Instructions: Classify columns as Dimensions (text, categories, groups, attributes) or Measuers (numbers, aggregates, etc.)

• Measure columns contain values that you want to aggregate (sum, average, etc). (ex: sales numbers, units sold.)
• Dimension columns contain values that you want to group by or filter the data set with. (ex: store location, sales person name.)
• We now support multiple date formats, including: MM/DD/YYYY and YYYY-MM-DD.
• Note: Just because a column contains numbers doesn't necessarly mean that you always want to aggregate it.
  Ex. An NFL data set may contain a "Quarter" column. It doesn't make sense to average, or sum, the Quarter of a play,
  therefore, it should be classified as a "Dimension".

Note: This data set may not be well formed. Please ensure the following:

• The data file must be a CSV file.
• Ideally, the file would contain between 100 and 10k rows.
• The first row of the file must contain column headers.
  • Ensure each column has a header value, and that there are no trailing columns/commas.
• Data should not be sparse. Most cells should contain data.
• Ensure Measure columns contain numbers without any formatting (bad: "$100M", good: "100000000").
• Data should be in a format that easily allows for pivoting.
  • Dimension columns contain many repeated values, the data set can be grouped by these Dimensions to aggregate Measures.
• Each cell has only a single piece of data. (ex: no date ranges)
• Ideally the file should contain a handful of Dimensions and a handful of Measures.

Take a look at some of our Example Boards to get an idea.
Or take a look at this example data file.