Data Visualization: Getting Value From Information

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data visualization

Data visualization technologies communicate large amounts of data in ways that are easier for business groups to understand, so insights can be quickly gained.

2. Output depends on input: Visualization tools can work only with the data they’re given, so part of the challenge lies in deciding which information to incorporate. Consider both technical issues—such as how to integrate different data sets—and more functional questions­—such as how different data is related and which open data or purchasable data sources might aid in the analysis.

3. Made-to-order or off- the-shelf tools?: While it is possible to build visualization tools in-house, many organizations choose to buy technologies from specialist providers, particularly because of the ongoing support they provide.

4. Paint a picture: The whole point of data visualization is to provide a visual experience, so simply describing what these tools might deliver is counterintuitive. Instead, start by selecting a data set to focus on and then use the tools to construct some basic visualizations. Seek feedback from colleagues and business users, and then amend and expand the prototype. The aim is to demonstrate what can be achieved.

5. Think about the users: Their experience, in terms of look, feel and usability, is absolutely crucial. Most business users have limited patience for experimentation and won’t use tools they can’t quickly learn to use. Graphic designers and user-experience specialists may prove valuable here.

6. Consider the future: Given that most organizations are making greater use of business intelligence and analytics—and will continue to do so—data visualization capabilities will become ever more important. Businesses need to decide what talent they’ll need, how to source that talent in the future, and whether to build internal resources or to work with third-party providers.

These considerations reflect an important lesson for organizations: While advances in analytics make it possible to generate a valuable array of potentially transformative business insights, there is no point to the exercise if those insights cannot be seen and understood by the people who are making the decisions.

The promise of advanced visualization tools is to make previously unseen insights visible. Only when an organization can see such signposts will it be able to make quick and effective decisions based on insights that will lead to tangible business outcomes.

Nick Millman is managing director of Accenture Analytics, part of Accenture Digital. John Miller is managing director of the Data Insight R&D Group at the Accenture Technology Labs.

This article was originally published on 2014-07-24
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