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Transcript
Intro to MIS – MGS351
Databases and
Data Warehouses
Chapter 3
Chapter Overview

Data Hierarchy

Traditional File Environment

Databases
–
Relational, Hierarchical, Network

Design and Normalization

Data Warehousing
Data Hierarchy

Database

Table, File, Relation

Records, Rows, Tuples

Fields, Columns, Attributes

Bytes

Bits
Data Hierarchy
Figure 7-1
Traditional File Environment
Issues:
Data Redundancy
Data Inconsistency
Data Isolation
Data Integrity
Security
Application / Data Dependence






Traditional File Processing
Figure 7-3
Database Approach






Minimal data redundancy
Data consistency
Integration of data
Sharing of data
Uniform security, privacy and
integrity
Data independence
Database Environment
Figure 7-4
DBMS Components
• Data definition language: Specifies
content and structure of database and
defines each data element
• Data manipulation language:
Manipulates data in a database
• Data dictionary: Stores definitions of
data elements, and data characteristics
Evolution of Databases
Relational Database
• Represents data as twodimensional tables called relations
• Relates data across tables based
on common data element
• Examples: DB2, Oracle, MS SQL
Server
Relational Database
Figure 7-6
Hierarchical Database
• Organizes data in a tree-like
structure
• Supports one-to-many parent-child
relationships
• Prevalent in large legacy systems
Hierarchical Database
Figure 7-8
Network Database



Depicts data logically as many-tomany relationships
Less flexible compared to RDBMS
Lack support for ad-hoc and
English language-like queries
Network Database
Figure 7-9
Database Design


Conceptual / Logical Design –
Abstract model of database from
business perspective.
Physical Design – shows how the
database is arranged on storage
devices.
ER Diagram
Figure 7-10
Business Intelligence

Knowledge about your:
– Customers
– Competitors
– Partners
– Competitive environment
– Internal operations
Business Intelligence
Business Intelligence
o Online transaction processing (OLTP) - the
gathering of input information, processing that
information, and updating existing information
to reflect the gathered and processed
information.
o Operational databases - databases that support
OLTP.
o Online analytical processing (OLAP) - the
manipulation of information to support
decision making.
Data Warehousing

Multidimensional Data Models

OLAP


Data Marts – subset of data
warehouse
Data Mining – finding hidden
patterns and trends in data
Data Warehousing

Data warehouse - a logical
collection of information gathered
from many different operational
databases (Extract, Transform,
Load) used to create business
intelligence that supports business
analysis activities and decisionmaking tasks.
Data Warehouse
Multidimensional Data Model
Figure 7-15
Data Marts

Data mart - a
subset of a
data
warehouse in
which only a
focused portion
of the data
warehouse
information is
kept.
Data Mining Tools
Distributed Databases
Figure 7-13
Databases and the Web
Figure 7-18