Candidate Key

Duration: 5 min

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Module outline

  1. Discrete Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic
  2. DataBase Management System/DBMS: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Relational Calculus, Transaction Management, Concurrency Control
  3. Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  4. Computer Architecture: Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design
  5. Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  6. C Language: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  7. Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  8. Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  9. Computer Networks: Introduction to CN, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware Basics
  10. Theory Of Computation/Automata Theory: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Complexity Theory
  11. Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  12. Engineering Mathematics: Permutation and Combination, Linear Algebra, Calculus, Probability, Statistics
  13. General Aptitude: Ratio and Proportion (Ratios), Divisibility Rules, Data Interpretation, Logarithm, Number System, HCF LCM, Sequence and Series (Series), Speed Time and Distance, Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Percentage, Mensuration and Geometry, Mental Ability, Arithmetic, Profit and Loss, Powers and Exponents (Surds and Indices), Average, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Syllogisms, Venn Diagram, Seating Arrangements, Blood Relations, Directions (Direction Test), Analogy, Algebra, Time and Work, Analytical Reasoning (Counting Figures Reasoning), Puzzle Solving (Puzzles), Cubes & Dices, Ranking, Order and Sequence, Mixture and Alligation, Age Problems, Clock, Selection Decision Table (Decision Making), Data Arrangement
  14. English (Verbal Aptitude): Vocabulary, Noun, Subject Verb Agreement (Verb Noun Agreement), Adjectives, Tenses, Pronoun, Preposition, Direct and Indirect Speech, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Sentence Correction (Error Correction), Verbal Analogy (Word Based Analogy), Conjunction, Interjection, Verb, Articles, Adverb, Modals, Sentence Construction
  15. Live Classes Recordings(Earlier Batch): GATE 2026 Live Class
  16. Full Mock Test:
  17. Previous Year Papers:
  18. GATE 2026 Counselling: Counselling and Guidance Sessions
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video lecture provides a detailed explanation of database normalization concepts, specifically focusing on the definitions and identification of Candidate Keys and Prime Attributes. The instructor begins by defining a Candidate Key as a minimal super key, meaning it is the smallest set of attributes that can uniquely identify a tuple in a relation. Using a specific example relation R(A, B, C, D) with functional dependencies A -> BCD and BCD -> A, the instructor demonstrates how to calculate attribute closures to determine candidate keys. He illustrates why a set like AB is a superkey but not a candidate key due to the presence of a proper subset (A) that is also a superkey. Finally, the lecture defines Prime Attributes as any attributes that are part of a candidate key, applying this definition to the initial example to identify all prime attributes in the relation.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video opens with a slide titled 'Candidate key' which defines it as the 'Minimum set of attributes that differentiates the tuple of a Relation' and notes it is also called a 'MINIMAL SUPER KEY'. The instructor writes a relation schema R(A, B, C, D) on the whiteboard and lists two functional dependencies: A -> BCD and BCD -> A. He begins the process of finding candidate keys by calculating the closure of attribute A, denoted as (A)+. He writes (A)+ = ABCD, demonstrating that A alone can determine all other attributes in the relation, thus making A a candidate key.

  2. 2:00 – 5:00 02:00-05:00

    The instructor continues the analysis by calculating the closure of the set AB, writing (AB)+ = ABCD. He explains that while AB is a superkey because it determines all attributes, it is not a candidate key because it contains a proper subset, A, which is already a superkey. This illustrates the 'minimal' requirement for candidate keys. He then identifies BCD as another candidate key because the functional dependency BCD -> A exists, and combined with A -> BCD, BCD determines all attributes. He circles A and BCD on the board to highlight them as the candidate keys for this specific relation.

  3. 5:00 – 5:26 05:00-05:26

    The slide changes to define 'Prime attribute' as 'Attributes that are member of candidate Keys are called Prime attributes'. The instructor applies this definition to the previous example R(A, B, C, D). Since A is a candidate key, A is a prime attribute. Since BCD is a candidate key, B, C, and D are also prime attributes. He concludes that in this specific relation, all attributes A, B, C, and D are prime attributes because they are all members of the identified candidate keys.

The lecture systematically builds the concept of Candidate Keys from the definition of Super Keys, emphasizing the 'minimal' property through a concrete example. By calculating closures for A and AB, the instructor clearly distinguishes between a superkey and a candidate key. The lesson concludes by extending this logic to define Prime Attributes, showing that any attribute participating in a candidate key holds this special status. This progression from definition to calculation to classification provides a complete understanding of these fundamental database concepts.

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