DATABASE MANAGEMENT SYSTEMS (DBMS) by Prof. Kudang B. Seminar, MSc, PhD e-mail:
[email protected]
Database sebagai Komponen Vital Sistem Informasi
Performance Control System
Data
Process
Info
Data Store N E T WAR E
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Data vs Information Data: raw facts or observations Information : data that have been
transformed into a meaningful and useful context for specific end users Data
Information
Data Sales person Sales Values Sales Units
Data Processing
Sales Analysis
Sample Business Application
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Sample Tabular View of Sales
Sample Pivot Chart for Sale Analysis
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Akusisi Data Geografis
Data Geografis Yang Tersimpan
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Produk Informasi Geografis
Basis Data (Database) Koleksi terpadu dari data-data yang saling berkaitan yang dirancang untuk suatu enterprise. Data Alumni Data Dosen
Data Mhs
Data Mkul
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Analisis Kebutuhan Data (Data Requirement Analyisis) • Think and conceptualize business objects and logic • Identify information needed -> then what data are needed • Formulate what computer applications are needed?
Kasus Contoh: Data Requirement Analysis Forward Support Analysis Sources of Data
Supporting Data
Supporting Information
Management Objectives
Management Functions
Backward Requirement Analysis • BAAK
• KRS
• Academic Progress
• Monitoring Student Progress …
• Monitoring
• Faculty
• Transkrip
• Treated Students
• Directing Student Research …
• Directing
• Dept.
• Supervisi
• Student Potentials
• Planning for Remedial Efforts .
• Planning
• Study Program
• Research List
• Academic Problem
• Acting on Remedial Plan …
• Acting
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Contoh Kasus: Analisis Kebutuhan Data Mhs Data
Info
KRS, Transkrip
IPK Kumulatif
Status Akademik Mhs
Warning 1, 2, 3, rekomendasi
D.O or Extended
Minat riset & PTA mhs, Data PTA
Profile minat riset & PTA mhs, Beban PTA
Analisis minat riset & PTA mhs
Alokasi PTA utk mhs
Alokasi final PTA utk mhs
Catatan riset mhs, Trankrip, KRS.
Kemajuan riset mhs
Status Akademik Mhs
Rekomendasi perlakuan
Eksekusi perlakuan
Catatan riset mhs, Trankrip, KRS
Profile kelulusan mhs: lama studi & prestasi akad.
Analisis kelulusan: rerata lama studi, ranking akademik
Rekomendasi program akselerasi studi
Eksekusi akselerasi studi
Data= Info= Data1..n Info1..n
Monitoring
Directing
Acting
Management Functions = Monitoring Directing Acting Mencapai Target Academic Excellence?
Utilisasi Vs Ketersedian Informasi • • • •
Ada dan Diperlukan Tak ada dan Diperlukan Ada dan Tak Diperlukan Tak Ada dan Tak Diperlukan Perlu
Ada
Tak Ada
Tak Perlu
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Data Acquisition & Information Production
Database Management Systems (DBMS) Koleksi terpadu dari sekumpulan program (utilitas) yang digunakan untuk mengakses dan merawat database
Users DBMS Utilitas
Database
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Application Programs on Top of DBMS Users Application programs
DBMS
Database
Eksplorasi Database
Tim Pengembangan Master Plan
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Keuntungan DBMS • Data menjadi shareable resources bagi berbagai user dan aplikasi • Metoda akses, penggunaan, dan perawatan data menjadi seragam dan konsisten • Pengulangan (redundancy) data dan kemajemukan struktur data diminimisasikan • Ketaktergantungan data terhadap program aplikasi (data independence) • Hubungan/relasi logik (logical relationship) antar data terpelihara secara sistematik.
Conventional Data Management Application
Application
• Data belongs to a certain application programs ; therefore it is difficult to share data among application programs • Data lifetime is limited (dependent ) to application program lifetime. • Data redundancy and inconsistency will likely occur • Non-uniform access method, data usage and maintenance. • Incompatibility of data among application programs
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Examples of software tools in DBMS • Designing : ERD (Entity Relationship Diagram), DDL (Data Definition Language) • Inputing & Manipulating: DML (Data Modification Language), QL (Query Language), Multimedia processor • Searching & Retrieving: QL (Query Language): SQL * QBE • Converting & Squeezing: Encoder & Decoder, Data Converter & Squeezer, Multimedia processor
• Optimizing : Data Organizer & Analyzer • Calculating: Math & statistical functions • Presenting: Report Generator, Multimedia Processor
DBMS Approach Enables Resource Sharing Among Applications and Users Multiple Systems
Shareable Resources
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Data Management Life Cycle • Need of changes Real World
• Observing • Identifying
• Updating • Monitoring • Protecting • Browsing
• Conceptualizing • Representing • Structuring
• Analyzing • Optimizing
• Coding
Data Modeling: Methods & Tools
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Why Modeling? Order
“Modeling captures essential
parts of the system.” Dr. James Rumbaugh
Item
Ship via
Business Process Visual Modeling is modeling using standard graphical notations: chart, diagrams, objects, symbols Copyright © 1997 by Rational Software Corporation
Data Model Definition: Integrated collection of concepts, theories, axioms, constraints for description, organization, validation, and interpretation of data.
Usage: a fundamental set of tools & methods to consistently & uniformly view, organize, and treat database .
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Types Data Models Record-Based Model
Relational Hierarchical Network
Object-Based Model
Entity-relationship Semantic Functional Object Oriented
Steps of Designing DBMS
• Determine what to store • Determine what relations exists • Determine what data services are needed
• Determine what data model is suitable
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Data Warehouse Kudang B. Seminar
What is Data warehouse? • Data warehouse as a subject- oriented,
•
integrated, time variant, non-volatile collection of data in support of management’s decision making process Data warehouse systems consist of a set of programs that extract data from the operational environment, a database that maintains data warehouse data, and systems that provide data to users
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The Goal of Data Ware House?
• to provide a "single image of business reality" for the organization
Fundamental Ideas Behind the Successful Data Warehousing • Operational vs. Decision Support Applications: One impetus for • • • •
data warehouse is the unsuitability of traditional operational applications for typical decision support usage patterns; Primitive vs. Derived Data: A critical success factor in data warehouse design is understanding knowledge workers’ demand demand for detailed vs. summary data; Time Series Data: Data warehouse often supports analysis of trends over time and comparisons of current vs. historical data; Data Administration: Another critical success factor is senior management commitment to maintenance of the quality of corporate data Systems Architecture: A system must be architected when it is very complex, requires the integration of many disciplines, or is developed in the face of uncertain requirements.
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Alignment of data warehouse entities with the business structure
Corporate Data for Warehouses
A corporate data warehouse is a
process by which related data from many operational systems is merged to provide a single, integrated business information view that spans all business divisions.
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