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
Traditional File Environment
Issues: Data Redundancy Data Inconsistency Data Isolation Data Integrity Security Application / Data Dependence
Database Approach
Minimal data redundancy Data consistency Integration of data Sharing of data Uniform security, privacy and
integrity Data independence
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
Relational Database
• Represents data as two-dimensional tables called relations
• Relates data across tables based on common data element
• Examples: DB2, Oracle, MS SQL Server
Hierarchical Database
• Organizes data in a tree-like structure
• Supports one-to-many parent-child relationships
• Prevalent in large legacy systems
Network Database
Depicts data logically as many-to-many relationships
Less flexible compared to RDBMS
Lack support for ad-hoc and English language-like queries
Database Design
Conceptual / Logical Design –
Abstract model of database from
business perspective.
Physical Design – shows how the
database is arranged on storage
devices.
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 decision-making tasks.
Data Marts
Data mart - a subset of a data warehouse in which only a focused portion of the data warehouse information is kept.
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