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Database Organization & Normalization for Efficient Management

Learn database design, normalization, relational model transformation, update anomalies, functional dependencies, and key concepts in efficient data organization.

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Database Organization & Normalization for Efficient Management

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  1. IT420: Database Management and Organization Normalization 31 January 2006 Adina Crăiniceanu www.cs.usna.edu/~adina

  2. Previously on IT420 • Database design • Entity-Relationship (ER) Model • Relational Model • Transform ER to relational model • Database Implementation • SQL Kroenke, Database Processing

  3. Goal • Refresh ER to Relational • Normalization Kroenke, Database Processing

  4. ER to Relational • ER: • Entities • identifiers • Relationships • cardinality • Relational model • Tables • Constraints Kroenke, Database Processing

  5. ER to Relational • Transform entities in tables • Transform relationships using foreign keys • Specify logic for enforcing minimum cardinalities Kroenke, Database Processing

  6. Class Exercise: Transform ER model into Relational Model Kroenke, Database Processing

  7. Outline • ER to Relational • Normalization Kroenke, Database Processing

  8. Premise • We have received one or more tables with data • The data is to be stored in a new database • QUESTION: Should the data be stored as received, or should it be transformed for storage? Kroenke, Database Processing

  9. Data Redundancy Application constraint: All employees with same rating have the same wage (Rating Wage) Problems due to data redundancy? Kroenke, Database Processing

  10. Modification Anomalies • Deletion Anomaly: What if we delete all employees with rating 8? • Insertion Anomaly: What if we have a new employee with new rating 12? • Update Anomaly: What if we change the wage for rating 7 to be 27? Kroenke, Database Processing

  11. Update Anomalies • The EMPLOYEE table before and after an incorrect update operation on Wage for Rating = 7 Kroenke, Database Processing

  12. Table decomposition Problem? Kroenke, Database Processing

  13. Decisions • Do we have to decompose / merge? • How do we identify problems caused by redundancy? • Functional dependencies Kroenke, Database Processing

  14. Functional Dependency (FD) • A functional dependency: the value of one (a set of) attribute(s) determines the value of a second (set of) attribute(s): Alpha  MIDNName Alpha  (DormName, DormRoom) • The attribute on the left side of the functional dependency is called the determinant • Functional dependencies may be based on equations: Charge = NbHours X HourlyPrice (NbHours, HourlyPrice)Charge • Function dependencies are not equations! Kroenke, Database Processing

  15. Functional Dependencies Are Not Equations ObjectColor  Weight ObjectColor  Shape ObjectColor (Weight, Shape) Kroenke, Database Processing

  16. Composite Determinants • Composite determinant: A determinant of a functional dependency that consists of more than one attribute • (StudentName, ClassName)  Grade • (NbHours, HourlyPrice)  Charge Kroenke, Database Processing

  17. Functional Dependency (FD) Rules • If A  (B, C), then A  B and A C • If (A,B)  C, then neither A nor B determines C by itself Kroenke, Database Processing

  18. FD Facts • A functional dependency is a statement about all allowable instances of a table • You cannot find the functional dependencies simply by looking at some data: • Data set limitations • Must be logically a determinant • Given some data in a table R, we can check if it violates some FD, but we cannot tell if the FD holds over R! Kroenke, Database Processing

  19. Functional Dependencies in the SKU_DATA Table Assuming data is representative, determine the FD Kroenke, Database Processing

  20. Functional Dependencies in the SKU_DATA Table SKU  (SKU_Description, Department, Buyer) SKU_Description  (SKU, Department, Buyer) Buyer  Department Kroenke, Database Processing

  21. Class Exercise Assuming all FD that are verified by the data are indeed FD, determine the FD in the ORDER_ITEM Table Kroenke, Database Processing

  22. What Makes Determinant Values Unique? • A determinant is unique in a relation if, and only if, it determines every other column in the relation • Unique determinants = superkey Kroenke, Database Processing

  23. Key • A set of columns is a key for a relation if : 1. No two distinct rows can have same values in all key columns, and 2. This is not true for any subset of the key • Part 2 false? A superkey • Primary key • Alternate key Kroenke, Database Processing

  24. Normal Forms • Relations are categorized as a normal form based on which modification anomalies or other problems that they are subject to: Kroenke, Database Processing

  25. Normal Forms • Boyce-Codd Normal Form (BCNF) – A relation is in BCNF if every determinant is a candidate key “I swear to construct my tables so that all nonkey columns are dependent on the key, the whole key and nothing but the key, so help me Codd.” Kroenke, Database Processing

  26. Eliminating Modification Anomalies from Functional Dependencies in Relations • Put all relations into Boyce-Codd Normal Form (BCNF): Kroenke, Database Processing

  27. Putting a Relation into BCNF:EQUIPMENT_REPAIR Kroenke, Database Processing

  28. Putting a Relation into BCNF:EQUIPMENT_REPAIR EQUIPMENT_REPAIR (ItemNumber, Type, AcquisitionCost,RepairNumber, RepairDate, RepairAmount) ItemNumber  (Type, AcquisitionCost) RepairNumber  (ItemNumber, Type, AcquisitionCost, RepairDate, RepairAmount) ITEM (ItemNumber, Type, AcquisitionCost) REPAIR (ItemNumber, RepairNumber, RepairDate, RepairAmount) Where REPAIR.ItemNumber must exist in ITEM.ItemNumber Kroenke, Database Processing

  29. Putting a Relation into BCNF:New Relations Kroenke, Database Processing

  30. Class Exercise Put the following relation into BCNF Kroenke, Database Processing

  31. Multivalued Dependencies • A multivalued dependency occurs when a determinant determines a particular set of values: Employee  Degree Employee  Sibling PartKit  Part • The determinant of a multivalued dependency can never be a primary key Kroenke, Database Processing

  32. Multivalued Dependencies Kroenke, Database Processing

  33. Eliminating Anomolies from Multivaled Dependencies • Multivalued dependencies are not a problem if they are in a separate relation, so: • Always put multivalued dependencies into their own relation • This is known as Fourth Normal Form (4NF) Kroenke, Database Processing

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