insights from the latest TDWI research.
Data visualization is one of the innovations of our time. From the moment most of us wake up in the morning and fire up our tablets, smartphones, and laptops, visual representations of data fill our lives. Developments in, for example, stock markets, sports, and science, are increasingly told through data visualization. We encounter beautifully rendered “infographics” to explain trends and patterns in data. News organizations such as The New York Times> compete on analytics by serving up infographics to shed light on aspects of news stories that would otherwise be buried in text. Such infographics are shared widely in blogs and social media, turning what might otherwise have been obscure data findings into the day’s biggest buzz.
Thus, although organizations need to be mindful of business users who have visual impairments, it is clear that their investments in data visualization libraries, tools, and applications -- and the professionals who know how to implement them -- are worthwhile. Visualization is often the best and most persuasive way of communicating quantitative insights. “We acquire more information through vision than through all of the other senses combined,” wrote Colin Ware, in his book Information Visualization. “The 20 billion or so neurons of the brain devoted to analyzing visual information provide a pattern-finding mechanism that is a fundamental component of our cognitive activity.”
The broad popularity of infographics is pushing higher expectations for data visualization and graphical interaction capabilities in business intelligence and analytics tools. Visualization, coupled with the expanding use of analytics, should be a key concern for data management because its growth affects how data is provisioned for users and the value they gain from it. Good data visualization is critical to making smarter decisions and improving productivity; poorly created visualizations, on the other hand, can mislead users and make it more difficult for them to overcome the daily data onslaught.
Data Visualization and Discovery: Research Insights
I recently finished writing a TDWI Research Report, Data Visualization and Discovery for Better Business Decisions, which will be published in early July and is the subject of an upcoming TDWI Webinar. “Visual discovery,” which brings together data visualization with easy-to-use, self-directed data analysis is, of course, one of the hottest trends in BI and analytics. Users are implementing visual discovery tools to explore data relationships between and across sources, perform what-if analysis, and discover previously unseen patterns and trends in data. (http://tdwi.org/webcasts/2013/07/data-visualization-and-discovery-for-better-business-decisions.aspx)
The research report, which includes the results of an extensive survey of the TDWI community, focuses on how organizations can use data visualization, visual analytics, and visual data discovery to improve decision-making, collaboration, and operational execution. Briefly, here are three insights from the report.
Insight #1: Future plans are focused on analytics
Three out of five (60 percent) of respondents said that their organizations are currently using data visualization for display or snapshot reports, and/or scorecards. Far fewer (33 percent) are currently implementing data visualization for discovery and analysis, and only about a quarter (26 percent) of respondents are doing so for operational alerting. However, larger percentages say they plan to employ data visualization for these latter two types of requirements (45 percent and 39 percent, respectively). The results suggest that although dashboard reporting currently dominates BI visualization, the future focus is on visual analytics and, to a somewhat lesser extent, real-time operational alerting.
Insight #2: Marketing functions are the biggest users of visual data discovery and analysis
TDWI Research finds that the function for which visual data discovery and analysis capabilities are most important is marketing. Both survey analysis and my interviews pointed to the marketing function as the user bastion driving the need for easy, self-directed visual analysis of customer and market data. The most important types of visualizations for executive management remain standard dashboard displays or snapshot reports, as well as scorecards. It appears that visual discovery and analysis has not yet become the mainstream for business functions beyond marketing.
Insight #3: Time series analysis is an important focus for visualization
A significant percentage of respondents implement visualizations for time-series analysis (39 percent). Users in most organizations need to analyze change over time, and they typically use various line charts for this purpose. Some will apply more exotic visualizations (such as scatter plots) for specialized time-series analysis, including examining correlations over time between multiple data sources. Time-series, pattern, and trend analysis complement predictive analysis. Almost a third (32 percent) of respondents use visualizations for forecasting, modeling, and simulation, and 22 percent are doing so for predictive analysis.
The Right Visualizations for the Right Activities
Visualization is exciting, but organizations have to avoid the impulse to clutter users’ screens with nothing more than confusing “eye candy.” One important way to do this is to evaluate closely who needs what kind of visualizations. Not all users may need interactive, self-directed visual discovery and analysis; not all need real-time operational alerting. With adroit use of visualization, however, users will be able to understand and communicate data far more effectively.
©2013 by TDWI (The Data Warehousing Institute), a division of 1105 Media, Inc. Reprinted with permission. Visit tdwi.org for more information.