Download Data Modeling

http://singadji.web.id/files/materikuliah/PSI/
Pengantar Sistem Informasi
Marcello Singadji, S.Kom, M.T
[email protected]
[email protected]
[email protected]
Learning Objectives
• Define general data management concepts and terms,
highlighting the advantages and disadvantages of the database
approach to data management.
• Name three database models and outline their basic features,
advantages, and disadvantages.
• Identify the common functions performed by all database
management systems and identify three popular end-user
database management systems.
• Identify and briefly discuss recent database applications.
The Hierarchy of Data
Date entries, attributes & keys
• Entity: Generalized class of people,
places, systems for which data is
collected. (Ex. Employees, customers)
• Attribute: Characteristic of an entity
(Ex. First name, last name)
• Key: A set of fields used to identify an
entity
• Primary Key: A key that uniquely
identified the entity
Keys and Attributes
The Traditional Approach To
Data Management
• Create new
files for each
application
• Data
redundancy
• Data integrity
The Database Approach to
Data Management
Advantages of the
Database Approach (1)
• Improved strategic use of corporate date
• Accurate information always available
• Reduced data redundancy
• Data is stored in one place
• Improved data integrity
• Changes are reflected throughout
• Easier modification and update
• No need to know where the data is
• Data and program independence
• Accurate information always available
Advantages of the
Database Approach (2)
• Better access to data and information
• Simple instructions to access data
• Standardization of data access
• Each DBMS uses the same set of instructions
• Standardization for programmers
• Should only know how to access the DBMS
• Better protection of data
• Require authorization on the data
• Shared data resources
• Setup the database once
• Several applications can use it
Disadvantages of the
Database Approach
• Costly
• Specialized DBMS software
• Specialized DBMS administrators and operators
• Increased vulnerability
• Single point of failure
• Targets for attacks
Data Modeling
• Planned data redundancy
• To have it available in more than one place
• To improve system performance
• Data model
• A diagram of entities and their relationships
• Enterprise data modeling
• Done at the level of enterprise
• Entity-relationship diagrams
• Use graphs to show how data is organized and how
it is related
Entity-Relationship Diagram
for a Customer Ordering Database
Entity
Relationship
(one-to-many)
Relationship
(many-to-one)
Relationship
(one-to-one)
Database Models
• Hierarchical (tree)
• Data is organized top-down
• Network
• Owner-membership relationship
• A member can have many owners
• Relational
• Uses tabular format with 2-dimensional tables
(relations)
• Relations resemble files
Hierarchical Database Model
Network Database Model
Relational Database Model
Project table
Manager table
Department table
Relational Models
• Describe data using a standard tabular format with all
data elements placed in two-dimensional tables, called
relations, that are the logical equivalent of files.
• Rows represent data entity
• Columns represent attributes
Providing a User View
• Schema - a description of the entire database
• First create a schema, then create the tables
• 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
• A sales representative has to see the data for her office, not the
company stock data
The Use of Schemas and
Subschemas
Data Access
• Concurrency control: Lock the record so that only one
application can access it at a time
• Data manipulation language (DML)
• Structured Query Language (SQL)
• SELECT * FROM Project
WHERE Project_number=“155”
• UPDATE Project
SET Project_number=“156”
WHERE Project_number=“155”
Structured Query Language
Database Output
Popular Database
Management Systems
•
•
•
•
•
•
Oracle
MySQL
Paradox database
FileMaker Pro
Microsoft Access
Lotus 1-2-3 Spreadsheet
Selecting a Database
Management System (1)
• Database size: Number of records in the database
• Number of concurrent users: People or applications that
will access it at the same time
• Performance: How fast can the DBMS access or update
records?
• Integration: Which operating system can it run under?
• Features: Which security procedures or privacy policies
are in place?
• Vendor: Size and reputation of the vendor
• Cost: Initial cost, maintenance costs, hardware costs,
personnel costs
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.
• For small and medium size businesses
• Used mostly for decision support system
• Data Mining - an information analysis tool that involves
the automated discovery of patterns and relationships in
a data warehouse.
Elements of a Data Warehouse
Common Data Mining Applications
Common Data Mining Applications
• Branding and positioning of products
• Customer churn
• Which customers can switch to competitors?
• Direct marketing
• Who would respond to telemarketing?
• Fraud detection
• Predict transactions which are likely to be illegal
Common Data Mining Applications
• Market-based analysis
• Which products are bought at the same time (diaper,
beer, chips)
• Market segmentation
• Group users based on similarity of products that they
buy
• Trend analysis
• Analyze how variables change over time (e.g., sales)
Business Intelligence
• Gathering enough of the right information in a
timely manner and usable form.
• Competitive intelligence
• What others are doing
• Counterintelligence
• Define trade secret information
• Knowledge management
• Capture company’s collective expertise wherever it resides
• Record knowledge and share it
Object-Relational Database
Management System
• Stores the following types of data as objects:
•
•
•
•
•
audio
images
unstructured
text
spatial data
Spatial Technology
Summary
• Data - one of the most valuable resources a firm
possesses.
• Entity - a generalized class of objects for which data is
collected, stored, and maintained.
• Attribute - a characteristic of an entity.
• DBMS - a group of programs used as an interface
between a database and application programs.
• Data mining - the automated discovery of patterns and
relationships in a data warehouse.
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