When I was deciding where to go with my husband, I experienced a bit of work-related déjà vu. Every option I considered was very different from the next, but all were possibilities chosen based on the same exact set of data (number of vacation days available, budget, etc.). I felt like I was back at the office working with a team, arguing about what decision to make, even though we were all reviewing the same data.
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Without a clearly or accurately defined problem, time and other resources will be wasted, and you’ll be left unable to make an effective decision. Often, nailing down exactly what you’re trying to solve is more difficult than the analysis itself.
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I’m going to discuss a very important relationship in every data analyst’s life: the marriage of technical skills to their soft-skill counterparts. Just like every relationship, this one requires understanding and balancing complementary aspects to be successful. Let’s look at how the skill for knowing how your sphere of influence—i.e. awareness of what you can do yourself, and how you can influence others—works hand-in-hand with your skill for driving data-based decisions.
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Happy Pi Day! To celebrate, I will be discussing one of the most widely-used (but not widely useful!) data visualizations: the Pie Chart. While charts and graphs are invaluable tools for easily and quickly communicating a complex message to an audience, if they aren’t wisely designed, they can also be misinterpreted, misleading, or even deterrents to action. And pie charts—despite their deceptively simple style and popularity—often lead viewers astray, or lead nowhere at all.
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There’s no better way to illustrate the ROI of a program than to literally illustrate it—with effective, irrefutable visuals of the data—which can serve as common ground for discussions about the work being analyzed.
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Data tells stories: of success and ambition, as well as failure and challenge. It looks to the past and to the future, while delivering a clear and accurate now. But data professionals know it speaks best when arranged with a simple visual alongside a cogent message. Visuals show the story of your data, but are your visuals telling the right story the right way? When data storytelling goes wrong—when the visual is too complicated, when there are too many meanings in the graphic, when the message can’t be read quickly or clearly—your audience will not hear the story. And just as a great visual presentation can be remembered for a long time, some stakeholders may take a long time to forget a bad one.
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