Dashboard development and data visualization tools for effective BI

Last updated:August 2013

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Editor's note

As the use of business intelligence and advanced analytics technologies proliferates in more companies and plays a bigger and bigger role in business success, deployments of data visualization software and tools are also expanding -- and evolving. BI and IT teams increasingly are getting requests from business users for data visualization capabilities, often delivered through user-friendly BI dashboards, to help meet business intelligence objectives. Furthermore, the growing adoption of big data applications increases the complexity of business data analytics, including the types of visualizations that data scientists and other users are looking to run. Used effectively, new data visualization tools and well-thought-out dashboard designs help streamline the visual presentation of large, complex sets of data for better business decision making.

Yet the wide array of available features and options can be overwhelming. Business intelligence managers and consultants say that dashboard designers must fight the temptation to create glitzy dashboards with bells and whistles galore and instead focus on what business users most need. In addition, a variety of vendors have advanced data visualization tools on the market. Understanding the different capabilities they support and identifying the appropriate tools for an organization's specific BI program needs are crucial steps for companies looking to effectively and meaningfully represent large sets of data without weighing down BI and IT staffers with development and end-user support tasks.

To help analytics and BI project teams navigate the challenges, this guide offers expert insight and advice on dashboard development and data visualization trends, including the application of data visualization tools in big data environments.

1Data visualization tools evolve with big data

Data visualization in the world of big data is challenging, yet increasingly necessary. And, in many cases, the use of data visualization tools must change to accommodate the needs of big data. In the articles in this section, experts offer fresh ideas on combining data visualization and big data analytics.