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Having in-depth demographic information is often seen as the holy grail in the eyes of data analysts and their business stakeholders, and there is a good reason why: the context that can be added to your analytics, as a result, is hugely advantageous.
If you haven't had a chance, please checkout the Decision 2016 Presidential Election application. The app predicts who the winning candidate will be within a given U.S. neighborhood, as well as breaks down the outcome by demographics such as age, education, income, and race. Data from SurveyMonkey and the blending, spatial, predictive and Gallery API functions in Alteryx are used to create predictions that are beautifully displayed with help from Carto and Tableau. This post will walk through the architecture that was used to accomplish this.
One of the most common support issues we face is when users of our software want to compare the population and growth of different races and ethnicities. When it comes to using Hispanic data, results seem skewed because percents do not add up or align with other race categories and it makes users question the integrity of the data. What most users don’t know is that the US Census does not classify Hispanic people as a separate race. But by simply aggregating different variables, we can get the data to align as we expect it to. Lonnie Yenny, Alteryx Data Products Specialist, breaks it down for us...