database management systems (dbms) by prof. kudang b. seminar, msc, phd e-mail: [email protected]
TRANSCRIPT
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DATABASE MANAGEMENT DATABASE MANAGEMENT SYSTEMS (DBMS)SYSTEMS (DBMS)
by
Prof. Kudang B. Seminar, MSc, PhD
e-mail: [email protected]
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Performance Control System
Data InfoProcessProcess
Data StoreData Store
BRAINWARE DATAWARE
HA
RD
WA
RE
SO
FTW
ARE
N E T W A R E
Database sebagai Komponen Vital Sistem Database sebagai Komponen Vital Sistem InformasiInformasi
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Data
ProcessingSales Analysis
Data Information
Data Sales person
Sales Values
Sales Units
Data vs InformationData vs Information
DataData: : raw facts or observationsraw facts or observations
InformationInformation : : data that have data that have been transformed into a been transformed into a meaningful and useful context meaningful and useful context for specific end usersfor specific end users
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Sample Business Application
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Sample Tabular View of Sales
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Sample Pivot Chart for Sale Analysis
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Akusisi Data Geografis
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Data Geografis Yang Tersimpan
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Produk Informasi Geografis
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Basis Data (Database)
Koleksi terpadu dari data-data yang saling berkaitan yang dirancang untuk suatu enterprise.
DataDataMhsMhs
Data Data DosenDosen
Data Data MkulMkul
Data Data AlumniAlumni
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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?
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Dokumentasikan hasil Analisis dengan Alat Bantu Permodelan (Modeling Tools)
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Management Functions
Management Objectives
Supporting Information
Supporting Data
Sources of Data
Backward Requirement AnalysisBackward Requirement Analysis
Forward Support AnalysisForward Support Analysis
• Monitoring
• Directing
• Planning
• Acting
• Monitoring Student Progress …
• Directing Student Research …
• Planning for Remedial Efforts .
• Acting on Remedial Plan …
• KRS
• Transkrip
• Supervisi
• Research List
• Academic Progress
• Treated Students
• Student Potentials
• Academic Problem
• BAAK
• Faculty
• Dept.
• Study Program
Kasus Contoh: Kasus Contoh: Data Requirement AnalysisData Requirement Analysis
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DataData InfoInfo MonitoringMonitoring DirectingDirecting ActingActingKRS, Transkrip IPK Kumulatif Status Akademik
MhsWarning 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= Data1..n
Info= Info1..n
Management Functions = Monitoring
Directing Acting Mencapai Target Academic Excellence?
Contoh Kasus: Analisis Kebutuhan Data MhsContoh Kasus: Analisis Kebutuhan Data Mhs
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Utilisasi Vs Ketersedian Informasi
• Ada dan Diperlukan
• Tak ada dan Diperlukan
• Ada dan Tak Diperlukan
• Tak Ada dan Tak Diperlukan
AdaTak Ada
Perlu
Tak Perlu
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Data Acquisition & Data Acquisition & Information ProductionInformation Production
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Database Management Systems (DBMS)Koleksi terpadu dari sekumpulan program (utilitas) yang
digunakan untuk mengakses dan merawat database
Database
DBMSDBMSUtilitas
UsersUsers
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Application Programs on Top of DBMS
Database
DBMSDBMS
Application programs
UsersUsers
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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.
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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
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Multiple Systems
ShareableResources
DBMS Approach Enables Resource Sharing Among Applications and Users
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Data Management Life Cycle
Real World
• ObservingObserving• IdentifyingIdentifying
• ConceptualizingConceptualizing• RepresentingRepresenting
• StructuringStructuring
• CodingCoding
• OptimizingOptimizing• AnalyzingAnalyzing• UpdatingUpdating
• ProtectingProtecting• MonitoringMonitoring
• BrowsingBrowsing
• Need of changesNeed of changes
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Data Modeling: Methods & Tools
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Copyright © 1997 by Rational Software Corporation
Business Process
Order
Item
Ship via
“Modeling captures essential parts of the system.”
Dr. James Rumbaugh
Visual Modeling is modelingusing standard graphical notations: chart, diagrams, objects, symbols
Why Modeling?
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Data Model
Usage: a fundamental set of tools & methods to consistently & uniformly view, organize, and treat database .
Definition: Integrated collection of concepts, theories, axioms, constraints for description, organization, validation, and interpretation of data.
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Types Data Models
Entity-relationshipEntity-relationship SemanticSemantic FunctionalFunctional Object OrientedObject Oriented
Object-Based Object-Based ModelModel
Relational Relational HierarchicalHierarchical NetworkNetwork
Record-Based Record-Based ModelModel
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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 WarehouseData Warehouse
Kudang B. SeminarKudang B. Seminar
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What is Data warehouse?What is Data warehouse?
• Data warehouse as a subject- oriented, Data warehouse as a subject- oriented, integrated, time variant, non-volatile integrated, time variant, non-volatile collection of data in support of collection of data in support of management’s decision making processmanagement’s decision making process
• Data warehouse systems consist of a Data warehouse systems consist of a set of programs that extract data from set of programs that extract data from the operational environment, a the operational environment, a database that maintains data database that maintains data warehousewarehouse data, and systems that data, and systems that provide data to usersprovide data to users
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The Goal of Data Ware The Goal of Data Ware House?House?
•to provide a "to provide a "single image single image of business realityof business reality" for the " for the organizationorganization
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Fundamental Ideas Behind the Fundamental Ideas Behind the Successful Data WarehousingSuccessful Data Warehousing
• Operational vs. Decision Support ApplicationsOperational vs. Decision Support Applications: : One impetus for One impetus for data warehouse is the unsuitability of traditional operationaldata warehouse is the unsuitability of traditional operational applications for typical decision support usage patterns;applications for typical decision support usage patterns;
• Primitive vs. Derived DataPrimitive vs. Derived Data: A critical success factor in data : A critical success factor in data warehouse design is understanding knowledge workers’ warehouse design is understanding knowledge workers’ demanddemand demand for detailed vs. summary data;demand for detailed vs. summary data;
• Time Series DataTime Series Data: Data warehouse often supports analysis of : Data warehouse often supports analysis of trends over time and comparisons of current vs. historical trends over time and comparisons of current vs. historical data;data;
• Data AdministrationData Administration: Another critical success factor is senior : Another critical success factor is senior management commitment to maintenance of the quality of management commitment to maintenance of the quality of corporate datacorporate data
• Systems ArchitectureSystems Architecture:: A system must be architected when it A system must be architected when it is very complex, requires the integration of many disciplines, is very complex, requires the integration of many disciplines, or is developed in the face of uncertain requirements.or is developed in the face of uncertain requirements.
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Alignment of data warehouse entities with the business structure
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A A corporate data warehouse is a corporate data warehouse is a process by which related data process by which related data from many operational systems is from many operational systems is merged to provide a single, merged to provide a single, integrated business information integrated business information view that spans all business view that spans all business
divisions.divisions.
Corporate Data for Corporate Data for WarehousesWarehouses