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How to choose the right data visualization tool

Big data has become an increasingly popular buzzword in nearly every industry. As more business users seek to make the most of the vast amounts of information and leverage analytics for innovative improvements, they will need to select the right tools for the job.

Information Week contributor Doug Henschen noted that there has recently been a plethora of emerging data visualization tools on the market in response to growing demand. Without visual representations of big data, insights can be difficult to come by, and Henschen pointed out that such tools are "hot" because they streamline the analysis process.

However, there are a few things users should look for when selecting data visualization applications to ensure ease of use and optimal functionality. Forrester analyst Boris Evelson and Noel Yuhanna recognized six traits which can identify advanced tools from simple static graphs, according to Henschen. These characteristics include dynamic data, visual querying, linked multidimensional visualization, animation, personalization and actionable alerts.

Additionally, computer software professional James Foster told Tech Trends Journal that administrators should investigate a few key components within their business before selecting a visualization tool. To start, decision makers should identify the "information consumers and users," or the people who will utilize the application and recognize their skills and abilities. Not knowing or having a full understanding of these aspects could result in low adoption and wasted resources.

"If you limit the process to the vendor and your IT team, you will get a very good visualization that works well for the IT team, but it might not be useful to the actual consumers of the data," Foster pointed out to Tech Trends Journal.

Users should also seek details into how often the data will be accessed and from what endpoints individuals will connect with the information. For example, certain solutions support mobile devices, allowing users to access analytics from a variety of platforms.


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