DBMS Topics
HubUnit 1 — Introduction to DBMS & Entity-Relationship ModelAdvantages and Disadvantages of DBMSAggregationCharacteristics of DBMSData IndependenceData ModelsDatabase Users and AdministratorsDBMS LanguagesER DiagramsEntity-Relationship ER ModelIntroduction to DBMSKeys in DBMSRelationships and CardinalitySchema and InstanceSpecialization and GeneralizationUnit 1 Summary — Introduction to DBMS & ER ModelThree-Level Architecture ANSI/SPARC ArchitectureWeak Entity SetUnit 2 — Relational Model & SQLConstraints in SQLCursorsDCL and TCL CommandsDDL CommandsDML CommandsDomain Relational Calculus DRCFunctions and Stored ProceduresJoins in SQLNested Queries SubqueriesRelational AlgebraRelational CalculusRelational ModelSQL IntroductionUnit 2 Summary — Relational Model & SQLTriggers in SQLTuple Relational Calculus TRCViews in SQLArmstrong's Axioms & Closure of AttributesBoyce-Codd Normal Form BCNFClosure of AttributesDependency PreservationFifth Normal Form 5NFFirst Normal Form 1NFFourth Normal Form 4NFFunctional DependencyLossless DecompositionMultivalued DependencyNormal Forms — OverviewNormalization — IntroductionSecond Normal Form 2NFUnit 3 Summary — NormalizationThird Normal Form 3NFUnit 4 — Transaction Management & Concurrency ControlACID PropertiesCheckpointsConcurrency Control & SerializabilityDeadlock in DBMSLock-Based Protocols & Two-Phase LockingLog-Based RecoveryRecovery SystemSerializabilityShadow PagingUnit 4 Summary — Transaction Management & Concurrency ControlTimestamp-Based ProtocolTransaction ManagementTransaction StatesTwo-Phase Locking 2PLUnit 5 — Storage & IndexingB+ TreeB-TreeCost EstimationDynamic HashingFile OrganizationHashing TechniquesIndexing — IntroductionMulti-Level IndexingQuery OptimizationQuery ProcessingSingle-Level IndexingStatic HashingUnit 5 Summary — Storage & IndexingUnit 6 — Advanced Topics in DBMSBig Data and DBMSCloud DatabaseData MiningData WarehouseDatabase SecurityDistributed DatabaseDistributed Query ProcessingDistributed DBMS Architecture, Fragmentation & ReplicationMongoDB — IntroductionNoSQL DatabaseReplication in Distributed DatabasesUnit 6 Summary — Advanced Topics in DBMSViva Voce — DBMSImportant Viva Questions — DBMSInterview Questions — DBMSViva Answers — DBMSDBMS Multiple Choice Questions MCQsDBMS Lab Programs
Unit 3 Summary — Normalization
Last Updated : 21 May, 2026
Unit 3186 words9 headingsTables includedExamples included
Key Concepts at a Glance
Functional Dependency Types
| Full FD: (A,B) | C where neither A→C nor B→C alone |
| Partial FD: (A,B) | C where A→C alone (violates 2NF) |
| Transitive FD: A | B → C where B is non-key (violates 3NF) |
| Trivial FD: {A,B} | A (Y ⊆ X — always true) |
Armstrong's Axioms (Quick Reference)
| Rule | Statement |
|---|---|
| Reflexivity | Y ⊆ X → X → Y |
| Augmentation | X → Y → XZ → YZ |
| Transitivity | X→Y, Y→Z → X→Z |
| Union | X→Y, X→Z → X→YZ |
| Decomposition | X→YZ → X→Y and X→Z |
| Pseudo-transitivity | X→Y, WY→Z → WX→Z |
Attribute Closure Algorithm
X+ = X
Repeat until no change:
For each FD (LHS → RHS) in F:
If LHS ⊆ X+:
X+ = X+ ∪ RHS
Normal Forms — One-Line Rules
| 1NF | All values are atomic; no repeating groups |
| 2NF | 1NF + No partial FDs on composite PK |
| 3NF | 2NF + No transitive FDs on PK |
| BCNF | Every FD determinant is a superkey |
| 4NF | Every MVD determinant is a superkey |
| 5NF | Every join dependency component is a superkey |
Normal Form Decision Flow
| NO | Fix → 1NF |
| YES | Remove partial deps → 2NF |
| YES | Remove transitive deps → 3NF |
| YES | Decompose → BCNF |
| YES | Decompose → 4NF |
| NO | 5NF achieved ✓ |
Decomposition Properties
| Property | 3NF | BCNF |
|---|---|---|
| Lossless join | ✓ Always | ✓ Always |
| Dependency preserving | ✓ Always | ✗ Not always |
Lossless Join Test (Binary Decomposition)
R decomposed into R1, R2 is lossless if:
(R1 ∩ R2) → R1 OR (R1 ∩ R2) → R2
i.e., common attributes form a superkey of R1 or R2.
Important Exam Points
- Candidate key = minimal superkey = all attributes functionally determined
- Prime attribute = any attribute that is part of some candidate key
- Non-prime attribute = attribute not part of any candidate key
- BCNF is stricter than 3NF — may lose dependency preservation
- MVDs always come in complementary pairs: X →→ Y implies X →→ (R − X − Y)
- Every FD X → Y implies MVD X →→ Y (but not vice versa)
- 3NF synthesis guarantees both lossless and dependency-preserving decomposition
Exam Focus
Revise definitions, diagrams, examples, and short-answer points for Unit 3 Summary — Normalization.
Interview Use
Prepare one clear explanation, one practical example, and one common mistake for this DBMS topic.
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Unit 3Normalization — IntroductionNormalization is the process of organizing a relational database to reduce data redundancy and improve data integrity by decomposing large, poorly structured tables into Unit 3Armstrong's Axioms & Closure of AttributesArmstrong's Axioms are a set of inference rules used to derive all functional dependencies FDs from a given set F. They were proposed by William W. Armstrong in 1974.Unit 3Boyce-Codd Normal Form BCNFA relation R is in BCNF Boyce-Codd Normal Form if, for every non-trivial functional dependency X → Y in R:Unit 3Closure of AttributesThe closure of a set of attributes X denoted X⁺ under a set of functional dependencies F is the set of ALL attributes that are functionally determined by X.Unit 3Dependency PreservationA decomposition of R into R1, R2, ..., Rn is dependency-preserving if the union of the functional dependencies that can be derived from each Ri restricted to the attributUnit 3Fifth Normal Form 5NFA relation R is in Fifth Normal Form 5NF — also called Project-Join Normal Form PJ/NF — if, for every non-trivial join dependency R1, R2, ..., Rn in R: