UGC NET Computer Science Database Management Systems Syllabus

Database Management Systems syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Database Management Systems in UGC NET Computer Science, not a summary of it.

1. 1

   Database System Concepts and Architecture

   4 topics

   • Data Models, Schemas, and Instances
   • Three-Schema Architecture and Data Independence
   • Database Languages and Interfaces
   • Centralized and Client/Server Architectures for DBMS
2. 2

   Data Modeling

   5 topics

   • Entity-Relationship Diagram
   • Relational Model - Constraints, Languages, Design, and Programming
   • Relational Database Schemas, Update Operations and Dealing with Constraint Violations
   • Relational Algebra and Relational Calculus
   • Codd Rules
3. 3

   SQL

   4 topics

   • Data Definition and Data Types
   • Constraints, Queries, Insert, Delete, and Update Statements
   • Views, Stored Procedures and Functions
   • Database Triggers, SQL Injection
4. 4

   Normalization for Relational Databases

   7 topics

   • Functional Dependencies and Normalization
   • Algorithms for Query Processing and Optimization
   • Transaction Processing
   • Concurrency Control Techniques
   • Database Recovery Techniques
   • Object and Object-Relational Databases
   • Database Security and Authorization
5. 5

   Enhanced Data Models

   8 topics

   • Temporal Database Concepts
   • Multimedia Databases
   • Deductive Databases
   • XML and Internet Databases
   • Mobile Databases
   • Geographic Information Systems
   • Genome Data Management
   • Distributed Databases and Client-Server Architectures
6. 6

   Data Warehousing and Data Mining

   14 topics

   • Data Modeling for Data Warehouses
   • Concept Hierarchy, OLAP and OLTP
   • Association Rules
   • Classification
   • Clustering
   • Regression
   • Support Vector Machine
   • K-Nearest Neighbour
   • Hidden Markov Model
   • Summarization
   • Dependency Modeling
   • Link Analysis
   • Sequencing Analysis
   • Social Network Analysis
7. 7

   Big Data Systems

   5 topics

   • Big Data Characteristics
   • Types of Big Data
   • Big Data Architecture
   • Introduction to Map-Reduce and Hadoop
   • Distributed File System, HDFS
8. 8

   NOSQL

   4 topics

   • NOSQL and Query Optimization
   • Different NOSQL Products, Querying and Managing NOSQL
   • Indexing and Ordering Data Sets
   • NOSQL in Cloud

Database Management Systems flashcards for UGC NET Computer Science

23 of 53 cards from the Database Management Systems deck — real questions with worked answers.

1. In DBMS terminology, what is a data model?

   A collection of concepts used to describe the structure of a database — its data types, relationships, and constraints — together with the basic operations and behavior allowed on the data.

2. Distinguish between a database schema and a database instance (state).

   The schema is the description/structure of the database (defined at design time and rarely changes); an instance/state is the actual data stored at a particular moment, which changes with every update.

3. What are the three levels of the ANSI/SPARC three-schema architecture?

   Internal level (physical storage details via the internal schema), conceptual level (overall logical structure for the whole community), and external/view level (individual user views via external schemas).

4. Define logical and physical data independence in the three-schema architecture.

   Logical data independence: ability to change the conceptual schema without altering external schemas/applications. Physical data independence: ability to change the internal (physical) schema without altering the conceptual schema.

5. What is the difference between a DDL and a DML in database languages?

   DDL (Data Definition Language) defines schemas (CREATE, ALTER, DROP); DML (Data Manipulation Language) retrieves and modifies data (SELECT, INSERT, UPDATE, DELETE). High-level DML is declarative/set-oriented; low-level is record-at-a-time (procedural).

6. Compare centralized and client/server DBMS architectures.

   Centralized: all DBMS functionality, application, and UI run on one machine. Client/server: functionality is split — clients handle UI/application logic and send requests to a server that manages the database, enabling distribution and scalability.

7. In an ER diagram, what notation distinguishes an entity, attribute, relationship, and key attribute?

   Entity = rectangle, attribute = oval (underlined oval for a key attribute), relationship = diamond, multivalued attribute = double oval, derived attribute = dashed oval, weak entity = double rectangle.

8. What is a weak entity type and what is its identifying (partial) key?

   A weak entity has no key attribute of its own; it depends on an identifying (owner) entity through an identifying relationship. Its partial key combined with the owner's key forms its full identifier.

9. What do cardinality ratios 1:1, 1:N, and M:N mean in a binary relationship?

   They specify the maximum number of relationship instances an entity can participate in: 1:1 (one-to-one), 1:N (one-to-many), and M:N (many-to-many).

10. Differentiate total and partial participation constraints in an ER model.

    Total participation (existence dependency, shown by a double line) means every entity instance must participate in the relationship; partial participation (single line) means participation is optional.

11. In the relational model, define relation, tuple, attribute, and domain.

    A relation is a table; a tuple is a row; an attribute is a named column; a domain is the set of atomic permissible values for an attribute.

12. State the entity integrity and referential integrity constraints.

    Entity integrity: no primary key attribute may be NULL. Referential integrity: a foreign key value must either match an existing primary key value in the referenced relation or be NULL.

13. Differentiate superkey, candidate key, and primary key.

    A superkey uniquely identifies tuples (may have extra attributes); a candidate key is a minimal superkey; the primary key is the chosen candidate key used as the main identifier.

14. What constraint-violation handling options exist for a referential integrity violation on delete/update?

    RESTRICT/NO ACTION (reject), CASCADE (propagate the delete/update), and SET NULL or SET DEFAULT for the referencing foreign key values.

15. List the basic operations of relational algebra.

    Unary: SELECT (σ), PROJECT (π), RENAME (ρ). Set: UNION (∪), INTERSECTION (∩), DIFFERENCE (−), CARTESIAN PRODUCT (×). Plus JOIN (⋈), DIVISION (÷), and aggregate/grouping.

16. How does relational calculus differ from relational algebra?

    Relational algebra is procedural (specifies how to compute the result via operations); relational calculus is declarative/non-procedural (specifies what is wanted). Calculus comes in tuple (TRC) and domain (DRC) forms.

17. What is a natural join and how does it differ from a theta join?

    A natural join (⋈) joins on equality of all common-named attributes and removes the duplicate column; a theta join joins on an arbitrary condition (θ) and keeps both columns of the joined attributes.

18. State three of Codd's 12 rules for a fully relational DBMS.

    Examples: Rule 0 (Foundation) — must manage data relationally; Information rule — all data represented as values in tables; Guaranteed access rule — every value accessible via table name + primary key + column; Systematic NULL handling rule.

19. What is the difference between the CHAR and VARCHAR SQL data types?

    CHAR(n) is fixed-length, padded with spaces to n characters; VARCHAR(n) is variable-length up to n characters, storing only the actual string and using storage more efficiently.

20. In SQL, what is the difference between the DELETE and TRUNCATE statements?

    DELETE is a DML command that removes rows (optionally with WHERE) and can be rolled back, logging each row; TRUNCATE is a DDL command that quickly removes all rows, resets storage, and generally cannot be rolled back.

21. What is a database view, and what is a materialized view?

    A view is a virtual table defined by a stored query, computed on demand. A materialized view physically stores the query result and must be refreshed to stay current.

22. Differentiate a stored procedure from a user-defined function in SQL.

    A function must return a value and can be used inside SQL expressions/queries, typically without side effects; a stored procedure performs actions, may return zero or many results via output params, and is invoked with CALL/EXECUTE.

23. What is a database trigger and what are its main timing/event options?

    A trigger is procedural code automatically executed in response to events (INSERT/UPDATE/DELETE), firing BEFORE or AFTER the event, at ROW or STATEMENT level, optionally with a WHEN condition.

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