modeling correct star schema for ssas tabular - sql-server

Question

I'm using ssas tabular (powerpivot) and need to design a data-model and write some DAX.
I have 4 tables in my relational database-model:
Orders(order_id, order_name, order_type)
Spots (spot_id,order_id, spot_name, spot_time, spot_price)
SpotDiscount (spot_id, discount_id, discount_value)
Discounts (discount_id, discount_name)
One order can include multiple spots but one spot (spot_id 1) can only belong to one order.
One spot can include different discounts and every discount have one discount_value.
Ex:
Order_1 has spot_1 (spot_price 10), spot_2 (spot_price 20)
Spot_1 has discount_name_1(discount_value 10) and discount_name_2 (discount_value 20)
Spot_2 has discount_name_1(discount_value 15) and discount_name_3 (discount_value 30)
I need to write two measures: price(sum) and discount_value(average)
How do I correctly design a star schema with fact table (or maybe two fact tables) so that I in my powerpivot cube can get:
If i choose discount_name_1 I should get
order_1 with spot_1 and spot_2 and price on order_1 level will have value 50 and discount_value = 12,5
If I choose discount_name_3 I should get
order_1 with only spot_2 and price on order level = 20 and discount_value = 30

Answer 1

Fact(OrderKey, SpotKey, DiscountKey, DateKey, TimeKey Spot_Price, Discount_Value,...)
DimOrder, DimSpot, DimDiscount, etc....
TotalPrice:=
SUMX(
SUMMARIZE(
Fact
,Fact[OrderKey]
,Fact[SpotKey]
,Fact[Spot_Price]
)
,Fact[Spot_Price]
)
AverageDiscount:=
AVERAGE(Fact[Discount_Value])
Fact table is denormalized and you end up with the simplest star schema you can have.
First measure deserves some explanation. [Spot_Price] is duplicated for any spot with multiple discounts, and we would get wrong results with a simple SUM(). SUMMARIZE() does a group by on all the columns passed to it, following relationships (if necessary, we're looking at a single table here so nothing to follow).
SUMX() iterates over this table and accumulates the value of the expression in its second argument. The SUMMARIZE() has removed our duplicate [Spot_Price]s so we accumulate the unique ones (per unique combination of [OrderKey] and [SpotKey]) in a sum.

Answer 2

You say
One order can include multiple spots but one spot (spot_id 1) can only
belong to one order.
That's is not supported in the table definitions you give just above that statement. In the table definitions, one order has only one spot but (unless you've added a unique index to Orders on spot_id) each Spot can have multiple orders. Each Spot can also have multiple discounts.
If you want to have the relationship described in your words, the table definitions should be:
Orders(order_id, order_name, order_type)
OrderSpot(order_id, spot_id) -- with a Unique index on spot_id)
Spots (spot_id, spot_name, spot_time, price)
or:
Orders(order_id, order_name, order_type)
Spots (spot_id, spot_name, spot_time, order_id, price)
You can create the ssas cube with Order as the fact table, with one dimention in the Spot Table. If you then add the SpotDiscount and Discount tables with their relations (SpotDiscount to Spot, Discount to SpotDiscount) you have a 1 dimentional.
EDIT as per comments
Well, the Fact table would have order_id, order_name, order_type
The Dimension would be made up of the other 3 tables and have the columns you're interested in: probably spot_name, spot_time, spot_price, discount_name, discount_value.