Download Chapter 3

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
Traditional File Environment
Issues:
Data Redundancy
Data Inconsistency
Data Isolation
Data Integrity
Security
Application / Data Dependence






Traditional File Processing
Database Approach






Minimal data redundancy
Data consistency
Integration of data
Sharing of data
Uniform security, privacy and
integrity
Data independence
Database Environment
DBMS Components
• Data definition language (DDL):
Specifies content and structure of
database and defines each data
element (data type, length, properties)
• Data manipulation language (DML):
Manipulates data records 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, MySQL
Relational Database
Hierarchical Database
• Organizes data in a tree-like
structure
• Supports one-to-many parent-child
relationships
• Prevalent in large legacy systems
Hierarchical Database
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
Database Design


Conceptual / Logical Design –
Abstract model of database from
business perspective.
Physical Design – determines how
the database is arranged and
optimized on storage devices.
ER Diagram
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

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
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

Data Mining - Used to find hidden patterns
and previously unknown trends in data.
Databases and the Web