example

Bevore we start with complex planning issues, it´s important to understand the basics of the „logic“ in the tool! So we build up a small personal budget where we take care about 2 income accounts (Salary and Family) and 4 expense accounts (Rent, Food, Fun and Communication).

identify dimensions

For every dataset, a basic dimension is needed, here we call it „Basic Dimension„. Additional we need two more dimensions for „Income“ and another for „Expense„.

Inside the Dimensions we need the following Dimension-Elements:

Basic Dimension

• „My Personal Budget„

Income

• „Salary„
• „Family„

Expense

• „Rent„
• „Food„
• „Fun„
• „Communication„

Additional we need to define the relationship between the dimensions:

1. Root – Basic Dimension
   1. Child – Income
   2. Child – Expense

This will build up an „virtual“ tree looking like this:

• My Personal Budget
  • Salary
  • Family
  • Rent
  • Food
  • Fun
  • Communication

Later you´ll see, that we have several visual helpers do divide them from each other. Those depend on the logical type of the related dimension. Those individual logics will be called structurelogic and we will use 3 seperate logics for our dimensions.

create structurlogic (calculation rules)

To make it simple, we only want to have a fact field, that allows to enter an absolut value for an individual period. This means, we build the following 3 structurtypes containing one fact field.

1. Company
   1. no factfield, only for aggregation
2. Income
   1. factfield, revenue (float)
3. Expense
   1. factfield, expense (float)

Later you’ll see how to build a calculation of Income–Expense.

periods

„The only limitation is time“ – it’s a fact, that time is the limited fact in a human live. So nearly everything is adjusted to timemanagament and the available ressources for the focused moment. For our budget we want to focus on months as smallest viewport and the year as aggreagtion of the individual months. The framework has a special handling of periods, that you need to know for further datasets:

Weeks:

• -10001,-10002,…..,-10048 (All weeks from the first year, 7.5 days per week)
• 1,2,….,12 (All months from the first year, 30 days per month)
• –1,-2,-3,-4 (All quaters from the first year, 3 months, 12 weeks, 90 days per quater)
• 10001 (the first year, 12 months, 4 quaters, 48 weeks, 360 days)