How:Slice & Dice Library Data: Difference between revisions

::* '''Name''' — single-line [[Text field]], entry name

::* '''Type''' — [[Radio Buttons field]], entry status, with items '''Consumer''' and '''Institution'''

:* '''Products''' with unique entry name and the following fields:

::* '''Name''' — single-line [[Text field]], entry name

Note that we already have some good hooks for subsequent analysis:

* Products have categories, cost, and a standard price. We can summarize by product category, and cost & standard price give us the basis for calculation of margins.

:* '''Customer type''' — [[Calculation field]], string result, entry status

::* Press the '''+Field''' button, choose '''customer.type''' from the list

:* '''Product category''' — [[Calculation field]], string result, entry status

::* Press the '''+Field''' button, choose '''product.category''' from the list

Enter as much data now as you can stand, as more data makes more meaningful analysis. Specifically, enter at least 2 entries for each of the following:

; Customers — Customer types: Enter at least 2 entries for Consumer-type customers and 2 for Institution-type customers.

; Products — Product categories: Enter at least 2 entries for Lumber products and at least 2 for Tools products.

; Orders — Orders: Enter as many orders as you can stand, making sure to reference as many customers of different types and zips as possible and products of as many categories as possible; then try some slicing & dicing, while reading the following sections. Then enter some more, until you are satisfied with what you can get out of slicing & dicing.

; Grouping

: Then, group by '''Customer type''' and see how consumer data compares to institutional data. Do they both make sense? Are there any surprises?

: Then, group by '''Product category'''. Are you more profitable selling lumber or tools? Can the margins be increased within either category?