January 9, 2007 at 11:32 am
I'm still learning on the BI/Datawarehousing front and I had a co-worker who informed me that Cubes and Stars are the same thing. Now I'm getting into reading about BI and I'm reading that they are two different things.
First, what exactly is a cube? I know what a star / snowflake is.
Second question, which do you prefer to use in your solution and why? What benefits does a cube give over a star or vice versa?
Thank you in advance for your comments and assistance.
January 9, 2007 at 9:27 pm
Hi Brandie,
A Star Schema and a Snowflake Schema are design structures, kind of like an ER diagram for a relational model.
A cube is an OLAP engine structure, which actually holds the data, similar to a table (in a way) in a relational database.
So, "Star" and "Cube" are not the same thing, but they all indeed relate to the same subject...
Also, I'm sure you now understand that the second question is a bit irrelevant, as you don't have (well, you can't) choose between using a "Star" and using a "Cube" as they are not really the same thing at all.
I would suggest you grab a good basic book on data warehousing/OLAP/Analysis Services which may assist you at this stage.
HTH,
Yaniv
January 10, 2007 at 11:01 am
Here's a great site for Data Warehousing: http://www.tdan.com/
RegardsRudy KomacsarSenior Database Administrator"Ave Caesar! - Morituri te salutamus."
February 13, 2007 at 1:26 am
The star schema (sometimes referenced as star join schema) is the simplest data warehouse schema,
consisting of a single "fact table" with a compound primary key, with one segment for each "dimension"
and with additional columns of additive, numeric facts.
An OLAP cube is a specially designed database that is optimized for reporting.
While most databases designed for online transaction processing such as those used in claims processing are
designed for efficiency in data storage, OLAP cubes are designed for efficiency in data retrieval.
This means that the data is stored in such a way as to make it easy and efficient for reporting.
Regular “relational” databases treat all data into the database similarly, however OLAP cubes
categorize data into "dimensions" and "measures". Measures represent items that are counted, summarized or
aggregated, such as costs or units of service. Dimensions are variables by which measures are summarized,
such as hospitals, physicians, or dates of service. This organization of data greatly facilitates the ability to
formulate data requests based on real-life situations. In addition, many of queries that could be posed to the
data are "pre-aggregated" in the database such that the answers have already been precalculated and
can be reported without delay.The term "cube" comes from the geometric object that has three dimensions.
OLAP cubes can have many more dimensions than 3, but the term continues to apply.
Viewing 4 posts - 1 through 3 (of 3 total)
You must be logged in to reply to this topic. Login to reply