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Database Development Indra Budi indra@cs.ui.ac.id
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What is differences ? Logical Data Independence Vs Physical data independence ? Logical Data Independence Vs Physical data independence ?
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Conceptual Schema Describes the Meaning of Data in the Universe of Discourse Describes the Meaning of Data in the Universe of Discourse –Emphasizes on General, Conceptually Relevant, and Often Time Invariant Structural Aspects of the Universe of Discourse Excludes the Physical Organization and Access Aspects of the Data Excludes the Physical Organization and Access Aspects of the Data
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Conceptual Schema Another Example Another Example
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External Schema Describes Parts of the Information in the Conceptual Schema in a form Convenient to a Particular User Group’s View Describes Parts of the Information in the Conceptual Schema in a form Convenient to a Particular User Group’s View Derived from the Conceptual Schema Derived from the Conceptual Schema
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External Schema Another Example Another Example
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Internal Schema Describes How the Information Described in the Conceptual Schema is Physically Represented in a Database to Provide the Overall Best Performance Describes How the Information Described in the Conceptual Schema is Physically Represented in a Database to Provide the Overall Best Performance
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Internal Schema Another Example Another Example
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Unified Example of Three Schemas
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Building a Database System Essentially the same as the process for building any other information system, consists of three basic phases: Essentially the same as the process for building any other information system, consists of three basic phases: Requirements phase: a data model is developed Requirements phase: a data model is developed Design phase: the data model is transformed into tables and relationships Design phase: the data model is transformed into tables and relationships Implementation phase: create tables into the DBMS Implementation phase: create tables into the DBMS
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Requirement Phase Data model is developed Data model is developed A data model is a logical representation of the structure of the database A data model is a logical representation of the structure of the database Its very important because design & implementation depend on this phase Its very important because design & implementation depend on this phase –If the data model inaccurate, then the result will be waste, aggravation, delays and useless
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Example: Data Model Rectangular are entity & diamonds are relationships We will discuss this model in detail later…
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The Design Phase The data model transform into tables & relationships The data model transform into tables & relationships Data properties established type, length, null/not null. Data properties established type, length, null/not null. Need for index determined Need for index determined Constraint, trigger, stored procedure are defined Constraint, trigger, stored procedure are defined Figure 1-19 Kroenke Figure 1-19 Kroenke
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The Implementation Phase Tables & relationships created Tables & relationships created –Via SQL –Via Graphical design tool Stored procedure & trigger are written & tested Stored procedure & trigger are written & tested Figure 1-20 Kroenke Figure 1-20 Kroenke
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Application Development Application development proceeds in parallel with database development Application development proceeds in parallel with database development
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Suggested structure of Report 1 Introduction Introduction –Brief overview of DBMS (name, vendor, version, price (if any), primary user, history of the DBMS, etc) –Description of DBMS features you want to compare and why they are important. Table comparation Table comparation Analysis Analysis Conclusion Conclusion
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