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MULTIDIMENSIONAL DATA MODELS:-
DG Kaur
INDEX:-
1. Definition of Multidimensional Data Models?
2. Types of MDDM:-
a. Star Schema
b. Data Cube Schema
c. Snowflake Schema
d. Fact Constellation schema
(Global Schema)
MULTIDIMENSIONAL DATA MODEL:-
 The MDDM was developed for implementing
data warehouse and data marts.
 MDDM provide both a mechanism to store data
and a way for business analysis.
TYPES OF MDDM:-
A. Data Cube Model.
B. Star Schema Model
C. Snow Flake Schema Model
D. Fact Constellations Schema Model
(Global Schema)
DATA CUBE MODEL:-
 When data is grouped or combined together in
multidimensional matrices called Data Cubes.
 In 2 Dimension:- row & column or products.
 In 3 Dimension:- one regions, products and fiscal
quarters. Regions
product
Reg 1 Reg 2 Reg 3
P1
P2
P3
p4
Fig:-Data Cube
CONT……….
Changing from one dimensional hierarchy to
another is early accomplished in data cube by a
technique called rotation.
STAR SCHEMA:-
 It is the simplest form of data warehousing
schema.
 It consists one large central table (fact) containing
the bulk of data and a set of smaller dimension
tables one for each dimension .
 Its entity relationship diagram between
dimensions and fact table resembles a star where
one fact table is connected to multiple dimensions
or table.
EXAMPLE OF STAR SCHEMA:-
SNOW FLAKE SCHEMA:-
 It is difficult from a star schema .
 In this dimensional table are organized into
hierarchy by normalization them.
 The Snow Flake Schema is represented by
centralized fact table which are connected to
multiple dimensions.
EXAMPLE OF SNOW FLAKE SCHEMA:-
FACT CONSTELLATIONS:-
 It is a set of fact tables that shares some
dimensional tables.
 It limits the possible queries for the data
warehouse.
THANK U……..
ANY QUERIES
?

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Multidimensional data models

  • 2. INDEX:- 1. Definition of Multidimensional Data Models? 2. Types of MDDM:- a. Star Schema b. Data Cube Schema c. Snowflake Schema d. Fact Constellation schema (Global Schema)
  • 3. MULTIDIMENSIONAL DATA MODEL:-  The MDDM was developed for implementing data warehouse and data marts.  MDDM provide both a mechanism to store data and a way for business analysis.
  • 4. TYPES OF MDDM:- A. Data Cube Model. B. Star Schema Model C. Snow Flake Schema Model D. Fact Constellations Schema Model (Global Schema)
  • 5. DATA CUBE MODEL:-  When data is grouped or combined together in multidimensional matrices called Data Cubes.  In 2 Dimension:- row & column or products.  In 3 Dimension:- one regions, products and fiscal quarters. Regions product Reg 1 Reg 2 Reg 3 P1 P2 P3 p4 Fig:-Data Cube
  • 6. CONT………. Changing from one dimensional hierarchy to another is early accomplished in data cube by a technique called rotation.
  • 7. STAR SCHEMA:-  It is the simplest form of data warehousing schema.  It consists one large central table (fact) containing the bulk of data and a set of smaller dimension tables one for each dimension .  Its entity relationship diagram between dimensions and fact table resembles a star where one fact table is connected to multiple dimensions or table.
  • 8. EXAMPLE OF STAR SCHEMA:-
  • 9. SNOW FLAKE SCHEMA:-  It is difficult from a star schema .  In this dimensional table are organized into hierarchy by normalization them.  The Snow Flake Schema is represented by centralized fact table which are connected to multiple dimensions.
  • 10. EXAMPLE OF SNOW FLAKE SCHEMA:-
  • 11. FACT CONSTELLATIONS:-  It is a set of fact tables that shares some dimensional tables.  It limits the possible queries for the data warehouse.
  • 12.