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7 Notable Data Visualization Tools: Page 2

By Drew Robb     Feedback
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Similarly, Birst has observed a rise in self-service data preparation. Gartner supports this trend with the prediction that, by 2018, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis. The reason is simple; users are looking for tools that enable them to access, combine and transform data without depending on experts.

"Advancements in data visualization and self-service data prep tools have enabled users to not only interact with analytic-ready data, but also ingest raw data and prepare it for analytics," said Pedro Arellano, vice president of Product Strategy at Birst.

Birst's interface enables users to create data visualizations using a drag-and-drop and double-click approach. A recommendation engine guides users through the process of building a data visualization, providing suggestions based on the data being analyzed. Visual filtering, user-created metrics, instant metrics (such as percentage of value) and intelligent search functionality add to the self-service capabilities.

Users can apply filters, sort data and limit results to "Top N" data points. Data formatting is available to accommodate currency symbols, dates (including locale-based dates), decimal precision, units, percentages and conditional formatting and on individual visual elements (axes, tool tips and display values).


The whole user base of analytics is changing; gone are the days of needing a data scientist to interpret your data. Now, with modern data visualization software, a line-of-business employee can collect and analyze data in the most appropriate chart type, and send it directly to their manager's tablet for their input.

Accordingly, Tableau 9.3 lets users connect to data from almost any source, cloud or on-premise, and start building data visualizations. New features include more mapping data, expanded data connectivity options, self-service content discovery features for organizations and increased speed.

Selecting a Data Visualization Tool: a Few Tips

There are other data visualization tools available on the market, of course, and as the market matures, more are releasing good data visualization tools. So how should you choose?

Michael Lock, vice president and principal analyst, Aberdeen Group, believes ease of use is the key. However, it needs to be interpreted against the needs of the user base, he stressed.

"Ease-of-use can be difficult to describe and varies from company to company, but the general concepts apply broadly," said Lock. "Users need intuitive, drag-and-drop, easy drill-down capabilities in order to explore the data."

This means mapping precise use cases to data visualization types. Some may prefer charts, some dashboards, others scorecards; many more will want some combination of these features. Some users may need the ability to lay out graphics in a storyboard format, in order to lead people along the sequence of an analysis or to show how a conclusion or strategy came into being, Evelson said.

Drew Robb is a freelance writer specializing in technology and engineering. Currently living in Florida, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).

This article was originally published on June 17, 2016
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