Tableau 10 introduces the ability to quickly perform clustering analysis in your visualizations. This allows you to find groups, or clusters, of individual data points that are similar based on any number of your choosing. This can be useful in many different industries and fields of study, as in the following examples:
- Marketing may find it useful to determine groups of customers related to each other based on spending amounts, frequency of purchases, or times and days of orders.
- Patient care directors in hospitals may benefit from understanding groups of patients related to each other based on diagnoses, medication, length of stay, and number of readmissions.
- Immunologists may search for related strains of bacteria based on drug resistance or genetic markers.
- Renewable energy consultants would like to pinpoint clusters of windmills based on energy production and...