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Executive Summary: Visual Analytics for Making Smarter Decisions Faster

Business users today want to move past the limits of spreadsheets and canned business intelligence (BI) reporting to gain a richer, more personalized experience with data. With data volumes exploding and a greater variety of data available to them, business users want to explore more data and discover new insights that they can apply readily to improve business strategies, processes, operations, and customer engagement. Along with easier data exploration, users are seeking to increase the depth and frequency of their data analysis. This is a significant change because users who are engaging in analytics processes interact with data differently from what has been the norm with traditional BI. Rather than just consume data, they ask questions, try different views and approaches, build predictive models, and more. Supporting users’ forays into analytics is critical because it’s becoming clear in nearly every industry that organizations need to be more analytical to compete effectively. To lead in their respective industries, organizations need to apply technologies and methods that enable them to spread to more users the ability to analyze data effectively without adding burdens and costs to IT.

Interest in performing analytics is intersecting with technology progress toward easier to use yet more sophisticated data visualization in tools and applications available on premises and in the cloud. The combination—visual analytics—is now a major trend. Visual analytics can help users become more productive with data by using software to integrate data analysis capabilities with modern, graphical ways of expressing information. Such technologies give users more power and control over analytic discovery, enabling them to progress further on their own, in a self-service fashion, rather than depend on IT developers’ intervention. This can be important in large organizations (where there are often considerable IT application backlogs) as well as in small and midsize organizations (that lack extensive IT support for data analysis).

This TDWI Best Practices Report examines experiences with BI, visual analytics, and visual data discovery to uncover how organizations can move forward to make users more productive with data and use technologies to improve collaboration. Our research explores where users are succeeding with BI and analytics and where visual analytics can improve their decisions. Currently, users are not fully satisfied with their ability to use visual analytics functionality. Training and education are needed to help them understand how to use visualization effectively and exploit new methods of data analysis.

In our report, TDWI Research advises that the best approach to expanding self-service visual analytics to more users will be balanced and well-managed, and include data governance. Our research finds that data governance is widely regarded as IT’s responsibility; however, business users must share this responsibility if self-service is to avoid pitfalls such as inconsistent data security and quality as well as performance problems with data access and analysis. Good governance will be important as users begin to implement self-service data preparation and data blending technologies to access and integrate a wider variety of data.

Visual analytics can play an important role in other data-driven objectives such as identifying repeatable decisions that could be automated and enabling users to monitor, analyze, and continuously improve decision management processes. This report examines how visual analytics fits with this and other important goals and trends that are enabling organizations to realize higher value from their data.

IBM, Information Builders, Oracle, Qlik, SAP, SAS, Tableau Software, and TIBCO Spotfire sponsored the research and writing of this report.

About the Author

David Stodder is senior director of TDWI Research for business intelligence. He focuses on providing research-based insights and best practices for organizations implementing BI, analytics, data discovery, data visualization, performance management, and related technologies and methods and has been a thought leader in the field for over two decades. Previously, he headed up his own independent firm and served as vice president and research director with Ventana Research. He was the founding chief editor of Intelligent Enterprise where he also served as editorial director for nine years. You can reach him by email ([email protected]), on Twitter (, and on LinkedIn (

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