Data Visualisation and Discovery for Better Business Decisions - TDWI - 2013-Q3

Business Visualisation Review by TDWI



Far from mere “eye candy,” data visualization is critical to fulfilling widely held goals for expanding
organizations’ analytics culture and driving more decisions with data. Across organizations,
employees who are subject matter experts in areas such as marketing, customer service, online
engagement, finance, and more need to interact with data and analyze it for significant patterns,
trends, and anomalies. Yet, most of these professionals would hardly consider themselves “business
intelligence users,” much less professional data scientists or data analysts. Tools and practices for data
visualization, data discovery, and visual analysis are enabling these “nontechnical” users to make
effective use of data and reduce their time to insight.

This TDWI Best Practices Report focuses on how organizations can use data visualization, visual
analytics, and data discovery to improve decision making, collaboration, and operational execution.
The report provides analysis of an in-depth research survey and user stories to reveal current
strategies and future plans for data visualization and analysis. The report offers recommendations
for successfully evaluating and deploying data visualization, data discovery, and visual analysis
technologies to achieve shorter time to insight for users across the enterprise.

Users need data visualization for a variety of BI and analytics activities, including reporting,
scorecards, operational alerting, and data discovery and analysis. Rather than just giving users “new
toys” to play with, organizations should examine how they can match visualization technologies
and practices to user requirements. Across the board, however, a key element in the success of
visualization is data interaction; users need broad capabilities for manipulating data, including to
drill down, cross cut, slice, and dice data directly from graphical interfaces.

Recommendations

• Improve data visualization and visual analysis for nontechnical users “Nontechnical” users are by definition not expert in the tools and practices of accessing data and creating visualizations, but they often know their data well. Their struggle is in trying to interact with data. With visualization, organizations can give nontechnical users easier and more powerful means of data interaction.
• Match visualization capabilities to users’ types of activities Some users, including executives, need visualization primarily for display or snapshot reporting and scorecards. Others need operational alerting. Still others need visual data discovery and analysis, which can demand different visualization capabilities. Ensure that the technology deployment fits each purpose.
• Increase data interactivity with broader visualization functionality Just as many users need to go beyond static and tabular data, they need the flexibility to explore visualization options other than standard bar and line charts. Evaluate tools that offer more visualization options, including the ability to plug in visualizations that may not be part of the BI tool’s library.
• Use dashboards to establish a single view of information TDWI Research finds that users would like to see dashboards provide a complete and consolidated interface to view all the information they need. However, at large organizations in particular, users must deal with many application interfaces. Aim at consolidating interfaces into a single or small number of dashboards. 
• Make self-service data visualization and discovery capabilities a priority The biggest trend in BI and analytics today is self-service. Users want tools and platforms that allow them to interact with data on their own without hands-on IT development and supervision. Self-directed visual reporting and data discovery can free users throughout organizations to be more creative in their analysis and selection of visualizations to express insights.
• Address time series analysis requirements with improved visualization TDWI Research shows that evaluating how business performance and other conditions change over time is a common need for nearly all users. Yet, some users have only primitive means of analysis for this requirement. Provide users with greater interactivity and breadth of visualization options for time series analysis.
• Evaluate geospatial analysis and GIS sources for visual analysis needs Location is fast becoming a vital new dimension for data analysis. Location’s relevance is growing for users in fields that may not have considered geospatial analysis previously. Organizations should consider whether mapping and geospatial analysis functionality could give users new insights for strategic and operational decisions.
• Develop a strategy for integrating desktop and mobile dashboards TDWI Research finds that in most organizations, existing dashboards and visualizations are not accessible from mobile devices. Yet, with mobile device use growing, more users will demand BI and analytics capabilities on devices. To avoid chaotic dashboard proliferation, organizations should develop a comprehensive strategy.
• Evaluate in-memory computing to support visual analysis In-memory computing is an alternative to the performance constraints and design complexity that exist in standard disk-based environments. It is not always the right solution if users need access to near-real-time, live data. However, for highly interactive and iterative visual analytics, in-memory computing should be considered.
• Make improved operational efficiency a goal of data visualization and analysis TDWI Research finds that improved operational efficiency is the top business benefit organizations seek from deploying data visualization and analysis technologies. Organizations should therefore ensure that the right functionality and visualization options are available for users’ dashboard reporting and analytics as they address operational challenges.