This document discusses database management and design. It explains the advantages of the database approach over traditional file-based data management, including supporting decision making and yielding business benefits. The database approach involves data modeling with entity-relationship diagrams and using relational databases with standardized tables. Database management systems provide user views of data through schemas and subschemas, and allow data creation and modification with definition languages and dictionaries. Structured query language is used for data storage, retrieval, and applications. Data warehouses, marts and mining are discussed for business intelligence gathering.

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Organizing Data and
Information

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Principles and Learning Objectives
• The database approach to data
management provides significant
advantages over the traditional file-based
approach.

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Principles and Learning Objectives
• A well-designed and well-managed database is
an extremely valuable tool in supporting decision
making.

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Principles and Learning Objectives
• Further improvements in the use of database
technology will continue to evolve and yield real
business benefits.

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The Traditional Approach To Data
Management

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The Database Approach to Data
Management

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Advantages of the Database Approach

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Disadvantages of the Database Approach

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Data Modeling
• Entity-relationship diagrams

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Entity-Relationship Diagram for a
Customer Ordering Database

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Relational Database Model

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Relational Models
Describe data using a standard tabular format with all
data elements placed in two-dimensional tables, called
relations.
– Domain
– Selecting
– Projecting
– Joining

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Linking Database Tables
to Answer an Inquiry

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Database Management
Systems

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Providing a User View
• Schema - a description of the entire database
• Subschema - a file that contains a description
of a subset of the database and identifies which
users can modify the data items in that subset

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The Use of Schemas and Subschemas

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Creating and Modifying the Database
• Data definition language (DDL) - a collection of
instructions and commands used to define and
describe data and data relationships in a specific
database
• Data dictionary – detailed description of data in
a database

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Typical Uses of a Data Dictionary
• Provide a standard definition of terms and data elements
• Assist programmers in designing and writing programs
• Simplify database modification
• Reduce data redundancy
• Increase data reliability
• Speed program development
• Ease modification of data and information

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Storing and Retrieving Data

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Structured Query Language

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Database Output

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Database Applications

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Data Warehouses, Data Marts,
and Data Mining
• Data Warehouse - a database that collects business
information from many sources in the enterprise,
covering all aspects of the company’s processes,
products, and customers.
• Data Mart – a subset of a data warehouse.
• Data Mining - an information analysis tool that involves
the automated discovery of patterns and relationships in
a data warehouse.

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Elements of a Data Warehouse

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Common Data Mining Applications

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Business Intelligence
Gathering enough of the right information in a
timely manner and usable form.
– Competitive intelligence
– Counterintelligence
– Knowledge management

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Comparison of OLAP and Data Mining