Answer / dhalpathi

in star schema dimension and master data table are same.
in extend star schema dimension and master data table are
different.( master data outside the cube and dim..table
inside cube). in star schema we can analyis only 16 angle.
but in ex..star schema we can analyis 16*248 angle.

Answer / latha

In starschema dimensions are not sharable where as in
extended starschema dimension tables are sharable using SID
tables,i.e master data tables are out side the cube and
every characteristic is connected to its corresponding
master data table using surrogate id table.

Answer / gigs

In star schema dimension and master data table are same.
in extend star schema dimension and master data table are
different.( master data outside the cube and dim..table
inside cube). in star schema we can analyis only 16 angle.
but in ex..star schema we can analyis 16*248 angle.

Master data table uses SID, b'cuse to convert alpha numeric
values to numeric this improves ur process speed.
And also we can analyze the angles in 16X248.

By Gigs
BW Consultant, SAP German.

Answer / pranith kumar chakilam

star schema
1.It can be analysed only in 16 dimensions.
2.Master data is not reusable.
3.performance is degraded because of the alphanumeric
values in the fact table.


Extended Star Schema
1.It can be analysed in 16*248 dimensions.
2.Master data can be reusable as it is not inside the cube.
3.Better performance as there r no alphanumeric values in
the fact table.

Answer / g k ramesh

1.In star schema the central fact table is surrounded by
master data tables(=dimension tables).since master data
lies with in the cube.we can not reuse the master data
information for other cubes.where as in Extended star
schema the central fact table is surrounded by dimension
tabes(!=master data tables).master data tables lies out
side the info cube.so,we can share the master data
information for other cubes.

2.In star schema the fact table holds Alpha-numaric
information.so,it degrades the database performance and
query performance.where as in Extended star schema using
SID tables we can see all the information in the fact table
as numaric.so,it improves the database performance and
query performance.

3.In star schema the fact table is directly connected to
the master data tables and it can be connected to a maximum
of 16 master data tables.so,we can not analyze the data
more then 16 angles.where as in Extended star schema the
fact table is connect to maximum 16 dimension tables and
each dimension table can be connected to a 248 SID
tables.so we can analyze the data in 16*248 angles

Answer / pritam

multi language support in extended star schema and also
slowly changing dimensions also supported ,,but in star
schema we dont have this option

Answer / suprakashmay nandi

a. Use of generated keys(numeric) for faster access.
b. Externa hierarchy
c. Multilanguage support
d. Master data common to all cubes
e. Slowly changing dimension supported.
f. Aggregates in its own table for faster access.

Answer / b.aravinda

In extended star schema Multi Languages is supported,
tracking of history is possible, hierarchical structure is
possible and master data is sharable.

Answer / kayani

my knowledge
is sap as data is divided into masterdata(data frequently not changed)+transaction data(frequently change of data).
arranging of masterdata(m.d) and transaction data(t.d) in dataware house we use a procedure that procedure called schema. as transactiondata table is middle of masterdata table we termed it as star schema.
disadvantages of star schema :
1)when we are designing a query we have infoprovider as infocube where transaction data is stored in infocube to perform query we need both m.d and t.d so data manager has to join both m.d table and infocube it consumes time, accessing time is more performance degrading takes place.
2)in star schema the master data (m.d)and t.d table split at one pointer so in a server there are many infocubes if many cubes want to use same masterdata we cannot access the same masterdata into another cube but only copy so data redundancy takes place same data is stored in multiple places in the server.
3)star schema doesn't support extrnal hirearchy model.
finally the limitations of star schema are:
1)system performance degradation due to single pointer.
2)data redundancy.
3)starschema doesn't support external hierarchy.
to overcome this limitation we go for extended star schema model.
1).where transactiondata table resides in center followed by dimensional datatable followed by sid table(which consists of masterdata table) out side of the dimensional table. so in performing a query data is accessible from one infocube to another so we overcome from data redundancy system performance increases.
2)when performing a query as the masterdata table and trasactional data table split not at one pointer but if n masterdata table and 1 transaction data table then it splits into (n+1) table there is no join so system performance further increases.
3) it supports external hirerchy model
aftr all we can eliminate system degrading performance,dataredundancy and we can use external hirerchy models.
note:
in extended star schema the master data table (sid tables ) connects the dimensional table through sid's i.e surrogate system genrated ids and dimensional table with transactional  data table through dimensional id's. where as in star schema masterdata table through dimensional ids only.as all masterdata resides in one table masterdata table.


hope this might be understand in overview.

Answer / aviroop

Star schema is a special case of snowflake schema. Here,
the fact table is surrounded by dimension master data
tables inside the Cube. Bt its extended schema version
further breaks up the dimension tables of star schema into
dimension Id table and master data table. It simplifies and
increases the database accessibility for other cubes to
make it more robust.

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