The gap between a bad and good data visualization is small. The gap between a good and great data visualization is a vast chasm! The challenge is that we, and our HiPPOs, bring opinions and feelings and our perceptions of what will go viral to the conversation. This is entirely counterproductive to distinguishing between bad, good, and great. What we need instead is a rock-solid understanding of the updraft we face in our quest for greatness, and a standard framework that can help us dispassionately assess quality. Let’s do that today. Learn how to separate bad from good and good…
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I worry about data’s last-mile gap a lot. As a lover of data-influenced decision making, perhaps you worry as well. A lot of hard work has gone into collecting the requirements and implementation. An additional massive investment was made in the effort to perform ninja like analysis. The end result was a collection trends and insights. The last-mile gap is the distance between your trends and getting an influential company leader to take action. Your biggest asset in closing that last-mile gap is the way you present the data. On a slide. On a dashboard in Google Data Studio. Or…