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MBI 630: Week 9 Conceptual Data Modeling and Designing Database

MBI 630: Week 9 Conceptual Data Modeling and Designing Database. 6/7/2014. Week 9: Conceptual Data Modeling and Designing Database. Data Modeling (Logical Design) Designing Database (Physical Design). Overview of Database Design. Capture Users’ “Views” of data Forms, Screens, Reports

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MBI 630: Week 9 Conceptual Data Modeling and Designing Database

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  1. MBI 630: Week 9Conceptual Data Modeling and Designing Database 6/7/2014

  2. Week 9: ConceptualDataModelingandDesigningDatabase • Data Modeling (Logical Design) • Designing Database (Physical Design)

  3. Overview of Database Design • Capture Users’ “Views” of data • Forms, Screens, Reports • Data Modeling (entity-based ERD) • Add keys, attributes, relationships (key-based, and fully-described ERD) • Consolidate data models – One big ERD • Determine Database Schema

  4. Data Modeling • Data modeling is a technique for organizing and documenting a system’s DATA. Data modeling is sometimes called database modeling because a data model is usually implemented as a database. • Entities • Attributes • Relationships • Cardinality

  5. Entity-Relationship (E-R) Diagram • Entity-Relationship diagram is graphical representation of E-R model, which is a detailed, logical representation of the entities, associations (relationships), and data elements (attributes) for an organization of business area.

  6. Basic Symbols (cf. Fig. 9.3 p. 287, etc.)

  7. FigureSample conceptual data model (entity-based)

  8. Figure: Example relationships of different degrees

  9. (Physical) Database Design • Purpose of database design -- Translate a relational data model into a technical file and database design that balances several performance factors -- Choose data storage technologies that will efficiently, accurately and securely process database activities

  10. The Database Schema • Data type. Each DBMS supports different data types, and terms for those data types. • Size of the Field. Different DBMSs express precision of real numbers differently. • NULL or NOT NULL. Must the field have a value before the record can be committed to storage? • Domains. Many DBMSs can automatically edit data to ensure that fields contain legal data. • Default. Many DBMSs allow a default value to be automatically set in the event that a user or programmer submits a record without a value. • Referential Integrity. An integrity constraint specifying that the value (or existence) of an attribute in one relation depends on the value (or existence) of the same attribute in another relation

  11. Other Considerations • Denormalization • Choices of storage formats • File organizations • Backup/Recovery • Security of Data

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