Download Module 1: Introduction to Data Warehousing

DW-1: Introduction to
Data Warehousing
Overview

What is Database

What Is Data Warehousing

Data Marts and Data Warehouses
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The Data Warehousing Process
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Data in a Data Warehouse
 What Is Database
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Before
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Now
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Program = Algorithm + Data Structure
Application (Weblication) = Visual I/F + SQL Query +
Database
Database is Integrated Data


from multiple file system data for OLTP
Data Base (From Air Base?), DB, 데이타베이스,
자료기지(북한)
Database and Data Model
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Computer Representation of Data for efficient
understanding and processing
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Data Model based on Relationship modeling
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Relationship between record
one-to-one(1:1), one-to-many(1:N), many-to-many(N:M)
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Hierarhical Model: Hierarchical Relationship, 1:N
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Network model: Network like relationship, N:M
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Relational Model: Use relation (table) for Relationship
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Object-Oriented data model: Complex object modeling
SET type, Reference, List
 What Is Data Warehousing
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Defining Data Warehousing
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Operational Systems: A Transactional Solution
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Analytical Systems: A Data Warehousing Solution
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Comparing Transactional and Data Warehousing
Solutions
Defining Data Warehousing
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Business Intelligence
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Database Marketing: Personalized Product
Especially S/W, Cocoon business etc.
Electronic Commerce
Data Warehouse: 자료 창고
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for OLAP, Data Mining, DSS
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Knowledge Management
Data Warehousing: Process to build Data Warehouse
Defining Data Warehousing
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A Data Warehouse Is a Database That Contains:
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Enterprise data
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Integrated sets of historical data
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Subject-oriented, consolidated, consistent data
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Data structured for distribution and querying
A Data Warehousing Solution Is a Process That:
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Retrieves and transforms data
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Manages the database
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Uses tools for building and managing the data warehouse
Operational Systems: A Transactional Solution
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Track Individual Events
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Used for Real-time Data Entry and Editing
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Examples:
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Order-tracking applications
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Customer service applications
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Point-of-sale applications
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Service-based sales applications
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Banking functions
Analytical Systems: A Data Warehousing Solution
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Assist with Strategic Decision Support
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Provide Different Levels of Analysis
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Allow Users to Navigate to Different Levels of Data
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Allow System Searches to Find New Relationships
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Examples:
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Spreadsheet-based applications
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Sales forecasting applications
Comparing Transactional and Data Warehousing
Solutions
Transactional
solutions
Data warehousing
solutions
Update frequency Real-time
Periodically
Structured for
Data integrity
Ease in querying
Optimized for
Transaction performance
Query performance
 Data Marts and Data Warehouses
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What Is a Data Mart
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Moving Data from a Data Warehouse to Data Marts
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Moving Data from Data Marts to a Data Warehouse
What Is a Data Mart
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What Is a Data Mart
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A subset of a data warehouse
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Used in an enterprise
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Specific to a particular subject or business activity
Why Build Data Marts
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Faster queries and fewer users
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Faster deployment time
Integrated Data Marts
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Ensure consistent data
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Require advance planning
Moving Data From a Data Warehouse to Data Marts
Sales Mart
Source 1
Source 2
Data
Warehouse
Source 3
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Advantages
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Shared fields
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Common source
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Distributed processing
Disadvantages

Longer time to develop
Financial Mart
Customer
Service Mart
Moving Data from Data Marts to a Data Warehouse
Source 1
Sales Mart
Source 2
Financial Mart
Source 3
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Advantages
Customer Service
Mart
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Simpler and faster to implement
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Department-specific data
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Smaller hardware requirements
Disadvantages
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Data duplication
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Incompatible data marts
Data
Warehouse
The Data Warehousing Process
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Basic Elements of the Process
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Tools to Manage the Process
Basic Elements of the Process
Source OLTP
Systems
Data Marts
Clients
Data
Warehouse
1
Retrieve Data
2 Transform Data
3
Populate
Data Warehouse
4
Populate
Data Marts
5
Query
the Data
Tools to Manage the Process
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SQL Server
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Data Transformation Services
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SQL Server OLAP Services
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Microsoft Repository
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Microsoft English Query
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PivotTable Service
ETL process
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Extraction, Transformation, Loading
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Extraction: 추출
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Transformation: 변환
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Data modification, sorting, calculation etc
Loading: 적재
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Data retrieval from existing data source such as File,
Table etc.
Bulk, incremental loading from operational DB
Time consuming process: may use special H/W
Data in a Data Warehouse
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Data Characteristics
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Example of Organizing Data
Data Characteristics
Data characteristic
Description
Consolidated
Enterprise-wide
Consistent
Within the data warehouse
Subject-oriented
Organized to user perspective
Historical
Snapshots over time
Read-only
Cannot update
Summarized
To appropriate level of detail
Example of Organizing Data
Monthly Southeast Regional Sales Report - May 1999
State
City
Units Sold
Sales $
FL
Miami
2,500
$12,850
FL
Tampa
2,750
$14,135
5,250
$26,985
FL Totals
GA
Atlanta
3,200
$16,800
GA
Savannah
1,725
$ 9,143
4,925
$25,943
1,900
$ 9,595
1,900
$ 9,595
12,075
$62,473
GA Totals
SC
Columbia
SC Totals
Southeast Region
Total
Data Warehouse Schema Example: Star schema
A Example of Cube Browsing
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1 Fact with 4 Dimension Table
-- Sales_Fact, Product, Store, Time, Customer
Drilling Down
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Drilling Down to products
Drilling Down
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Drilling Down to the lowest level of Customer Dimension
Rolling up
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Rolling up
Review

What Is Data Warehousing

Data Marts and Data Warehouses

The Data Warehousing Process

Data in a Data Warehouse
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Data Warehouse will be more popular than DB?