For Data Scientists, Visualization Experts, and Excel Formula Architects, the standard Dimensions and Measures may not completely fit your needs. Your story has a deeper level of complexity which requires a deeper connection with the data. Custom Fields give you greater flexibility with your data.
A frequent custom data field you would probably use is a Table Calculation (or Table Calc): perform mathematical, logical (true/false), lexical (text-based), and date-based calculations on the dimensions, measures, and other calculations in your query. Table Calcs are similar to Excel functions. Let's break down what a Table Calc is, in terms of the syntax.
Table Calculations Syntax
With Table Calculations (or 'Table Calcs'), you can create metrics on-the-fly. Table Calcs are similar to formulas found in spreadsheet tools like Excel.
Let's take a very simple example: work order status and work order count per status. Let's say you want to calculate the percentage of work orders, per work order status, to the total number of work orders. In Excel, it may appear akin to this:
In Analytics you would create a similar formula, except that you would not refer to cells (like "C2" or "A3"), but rather refer to the Dimensions or Measures involved. Also, you would not have to duplicate the formula for each cell or make sure the $X$n cell remained intact. Therefore, this formula in Analytics would appear as:
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${subscriber_workorders.count}/sum(${subscriber_workorders.count})
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Table Calcs appear as green columns in the data table, rather than as blue columns (Dimensions) or orange columns (Measures).
To use a Table Calc, first you should activate the data fields you want to use.
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