Factless fact tables record events like student attendance or meeting participation without numeric facts. They contain only foreign keys to associated dimensions. Aggregate fact tables contain pre-calculated summaries derived from the lowest level fact table. Having the fact table at the lowest grain allows retrieving large result sets from the data warehouse more efficiently than querying the operational system. Aggregate tables reduce fact table size and the need to aggregate data during queries.

1. Fact Less Fact Tables
&
Aggregate Tables
in
Dimensional Modeling
By:
Prof. Sunita Sahu
Assistant Prof.,VESIT,Mumbai

2. Fact less Fact table
 Fact less Fact table does not contain any facts.
 Generally Fact less fact tables are used to record
the events such as students attendance,
attendance of participants for an Event like a
Meeting.
 There are applications in which fact tables do not
have non key data but that do have foreign keys for
the associated dimensions

4. Fact less Fact table Example

5. Aggregate Fact Tables
 Aggregates are pre calculated summaries derived
from the most granular fact table(level of detail in
the fact table).
 If the fact table is at the lowest grain.
 The facts or metrics are at the lowest possible level
at which they could be captured from the
operational system.
 what is the Advantages of lowest grain?

6.  Choose a simple STAR schema with the fact table
at the lowest possible level of granularity.
 Assume four dimension table with most granular
fact table.
 Operational system-single order, invoice, product
and so on.
 Data warehouse- produce large result set(these
retrieve hundreds and thousands
Aggregate Fact Tables

10. Fact table size

12. Need for aggregates

14. Aggregating fact table

17. THREE WAY