Best way to combine multiple fact tables in single mart

Question

Hi, quick question that I think I know the answer to, just wanted to bounce it off everyone here to make sure I'm on the right track.
I have a HR datamart that contains several different fact tables. Some of the facts are additive across time (i.e. compensation - people get paid on different days, when I look at a month I want to see the total of all pay dates within that month). The other type of fact is more "status over a set of time" - i.e. a record saying that I'm employed in job X with a salary of Y from a given start date to a given end date.
For the "status over time" type facts, if I choose January 2009 (month level) in the time dimension, what I'd really like to see is the fact records that were in place "as of" the last day of the month - i.e. all records where the start date is on or before 1/1/2009, and whose end date is on or after 1/1/2009. Note that my time dimension does go down to the day level (so you could look at a person "as of" the middle of the month, etc. if you're browsing on a day-by-day basis)
I've set up the join between the time dimension and the fact table as a complex join in the physical layer, with a clause like "DIM_DATE.DATE >= FACT.START_DATE AND DIM_DATE.DATE <= FACT.END_DATE". This seems to work perfectly at the day level - I have no problems at all finding the proper records for a person as of any given day.
However, I'm not quite sure how to proceed at the month level. My initial thought is:
a) create a new LTS for the fact table at the month level
b) in the new LTS, add the join to the time dimension
c) in the new LTS, add a where clause similar to LAST_DAY_IND = 'Y' (true for the last day of each month).
Is this the proper way to do this?
Thanks in advance!
Scott

Answer 1

Hi Scott,
I think you're on the right track but I don't think you need the last part. Let me generalize the situation to the following tables
DAILY_FACT (
DAILY_FACT_KEY NUMBER, -- PRIMARY KEY
START_DATE_KEY NUMBER, -- FOREIGN KEY TO DATE DIMENSION FOR START DATE
END_DATE_KEY NUMBER, -- FOREIGN KEY TO DATE DIMENSION FOR END DATE
DAILY_VALUE NUMBER); -- FACT MEASURE
MONTHLY_FACT(
MONTHLY_FACT_KEY NUMBER, -- PRIMARY KEY
MONTH_DATE_KEY NUMBER, -- FOREIGN KEY TO DATE DIMENSION, POPULATED WITH THE KEY TO THE LAST DAY OF THE MONTH
MONTHLY_VALUE NUMBER); -- FACT MEASURE at MONTH LEVEL. DATE_KEY is at END of MONTH
DIM_DATE(
DATE_KEY NUMBER,
DATE_VALUE DATE,
DATE_MONTH VARCHAR2(20),
DATE_YEAR NUMBER(4));
DIM_DATE_END (ALIAS OF DIM_DATE for END_DATE_KEY join)
Step 1)
Make the following three joins in the physical layer:
a. DAILY_FACT.START_DATE_KEY = DIM_DATE.DATE_KEY
b. DAILY_FACT.END_DATE_KEY = DIM_DATE_END.DATE_KEY
C. MONTHLY_FACT.DATE_KEY = DIM_DATE.DATE_KEY
Note: The MONTHLY_FACT DATE_KEY is joined to the same instance of the date dimension as the START_DATE_KEY of the DAILY_FACT table. This is because these are the dates you want to make sure are in the same month.
Step 2)
Create a business model and drag DIM_DATE, DAILY_FACT and DIM_DATE_END into it.
Step 3)
Drag the physical table MONTHLY_FACT into the logical table source of the logical table DAILY_FACT.
Step 4)
Set DAILY_VALUE and MONTHLY_VALUE to be aggregates with a "SUM" aggregation function
Step 5)
Drag all required reporting columns to the Presentation layer.
Step 6)
Create your report using the two different measures from the different fact tables.
Step 7)
Filter the report by the Month that joined to the Start Date/Monthly Date (not the one that joined to the end date).
Step 8)
You're done.
The act of combining the two facts into one logical table allows you to report on them at the same time. The strategy of joining the START_DATE_KEY and the MONTH_DATE_KEY allows you to make sure that the daily measure start date will be in the same month as the monthly fact table.
Hope that helps!
-Joe
Edited by: Joe Bertram on Jan 5, 2010 6:29 PM