Data Warehouse and Business Intelligence

1. DATA WAREHOUSE
KIMBALL OR INMON
Understanding different approach

2. Understand the basics of 2 approaches
Enterprise Data Warehouse
Dimensional Modelling and Design
Understand the Similarities and Differences

3.  In 1990 Inmon wrote a book “Building the Data Warehouse”
 Inmon defines architecture for collection of disparate sources
into detailed, time variant data store( The top down approach)
 In 1996 Kimball wrote “The Data Warehouse Toolkit”
 Kimball updates book and defines multiple databases called
data-marts that are organized by business processes, but use
Data bus architecture (The bottom-up approach)

4.  A Data warehouse is a collection of Enterprise wide data across line of business
and subject areas
 Data is integrated using a massive database
 Provides complete organizational view of the information needed to run
the business
 A Data mart provides departmental view of information specific and subject
oriented
 Build multiple data-marts using dimensional architecture
 Provides Fact based information integrated with multiple dimensions

5. Data Warehouse
Data Marts
Scope
• Application independent
• Centralized or Enterprise
• Planned
• Specific application
• Decentralized by group
• Organic but may be planned
Data
• Historical, detailed, summary
• Some de-normalization
• Some history, detailed, summary
• High de-normalization
Subjects
• Multiple subjects
• Single central subject area
Source
• Many internal and external sources
• Few internal and external sources
Pros & Cons
•
•
•
•
Flexible
Data oriented
Long life
Single complex structure
•
•
•
•
•
Restrictive
Project oriented
Short life
Multiple simple structures that may
form a complex structure

6.  Bill Inmon: A data warehouse is a subject-oriented and the data in the database is
organized with data elements relating and linking together.
 Time-variant: The changes to the data in the database are tracked and
recorded showing changes over time;
 Non-volatile: Data in the database is never over-written or deleted once committed, the data is static, read-only, but retained for future
Database: The database contains data from all operational applications,
and that this data is made consistent
 the data warehouse should be designed from the top-down to include all
corporate data. In this methodology, data marts are created only after the
complete data warehouse has been created.

7.  Ralph Kimball: A proponent of the dimensional modelling and approach to
building data warehouse through data marts.
 The data warehouse is nothing more than the union of all the data-marts,

Kimball indicates a bottom-up approach for data warehousing
 Individual data marts are created providing views into the organizational
data in chunks
 Eventually an Enterprise Data warehouse is create by combining the data
marts together using Bus architecture.

8. INMON
KIMBALL
The warehouse is a part of Corporate information
factory consists of all Data bases.
Fact and Dimensions using Dimensional modelling
Defines database environment as
Operational: Day to day operations
Atomic: Transaction captured
Departmental: Focused
Individual: Ad-hoc
Metrics or facts and Dimension with attributes
ERD refines entities, attributes and relationships
Bus architecture
Data Items sets and Data sets by department
Physical modelling to optimize performance by
de-normalizing
Does not adhere to normalization theory
Subject-Oriented, Integrated, Non-Volatile
Time-Variant, Top-Down, Enterprise Data Model
Characterizes Data marts as Aggregates
Business-Process-Oriented, Bottom-Up ,
Dimensional Model, Integration Achieved via
Conformed Dimensions, Star Model

9. DB2
Data warehouse
DW
DW
ORACLE
STAGING AREA
Flat files
CUBE
SAP
USER
ACCESS

10. DB2
Data warehouse
DW
ORACLE
STAGING AREA
Flat files
SAP
DW
CUBE
USER
ACCESS

11. REQUIREMENTS
INMON
KIMBALL
Organization requirements
Strategic
Tactical
Data Integration
Enterprise
Departmental
Structure
Non metric data, meets multiple
varied information needs
Business metrics , KPI’s, Scorecards
Scalability
Change of Scope and
requirements
Limited scope and volatile needs

12. REQUIREMENTS
INMON
KIMBALL
Data Stability
Source systems changes frequently Stable source systems
Staff requirement
Large
Small
Delivery
Slow and Long
Quick turnaround
Cost
Low upfront cost
High expenditure