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October 2016, Volume 4, Number 5

Four steps to make a data visualization project succeed

There's more to effective data visualization in advanced analytics applications than simply dumping data into a visualization tool and creating charts and graphs. Speaking at the 2016 TDWI Accelerate conference in Boston, Jennifer Shin, senior principal data scientist at The Nielsen Company and founder of consultancy 8 Path Solutions, provided the following tips on getting the most out of a data visualization project. Keep an open analytical mind, with visualization's help. Data science isn't a linear pursuit, Shin said. Investigating one line of inquiry might lead to answers you weren't even looking for, but only if you're open to seeing them. These kinds of unexpected insights are more likely to pop up when data is plotted out graphically instead of put in a spreadsheet. "You need to explore the data,” she added, “because a lot of times you might come up with new applications that you hadn't thought of." Know your audience. Data visualizations are essentially vehicles for communicating information, but they tend to fail when ...

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