Building the Data WareHouse http://it-slideshares.blogspot.com

1. Building Data WareHouse by
Inmon
Chapter 13: The Relational and the Multidimensional
Model as a Basis for Database Design
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2. Contents
The Relational Model
The Multidimensional Model
Snowflake Structures
Differences between the Models
Independent Data Marts
Building Independent Data Marts
Summary

3. The Relational Model
 Organize data into a table
 Normalization of data implies that the database design
has caused the data to be broken down into a very low
level of granularity

4. The Multidimensional Model
 Sometimes
called the star join approach
 Components:
◦ A fact table is a structure that contains many occurrences of
data.
◦ Dimensions table, which describe one important aspect of the
fact table

5. Snowflake Structures
 More than one fact table can be combined in a database
design to create a composite structure called a
snowflake structure
 Advantage of the multidimensional design is its
efficiency of access

6. Differences between the Models
The Roots of the Differences
◦ The relational model is shaped from a data
model.
◦ A star join is shaped from user requirements.

7. Differences between the Models
Reshaping Relational Data
◦ The base data in the relational model can be
shaped and reshaped in as many ways as
desired

8. Differences between the Models
Indirect Access and Direct Access of
Data
◦ The relational model is good for indirect
access of data
◦ The multidimensional model is good for
direct access of data

9. Differences between the Models
Servicing Future Unknown Needs
◦ The granular data in the relational model is
used to service unknown future needs for
information

10. Differences between the Models
Servicing the Need to Change Gracefully
◦ Another advantage of the relational model as
a basis for the data warehouse—the ability to
change gracefully
◦ The impact of change is minimal

11. Differences between the Models
Servicing
the Need to
Change Gracefully
◦ The relational model forms an
ideal basis for the data
warehouse, while the star join
forms the ideal basis for the
data mart.

12. Independent Data Marts
Data Marts
◦ A data mart is a data structure that is
dedicated to serving the analytical needs of
one group of people
◦ The independent data mart is a data mart that
is built directly from the legacy applications

13. Independent Data Marts
Data Marts
◦ A dependent data mart is one that is built from
data coming from the data warehouse
◦ The dependent data mart requires multiple
users to pool their information needs for the
creation of the data warehouse

14. Building Independent Data Marts
Problem with building independent data marts

◦ Do not provide a platform for reusability
◦ Do not provide a basis for reconciliation of data
◦ Do not provide a basis for a single set of legacy interface
programs
◦ Do require that every independent data mart create its own
pool of detailed data, which is, unfortunately, massively
redundant with the pools of detailed data created by other
independent data marts

15. Building Independent Data Marts
With dependent data marts, all problems of

independent data marts are solved

16. Summary
 Basic models that are used for database design for the
data warehouse: the relational model and the
multidimensional (star join) model
 The relational model is ideal for serving indirect access
to the data warehouse, while the multidimensional
model is ideal for serving the needs of the direct use of
the data warehouse.
 Dependent data marts that take data from a data
warehouse do not have to have the same set of
architectural problems (like independent data marts).
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