MANAGING DATA RESOURCES

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MANAGING DATA RESOURCES

• pertemuan 7
• Oleh Ir. Abdul Hayat, MTI

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OBJECTIVES

• Why do businesses have trouble finding the
  information they need in their information
  systems?
• How does a database management system help
  businesses improve the organization of their
  information?
• How do the principal types of database models
  affect the way businesses can access and use
  information?
• What are the managerial and organizational
  requirements of a data-base environment?
• What new tools and technologies can make
  databases more accessible and useful?

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MANAGEMENT CHALLENGES

• Organizational obstacles to a database
  environment
• Integrating data and ensuring quality

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ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT

• File Organization Terms and Concepts
• Bit Smallest unit of data binary digit (0,1)
• Byte Group of bits that represents a single
  character
• Field Group of words or a complete number
• Record Group of related fields
• File Group of records of same type
• Database Group of related files
• Entity Person, place, thing, event about which
  information is maintained
• Attribute Description of a particular entity
• Key field Identifier field used to retrieve,
  update, sort a record

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ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT

• Data Hierarchy in a Computer System

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ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT

• Entities and Attributes

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ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT

• Problems with the Traditional File Environment
• Data redundancy
• Program-Data dependence
• Lack of flexibility
• Poor security
• Lack of data-sharing and availability

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ORGANIZING DATA IN A TRADITIONAL FILE ENVIRONMENT

• Traditional File Processing

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THE DATABASE APPROACH TO DATA MANAGEMENT

• Database Management System (DBMS)
• The contemporary database environment
• Components of DBMS
• Sample Data Dictionary report
• Types of databases
• Relational DBMS
• Relational Data Model
• Basic Operations in a Relational Database
• Hierarchical and Network DBMS

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DATABASE MANAGEMENT SYSTEM (DBMS)

• Creates and maintains databases
• Eliminates requirement for data definition
  statements
• Acts as interface between application programs
  and physical data files
• Separates logical and physical views of data

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THE CONTEMPORARY DATABASE ENVIRONMENT
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COMPONENTS OF DBMS

• 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

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SAMPLE DATA DICTIONARY REPORT
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TYPES OF DATABASES

• Relational DBMS
• Hierarchical and Network DBMS
• Object-Oriented Databases

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RELATIONAL DBMS

• Represents data as two-dimensional tables called
  relations
• Relates data across tables based on common data
  element
• Examples DB2, Oracle, MS SQL Server

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RELATIONAL DATA MODEL
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BASIC OPERATIONS IN A RELATIONAL DATABASE (1)

• Select
• Creates subset of rows that meet specific
  criteria
• Join
• Combines relational tables to provide users with
  information
• Project
• Enables users to create new tables containing
  only relevant information

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BASIC OPERATIONS IN A RELATIONAL DATABASE (2)
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HIERARCHICAL AND NETWORK DBMS

• Hierarchical DBMS
• Organizes data in a tree-like structure
• Supports one-to-many parent-child relationships
• Prevalent in large legacy systems
• Network DBMS
• Depicts data logically as many-to-many
  relationships

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HIERARCHICAL DBMS
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NETWORK DBMS
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DISADVANTAGES OF HIERARCHICAL AND NETWORK DBMS

• Outdated
• Less flexible compared to RDBMS
• Lack support for ad-hoc and English language-like
  queries

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OBJECT-ORIENTED DATABASE

• Object-oriented DBMS
• Stores data and procedures as objects that can be
  retrieved and shared automatically
• Object-relational DBMS
• Provides capabilities of both object-oriented and
  relational DBMS

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BASIC SQL COMMAND

• SELECT Specifies columns
• FROM Identifies tables or views
• WHERE Specifies conditions

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RESULTS OF SELECT STATEMENT
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RESULTS OF CONDITIONAL SELECTION
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PROJECTION FROM JOINING PART AND SUPPLIER TABLES
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DESIGNING DATABASES

• Conceptual design Abstract model of database
  from a business perspective
• Physical design Detailed description of business
  information needs
• Entity-relationship diagram Methodology for
  documenting databases illustrating relationships
  between database entities
• Normalization Process of creating small stable
  data structures from complex groups of data

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ENTITY-RELATIONSHIP DIAGRAM
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NORMALIZATION
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DISTRIBUTING DATABASES

• Centralized database
• Used by single central processor or multiple
  processors in client/server network
• Distributed database
• Stored in more than one physical location
• Partitioned database
• Duplicated database

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DISTRIBUTED DATABASES
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KEY ELEMENTS IN A DATABASE ENVIRONMENT

• Data Administration
• Data Planning and Modeling Methodology
• Database Technology and Management
• Users

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MANAGEMENT REQUIREMENTS FOR DATABASE SYSTEMS
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DATABASE TRENDS

• Data Warehousing and Data Mining
• Database and the web

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DATA WAREHOUSE

• Supports reporting and query tools
• Stores current and historical data
• Consolidates data for management analysis and
  decision making

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COMPONENTS OF DATA WAREHOUSE
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TYPICAL ARCHITECTURE OF DATA WAREHOUSE
Warehouse Manager
Operational Data source 1
Reporting, query, application development, and
EIS tools
Query Manager
Load Manager
Metadata
Operational Data source 2
Highly summarized data
OLAP tools
Lightly summarized data
Detailed data
Warehouse Manager
Operational Data source N
Data mining tools
End-user access tools
Operational Data store (ODS)
Archive/backup data
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DATA MART

• Subset of data warehouse
• Contains summarized or highly focused portion of
  data for a specified function or group of users

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TYPICAL ARCHITECTURE OF DATA MART
Reporting, query, application development, and
EIS tools
(First Tier)
Data Marts
OLAP tools
Summarized data (Relational Database)
Data mining tools
Summarized data (Multi-dimensional Database)
(Third Tier)
(Second Tier)
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DATA ACCESS AND ANALYSIS

• Queries and reports
• Online Analytical Processing (OLAP)
• Data Mining

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ON-LINE ANALYTICAL PROCESSING

• Multidimensional data analysis
• Supports manipulation and analysis of large
  volumes of data from multiple dimensions/perspecti
  ves

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MULTIDIMENSIONAL DATA MODEL
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DATA MINING

• Tools for analyzing large pools of data
• Find hidden patterns and infer rules to predict
  trends

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BENEFITS OF DATA WAREHOUSE

• Improved and easy accessibility to information
• Ability to model and remodel the data

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DATABASE AND THE WEB

• Hypermedia database
• Database server
• Application server
• Link internal databases to the web

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HYPERMEDIA DATABASE

• Organizes data as network of nodes
• Links nodes in pattern specified by user
• Supports text, graphic, sound, video and
  executable programs

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DATABASE AND APPLICATION SERVER

• Database server
• Computer in a client/server environment runs a
  DBMS to process SQL statements and perform
  database management tasks
• Application server
• Software handling all application operations

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LINK INTERNAL DATABASES TO THE WEB