4. What are cubes (cont.)?
syn: Hypercube, multidimensional database (MDB),
olap cube
Cubes can have more than three dimensions
5. Fact Tables
Contain numerical measurements of a certain
business process.
E.g. $12.000 sales in NY store on 12-01-08
Additionally foreign keys to different dimension
tables
E.g. further store/sales person information
Center in star schema
6. Dimension Tables
Contain attributes by which data can be grouped
e.g. city/region of store, product category
Linked to the fact table via their primary keys
Slowly changing dimensions: dimensions which
change over time. Can be dealt with in 3 ways:
Overwritingold values
Add new row to table, distinguish records by versioning
Add new column (attribute) to existing row
7. Data Storage Models
relational databases (ROLAP)
Datain tables
Summaries stored in precalculated tables
multi-dimensional databases (MOLAP)
Data in multidimensional arrays
+ Less disk space
+ Better Performance (precalculated aggregates)
- Time to aggregate & calculate
- Updates require recalculation
Hybrid (HOLAP)
8. Hierarchies
Grouping of dimensions e.g. country -> sales
e.g. month -> semester - region -> state -> city
> quartal -> year -> store
2008 Germany
H1 2008 Southern germany
Q1 2008 BaWue
Jan 2008 Stuttgart
Store A
Feb 2008
Store B
March 2008
Q2 2008 … Bavaria
Munich
H2 2008 … Store A B C
9. Operations: Slice
Slicing is the process of retrieving a block of data
from a cube by filtering on one dimension
10. Operations: Dice
Dicingis the process of retrieving a block of data
from a cube by filtering on all dimensions
11. Operations: Drill Up/ Down
Drilling up: Presenting data at a higher level on the
hierarchy e.g. Store -> Region
Drilling Down: Presenting data at a lower level on
the hierarchy Region -> Store
12. Building the cube in SSAS
Preconditions
Connecting datasources
Defining views
Selecting dimensions
Define fact & dimension tables & time dimension
Select measures
Deploy & query the cube
Demo