Dw concepts

Data Warehouse

Concepts
&
Architecture

© Principle Partners, Inc.
Info@PrinciplePartners.Com
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Data Warehouse Concepts

Topics To Be Discussed:

• Why Do We Need A Data Warehouse ?

• The Goal Of A Data Warehouse ?

• What Exactly Is A Data Warehouse ?

• Comparison Of A Data Warehouse And
An Operational Data Store.

• Data Warehouse Trends.

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Why Do We Need A Data Warehouse ?

We Can Only
See - What We
Can See !

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Why Do We Need A Data Warehouse ?

BETTER !
FASTER ! FUNCTIONALLY COMPLETE !
CHEAPER !

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Data Warehouse Development Perspective

Data Driven Vs. Function Driven

A/P
O/P
Order
Processing
Data
EIS
Data
DSS

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What Do We Need To Do ?

Use Operational Legacy Systems’ Data:
To Build Operational Data Store,
That Integrate Into Corporate Data Warehouse,
That Spin-off Data Marts.

Some May Tell You To Develop These In Reverse!

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Our Goal for A Data Warehouse ?

• Collect Data-Scrub, Integrate & Make It Accessible

• Provide Information - For Our Businesses

• Start Managing Knowledge

• So Our Business Partners Will Gain Wisdom !

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Data Warehouse Definition
A Data Warehouse Is A Structured Repository
of Historic Data.

It Is Developed in an Evolutionary Process
By Integrating Data From Non-integrated
Legacy Systems.

It Is Usually:
• Subject Oriented
• Integrated
• Time Variant
• Non-volatile

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Subject Oriented
Data is Integrated and Loaded by Subject

Cust 1996

1996
Prod D/W
Data
1997

O/P
1998

A/R

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Time Variant

Operational System Data Warehouse

• View of The Business • Designated Time Frame
Today (3 - 10 Years)

• Operational Time Frame • One Snapshot Per Cycle

• Key Need Not Have Date • Key Includes Date

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Integrated

Operational Systems

Order Processing Order ID = 10
D/W
Accounts Receivable Order ID = 12
Order ID = 16
Product Management Order ID = 8

HR System Sex = M/F
D/W
Payroll Sex = 1/2
Sex = M/F
Product Management Sex = 0/1

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Non-Volatile

Operational System Data Warehouse

• “CRUD” Actions • No Data Update

Insert
Read
Load
Create
Read Read

Update Replace Read

Delete Read

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Data Warehouse Environment Architecture
Contains Integrated Data From Multiple Legacy Applications

Update
A/P
Insert Data
Load Mart
O/P
Integration Read
ODS
Replace
Pay Data
Criteria Mart
All Or Part Delete
Mktg Of System of
Record Data

HR Data
Mart
A/R D/W Load Loads

Best System of Read D/W
Record Data

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Meta Data - Map of Integration
The Data That Provides the “Card Catalogue” Of
References For All Data Within The Data Warehouse

System of Record
Data Source

D/W Structure
Source Data Structure

Definition

Allowable
Domains Aliases

Data Relationships

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ODS Vs. Data Warehouse

Operational Data Store Data Warehouse

Characteristics: Data Focused Integration Subject Oriented
From Transaction Processing Integrated
Focused Systems Non-Volatile
Time Variant
Age Of The Data: Current, Near Term Historic
(Today, Last W eek’s) (Last M onth, Qtrly, Five
Years)
Primary Use: Day-To-Day Decisions Long-Term Decisions
Tactical Reporting Strategic Reporting
Current Operational Results Trend Detection
Frequency Of Load: Twice Daily , Daily, W eekly W eekly, M onthly, Quarterly

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Building The Data Warehouse

Tasks Deliverables

• Define Project Scope • Scope Definition
• Define Business Reqmts • Logical Data Model
• Define System of Record • Physical Database Data
Data Model
• Define Operational Data • Operational Data Store
Store Reqmts Model
• Map SOR to ODS • ODS Map
• Acquire / Develop • Extract Tools and
Extract Tools Software
• Extract Data & Load ODS • Populated ODS

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Building The Data Warehouse
(Continued)

Tasks Deliverables

• Define D/W Data Reqmts • Transition Data Model
• Map ODS to D/W • D/W Data Integration Map
• Document Missing Data • To Do Project List
• Develop D/W DB Design • D/W Database Design
• Extract and Integrate D/W • Integrated D/W Data
Data Extracts
• Load Data Warehouse • Initial Data Load
• Maintain Data Warehouse • On-going Data Access
and Subsequent Loads

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Relationship Among Data Warehouse Data Models

Business Business
Partner Business Requirements Requirements

Knowledge Logical
& Wisdom Model
Data
Warehouse Strategic
Validation Business
Physical
Structured
of Current Requirements
Model Requirements
Data

Operational
Data Store
Physical Tactical Business
Data Model Reqmts & Structures
Load

Current Data Whse
Database Requirements
Current Structure
Physical Transition
Model Model

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Sources of Data Warehouse Data

Archives
(Historic Data)

Current Systems
of Record
(Recent History)

Enterprise
Data Warehouse
Operational
Transactions
(Future Data Source)

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Appropriate Uses of Data Warehouse Data

• Produce Reports For Long Term Trend Analysis

• Produce Reports Aggregating Enterprise Data

• Produce Reports of Multiple Dimensions
(Earned revenue by month by product by branch)

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Inappropriate Uses of Data Warehouse Data

• Replace Operational Systems

• Replace Operational Systems’ Reports

• Analyze Current Operational Results

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Levels of Granularity of Data Warehouse Data

•Atomic (Transaction)

•Lightly Summarized

•Highly Summarized

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Options for Viewing Data

• Text

9 0
8 0
7 0
6 0

•
5 0
4 0
3 0
2 0
1 0
0
1 s t 2 n d 3 rd 4 th
Q tr Q tr Q tr Q tr

•

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Next Steps In Data Warehouse Evolution

• Use It - Analyze Data Warehouse Data

• Determine Additional Data Requirements

• Define Sources For Additional Data

• Add New Data (Subject Areas) to
Data Warehouse

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Future Trends In Data Warehouse

• Increased Data Mining
Exploration
Prove Hypothesis

• Increase Competitive Advantage
(i.e., Identify Cross-selling Opportunities)

• Integration into Supply Chain & e-Business

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Summary

A Data Warehouse Is A Structured Repository
of Historic Data.

It Is: • Subject Oriented
• Integrated
• Time Variant
• Non-volatile
It Contains:
• Business Specified Data,
To Answer Business Questions

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Questions and Answers

Page 27
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