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Chapter 3: Data Modeling

Chapter 3: Data Modeling. Introduction An Overview of Databases Steps in Developing a Database Using Resources, Events and Agents Model Normalization. Introduction. Uses of a modern AIS Systematically record data Provide convenient and useful formats Easy access to information.

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Chapter 3: Data Modeling

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  1. Chapter 3:Data Modeling • Introduction • An Overview of Databases • Steps in Developing a Database Using Resources, Events and Agents Model • Normalization

  2. Introduction • Uses of a modern AIS • Systematically record data • Provide convenient and useful formats • Easy access to information

  3. Data Stores-Specific Diagrams • Included on both Flowcharts and DFDs • There are also rules related to data stores. For example • Can a customer have more than one address? • Can an address belong to more than one customer?

  4. What is a Database? • Collection of organized data • Used by many different computer applications • Manipulated by database management systems (DBMS)

  5. Significance of a Database • Critical information • Volume • Distribution • Privacy • Irreplaceable data • Need for accuracy • Internet uses

  6. Storing Data in Databases • Data must be stored and organized systematically • Three important concepts: • Data hierarchy • Record structures • Database keys

  7. Data Hierarchy • Data organization in ascending order: • Data field • Record • File • Database

  8. Record Structures • Data fields in each record of a database table • Structure is usually fixed • Example

  9. Database Keys • Primary Key • Unique to each record • Foreign Keys • Enable referencing of one or more records • Matches primary key of related table

  10. Records Combined Into Report

  11. Additional Database Issues • Administration • Database Administrator • Documentation • Includes a variety of descriptions • Structures, Contents, Security Features • Data Dictionary • Metadata

  12. Data Dictionary Example

  13. Additional Database Issues • Data Integrity • Data Integrity controls • Designed by database developers • Processing Accuracy and Completeness • Transaction controls • Ensures accurate transaction processing

  14. Additional Database Issues • Concurrency • Concurrency controls • Prevent multi-user access at same time • Backup and Security • Ability to recreate data • Prevent unauthorized access • View controls

  15. Study Break #1 • The part of the data hierarchy that represents one instance of an entity is a: • Field • Record • File • Database

  16. REA(L) Model • Resources • Organization’s assets • Events • Activities associated with a business processes • Agents • People associated with business activities • Location

  17. Steps in DevelopingDatabases with REA • Identify Business and Economic Events • Identify Entities • Identify Relationships Among Entities

  18. Steps in DevelopingDatabases with REA • Create Entity-Relationship Diagrams • Identify Attributes of Entities • Convert E-R Diagrams into Database Tables

  19. Identify Events and Entities • Types of Events • Business • Economic • Types of Database Entities • Entities • Agents • Resources

  20. Entity Examples

  21. Identify RelationshipsAmong Entities • Types of Relationships • Direct relationship • Indirect relationship • Cardinalities • Nature of relationships among entities

  22. Cardinality Relationships • Notations • One-to-one (1:1) • One-to-many (1:N) • Many-to-many (N:M) • Purpose • Occurrence of one entity • Associated with occurrence of one event of another entity • Examples of each (1:1, 1:N, N:M)

  23. Cardinality Relationships

  24. Entity-Relationship Diagram • Purpose • Diagram entities • Relationships among entities • Structure • Rectangles represent entities • Connecting lines represent relationships

  25. E-R Diagram Example

  26. Relationship Tables • Provide greater flexibility • Need for Relationship Tables • Many-to-many relationships • Linking tables with foreign keys

  27. Relationship Tables

  28. Schematic of Database Tables

  29. Normalization • Normalization • Methodology ensuring attributes are stored in most appropriate tables • Design promotes accuracy • Avoids redundancy of data storage • Levels • First normal form • Second normal form • Third normal form

  30. Unnormalized Data

  31. First Normal Form • In First Normal Form (1 NF) when: • All data fields are singular • Each attribute has one value • Problems • Data redundancy • Insertion anomaly • Deletion anomaly

  32. First Normal Form Example

  33. Anomalies

  34. Second Normal Form • In Second Normal Form (2 NF) when: • It is in 1 NF • All data items depend on primary record key (i.e., no partial dependencies) • Benefits • More efficient design • Eliminates data redundancy

  35. Second Normal Form Example

  36. Third Normal Form • In Third Normal Form (3 NF) when: • It is in 2 NF • Does not contain transitive dependencies • Data field A does not determine data field B • Ultimate Goal • Create database in 3 NF

  37. Third Normal Form Example

  38. Study Break #5 • A database is in third normal form (3NF) if it is second normal form and: • All the data attributes in a record are well defined • All the data attributes in a record depend on the record key • The data contain to transitive dependencies • The data can be stored in two or more separate tables

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