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Advanced Database Systems

This is the collection of Sikkim Manipal University (SMU) question and answers for Advanced Database Systems. It will help to prepare your examination. All question paper are classified as per semester, subject code and question type of Part A, Part B and Part C with multiple choice options as same as actual examination. SMU question papers includes year 2024, 2023, 2022 Sem I, II, III, IV, V, VI examinations of all subjects.

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Course Name        MCA (Master of Computer Application)

Subject Code       MC0077 (Advanced Database Systems)

Get Questions        PART - A    PART - B    PART - C

Advanced Database Systems Syllabus.

Unit 1 Introduction
Introduction; History; Database models; Flat Model: Hierarchical Model, Network Model, Relational Model: Relational Operations; Normal Forms: First Normal Form, Second Normal Form, Third Normal Form, Boyce-Codd Normal Form, Fourth Normal Form, Domain/Key Normal Form; Dimensional Model, Object Database Models, Post-relational Database Models; Database Internals: Indexing, Transactions and Concurrency, Replication

Unit 2 Query Processing
Introduction; Query Optimizer; Query Plan; Implementation; Heuristics of Query Optimizations: Equivalence of Expressions, Selection Operation, Projection Operation, Natural Join Operation: Join Ordering; Query Planning for Nested SQL queries; Cost Estimation; Measuring Index Selectivity: Index Selectivity, How to Measure Index Selectivity?, Manually measure index selectivity; How to choose Composite Indexes?; Guidelines for choosing columns for composite indexes: Join Strategies for Parallel Processors: Parallel-Join, Pipelined Multi-way
Join, Physical Organization, Database Tuning, Efficient SELECT statements; Optimizing SQL Query Processing: Introduction; Query Processing; Query Optimizing: Indexes, Selectivity, Uniformity, Disjunctive Clauses, Join Selectivity, Views.

Unit 3 Advanced Data Management Systems
Introduction; Data Collection; Data Management Functions; Database Design & Creation; Information & Data Retrieval; The Evolution of Data Management Systems; Administrative Database Management Systems; Text-based Information Retrieval; Systems; Image Retrieval Systems; Multiple Media Information Retrieval Systems, MIRS; Management of Web Databases, W-DBM

Unit 4 Advanced Data Modeling
Introduction; A Brief History; Concepts & Components; Methodology; Graphic vs. Declarative Data Models; Model Types: Relational, Entity-Relationship, Object-Oriented; A Structural Semantic Data Model – SSM: SSM Concepts: Entity Types, Relationship Types, Attribute Types, Domain Specification, Cardinality Specifications, Data Value Constraints; SSM Syntax; Translation to Relational Constructs; Modeling Multiple Media Data Collections: Metadata; Metadata for Mulltimedia: Semantic Metadata, Context Metadata, Structural Metadata; Standards for Metadata Specification: Dublin Core, MPEG-7, CIDOC-CRM, Multiple Media Documents, Characteristics of Text Documents, Characteristics of Images; Modelling Multimedia Collections in SSM

Unit 5 SQL 3 – Querying Complex Objects
Introduction; Database Query Language; New Features in SQL3: Accessing Hierarchic Structures, Accessing Multi-Valued Structures, Utilizing User Defined Data Types (UDT), Accessing Large Objects, Result Presentation; An example SQL3 query; Query Optimization; Text Retrieval Using SQL3/Text Retrieval: Text Document Retrieval, Retrieval using Context Metadata, Text Retrieval by Semantic Content; Result Presentation: Ordering Query Results – Ranking, Measuring Retrieval Quality - Recall and Precision; Image Retrieval: Using Extended SQL3 for Image Retrieval, Attribute-Based Image Retrieval, Text-Based Image Retrieval; Query by Image Content, CBIR: Using Content Descriptors; Color And Texture, Identifying Shapes - Image Objects, Streamed Image Retrieval – Video, Improving Result Quality.

Unit 6 Object Oriented Databases
Introduction; Query Processing in Object-Oriented Database Systems: Type System, Encapsulation, Complex Objects and Inheritance, Object Models; Query Processing Architecture: Query Processing Methodology; Object - Relational Database Implementation: DB Components; DB Design: From Requirement Analysis to DB Specification, Schema Architecture; SQL3 DB specification: Complex Structures, Hierarchical Structures, Relationships, Large Objects, LOBs, Storage of LOBs.

Unit 7 Data Warehouse & Data Mining
Introduction; History of Data Warehousing; Data Warehouse Architecture; Data Storage Methods; Advantages of using Data Warehouse; Introduction to Data Mining; Data dredging; Data Mining Functions: Classification, Associations, Sequential/Temporal patterns, Clustering/Segmentation, IBM - Market Basket Analysis example; Data Mining Techniques: Cluster Analysis, Induction, Decision Trees, Rule Induction, Neural Networks, On-line Analytical Processing, OLAP

Part 1 Introduction
Introduction; History; Database models; Flat Model: Hierarchical Model, Network Model, Relational Model: Relational Operations; Normal Forms: First Normal Form, Second Normal Form, Third Normal Form, Boyce-Codd Normal Form, Fourth Normal Form, Domain/Key Normal Form; Dimensional Model, Object Database Models, Post-relational Database Models; Database Internals: Indexing, Transactions and Concurrency, Replication

Part 2 Query Processing
Introduction; Query Optimizer; Query Plan; Implementation; Heuristics of Query Optimizations: Equivalence of Expressions, Selection Operation, Projection Operation, Natural Join Operation: Join Ordering; Query Planning for Nested SQL queries; Cost Estimation; Measuring Index Selectivity: Index Selectivity, How to Measure Index Selectivity?, Manually measure index selectivity; How to choose Composite Indexes?; Guidelines for choosing columns for composite indexes: Join Strategies for Parallel Processors: Parallel-Join, Pipelined Multi-way
Join, Physical Organization, Database Tuning, Efficient SELECT statements; Optimizing SQL Query Processing: Introduction; Query Processing; Query Optimizing: Indexes, Selectivity, Uniformity, Disjunctive Clauses, Join Selectivity, Views.

Part 3 Advanced Data Management Systems
Introduction; Data Collection; Data Management Functions; Database Design & Creation; Information & Data Retrieval; The Evolution of Data Management Systems; Administrative Database Management Systems; Text-based Information Retrieval; Systems; Image Retrieval Systems; Multiple Media Information Retrieval Systems, MIRS; Management of Web Databases, W-DBM

Part 4 Advanced Data Modeling
Introduction; A Brief History; Concepts & Components; Methodology; Graphic vs. Declarative Data Models; Model Types: Relational, Entity-Relationship, Object-Oriented; A Structural Semantic Data Model – SSM: SSM Concepts: Entity Types, Relationship Types, Attribute Types, Domain Specification, Cardinality Specifications, Data Value Constraints; SSM Syntax; Translation to Relational Constructs; Modeling Multiple Media Data Collections: Metadata; Metadata for Mulltimedia: Semantic Metadata, Context Metadata, Structural Metadata; Standards for Metadata Specification: Dublin Core, MPEG-7, CIDOC-CRM, Multiple Media Documents, Characteristics of Text Documents, Characteristics of Images; Modelling Multimedia Collections in SSM

Part 5 SQL 3 – Querying Complex Objects
Introduction; Database Query Language; New Features in SQL3: Accessing Hierarchic Structures, Accessing Multi-Valued Structures, Utilizing User Defined Data Types (UDT), Accessing Large Objects, Result Presentation; An example SQL3 query; Query Optimization; Text Retrieval Using SQL3/Text Retrieval: Text Document Retrieval, Retrieval using Context Metadata, Text Retrieval by Semantic Content; Result Presentation: Ordering Query Results – Ranking, Measuring Retrieval Quality - Recall and Precision; Image Retrieval: Using Extended SQL3 for Image Retrieval, Attribute-Based Image Retrieval, Text-Based Image Retrieval; Query by Image Content, CBIR: Using Content Descriptors; Color And Texture, Identifying Shapes - Image Objects, Streamed Image Retrieval – Video, Improving Result Quality.

Part 6 Object Oriented Databases
Introduction; Query Processing in Object-Oriented Database Systems: Type System, Encapsulation, Complex Objects and Inheritance, Object Models; Query Processing Architecture: Query Processing Methodology; Object - Relational Database Implementation: DB Components; DB Design: From Requirement Analysis to DB Specification, Schema Architecture; SQL3 DB specification: Complex Structures, Hierarchical Structures, Relationships, Large Objects, LOBs, Storage of LOBs.

Part 7 Data Warehouse & Data Mining
Introduction; History of Data Warehousing; Data Warehouse Architecture; Data Storage Methods; Advantages of using Data Warehouse; Introduction to Data Mining; Data dredging; Data Mining Functions: Classification, Associations, Sequential/Temporal patterns, Clustering/Segmentation, IBM - Market Basket Analysis example; Data Mining Techniques: Cluster Analysis, Induction, Decision Trees, Rule Induction, Neural Networks, On-line Analytical Processing, OLAP Example, Comparison of OLAP and OLTP, Data Visualization

Part 8 Fuzzy Dimension to Databases
Introduction; Uncertainty: A Modern Outlook; Fuzzy Sets: Basic Concepts: Introduction, Definition, Fuzzy Set Operators and Fuzzy Logic; Fuzzy Databases: Need for Fuzzy Databases, Techniques for implementation of Fuzziness in Databases, Classification of Data; Fuzzy Querying to Relational Databases: The proposed model, Meta Knowledge, Implementation; Realization of Fuzzy SQL.

Part 9 Distributed Database Systems and Data Replication
Introduction; Clients, Servers and Nodes; Direct and Indirect Connections; Site Autonomy; Schema Objects and Naming in a Distributed Database; Database Links; Statements and Transactions in a Distributed Database: Remote and Distributed Statements, Remote and Distributed Transactions; Transparency in a Distributed Database System; Heterogeneous Distributed Database Systems: The Mechanics of a Heterogeneous Distributed Database; Data Replication: Availability, Performance, Disconnected Computing, Network Load Reduction, Mass Deployment; Applications That Use Replication: Replication Objects, Groups,  and Sites: Replication Objects, Replication Group, Replication Sites; Types of Replication Environments: Multi - Master Replication, Materialized View Replication, Multi-Master and Materialized View Hybrid Configurations; Other Options for Multi-Master Replication: Synchronous Replication, Procedural Replication, Conflict Detection and Procedural Replication

Part 10 Transaction Management in Distributed Database Management
Introduction; Features of Distributed vs. Centralized Databases or Differences in Distributed & Centralized Databases: Centralized Control vs. Decentralized Control, Data Independence, Reduction of Redundancy, Complex Physical Structures and Efficient Access, Integrity, Recovery and Concurrency Control, Privacy and Security, Distributed Query Processing, Distributed Directory (Catalog) Management; Relative Advantages of Distributed Databases over Centralized Databases: Organizational and Economic Reasons, Incremental Growth, Reduced Communication Overhead, Performance Considerations, Reliability and Availability, Management of Distributed Data with Different Levels of Transparency: Distribution or Network Transparency, Replication Transparency, Fragmentation Transparency; Problem Areas of Distributed Databases; Structure of Distributed Database Management Systems; Transaction Processing Framework; Models of Failure; Two-Phase Commit Protocol; Recovery in Two-Phase Commit Protocol: Site Failures, Failure of Coordinator, Network Partitions; Elimination of ―Prepare‖ Message: Increasing Efficiency by Using Defaults, Remote Recovery Information Problem; Three-Phase Commit Protocol: Recovery in Three-Phase Commit Protocol: Site Failures, Failure of the Coordinator, Coordinator Failure Protocol; Classification of Concurrency Control Techniques; Two-Phase Locking Algorithm; Concurrency Control (Serializability); Locking Protocols for Concurrency Control in Distributed Databases: Single-Lock-Manager Approach, Multiple Coordinators, Majority Protocol, Biased Protocol, Primary Copy; Concurrency Control Techniques: Timestamp-Based Algorithms, Conservative Timestamp Ordering Algorithm, Optimistic Algorithm; Deadlock Handling: Deadlock Prevention, Deadlock Detection, Centralized Deadlock Detection, Hierarchical Deadlock Detection; Distributed Deadlock Detection: False Deadlock.
 

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