A short overview of the simplest style of data mart schema that can be used to construct data warehouses. It helps reduce the complexities in joining tables when presenting your data through reports and data visualizations.

1. MURUGAN PANDIAN
2 0 2 1
STAR SCHEMA OVERVIEW

2. 2
STAR SCHEMA INTRODUCTION
D e s i g n e d f o r A n s w e r i n g B u s i n e s s
Q u e s t i o n s
Design in relational databases for a data warehouse
system.
Data organized and structured to answer business
questions.
Modeled after a business process.
Greater insight.
Eliminate complex SQL.
Low maintenance.
Point a BI and analytics tool (Exago BI) at the data to
immediately ask questions.
2

3. 3
STAR SCHEMA OVERVIEW
D a t a D e s i g n P a t t e r n T h a t R e s e m b l e s a
S t a r
Contains fact and dimension tables.
Fact - subject of analysis.
• Numerical. Changing over time. Activity.
Dimension - the context of that analysis.
• Text. Descriptive.
One join away.
3
Fact
Dim
Dim Dim
Dim
Dim

4. DENORMALIZED VS NORMALIZED
DENORMALIZED NORMALIZED
 Human Oriented
 Redundancy
 Fast Query Processing
 Machine Oriented
 Less Redundancy
 Fast Transaction Processing
4

5. 5
DIMENSION MODELING
M o d e l i n g t h e B u s i n e s s P r o c e s s
Data organized and structured to answer business
questions.
What is the atomic grain of the process?
• Single row in fact table that represents a business
statement.
• Lowest level detail.
The business process is the activity performed by the
organization.
5

6. FACT TABLES
H e a r t o f S t a r S c h e m a
R e p r e s e n t B u s i n e s s P r o c e s s
C o n t a i n s c o m p o s i t e k e y s m a d e u p o f t h e
s u r r o g a t e k e y s f r o m t h e d i m e n s i o n t a b l e s .
S t o r e s f a c t s o r m e a s u r e o f i n t e r e s t s
Ty p i c a l l y, c o n t a i n n u m b e r s t h a t c a n b e
a g g r e g a t e d o r s u m m a r i z e d .
6

7. DIMENSION TABLES
P r o v i d e s c o n t e x t t o o u r b u s i n e s s p r o c e s s
a n d a n a l y s i s .
H e l p s a n s w e r q u e s t i o n s .
E n a b l e u s t o s l i c e a n d d i c e t h e a n a l y s i s .
C o n t a i n s s u r r o g a t e k e y s n o t d e p e n d e n t o n
s o u r c e s y s t e m s .
F l a g / I n d i c a t o r f i e l d s ( v e r s i o n ) .
7

8. 8
QUERYING STAR SCHEMA
O NE JO IN AWAY
Requires simple joins.
O NE DIME NS IO N
Start with fact table and join to a dimension table.
MULTIPLE DIME NS IO NS
Start with fact table and join to as many dimension tables.
8

9. S TA R S C H E M A – S A L E P R O C E S S

10. 10
BI DATA STRATEGY
DE TE R MINE DATA S O URCES
What data do you want for your reports and data visualizations?
E TL + DATA INEGR ATIO N
Determine and implement the processes that prepare your data
to be stored in a star schema.
BI A NA LYTICS TO O L
Connect your BI tool to your newly created data sources.
10

11. THANK YOU
M U R U G A N PA N D I A N + 1 ( 3 1 5 ) 5 7 2 - 2 4 8 3 m u r u ga n . p a n d i a n @ i c l o u d . c o m
W W W. M U R U G A N PA N D I A N .C O M