For many of the projects we do at Visually, data comes from a source that has already done some aggregation. This is both a blessing and a curse. Aggregation definitely simplifies the analysis and visualization process, but it can also greatly reduce the visualization and analysis options. This is because aggregation often destroys connections in data.
Survey data is one of the most common places where connections get destroyed by aggregation. The typical aggregated output we see from survey data looks something like this (data is manufactured):Do you like: Blueberries? Raspberries? Limes? Bananas? Oranges? 60% 56.67% 70% 80% 86.67%
And that can produce visualizations like this:
But this data is missing a lot of valuable information. For example, how likely is it that people who enjoy blueberries also enjoy raspberries? Is there correlation between people who like citrus and people who... keep reading