IT34 - Advance Database Management System
Objective:
To study the further database techniques beyond which covered in the second year,
and thus to acquaint the students with some relatively advanced issues. At the end
of the course students should be able to: gain an awareness of the basic issues in
objected oriented data models, learn about the Web-DBMS integration technology
and XML for Internet database applications, familiarize with the data-warehousing
and data-mining techniques and other advanced topics
1 OODBMBS & ORDBMS
1.1Overview of Object-Oriented concepts &
characteristics
1.2 Objects, OIDs and reference types
1.3 Database design for ORDBMS
1.4 Comparing RDBMS, OODBMS &
ORDBMS
2 Advance Database Management System –
Concepts & Architecture
2.1 Spatial data management
2.2 Web based systems
Overview of client server architecture,
Databases and web architecture, N-tier
Architecture, Business logic – SOAP
2.3 Multimedia databases
2.4 Mobile database
3 Parallel databases
3.1 Introduction
3.2 Parallel database architecture
3.3 I/O parallelism
3.4 Inter-query and Intra-query parallelism, Interoperational
and Intra-operational parallelism
3.5 Design of parallel systems
4 Distributed Databases
4.1 Introduction,
4.2 DDBMS architectures
4.3 Homogeneous and Heterogeneous
Databases
4.4 Distributed data storage,
4.5 Distributed transactions
4.6 Commit protocols
4.7 Availability
4.7 Concurrency control & recovery in distributed
databases,
4.8 Directory systems
5 Knowledge base Systems
5.1 Integration of expert in database
application & object database overview
6 Data Warehousing
6.1 Introduction to Data warehousing,
6.2 Architecture
6.3 Dimensional data modeling- star, snowflake
schemas, fact constellation
6.4 OLAP and data cubes
Operations on cubes
6.5 Data preprocessing -need for preprocessing,
data cleaning, data integration and
transformation, data reduction
7 Data Mining
7.1 Introduction to data mining
7.2 Introduction to machine learning,
7.3 Descriptive and predictive data mining, 6.4
outlier analysis, clustering –
7.5 k means algorithm,
7.6 Classification - decision tree, association
rules - apriori algorithm,
7.7 Introduction to text rnh.mg, Bayesian
classifiers.
8 Information Retrieval & XML data
8.1 Introduction to information retrival
8.2 Indexing for Text search
8.3 Web search engines
8.4 Managing text in DBMS
8.5 Data model for XML
8.6 XML DTD's,
8.7 Domain specific DTD's
8.8 Querying XML data
Reference Books
1. Database system concepts'*, 5th Edition –by Abraham Silberschatz, Henry Korth, S,
Sudarshan, (McGraw Hill International )
2. Data Mining: Concepts and systems'*, by Jiawei nan, Micheline Kamber, (Morgan
Kaufmann publishers )
3. Database systems : "Design implementation and management", by Rob Coronel, 4th
Edition, (Thomson Learning Press)
4. Database Management Systems by Raghu Ramkrishnan, Johannes Gehrke Second
Edition, (McGraw Hill International )
5. Database Management System by Alexis Leaon, Mathews Leon, (leon press)
6. Fundamentals of Database Systems by Remez Elmasri , Shamkant Navathe
Reference http://www.unipune.ernet.in/stud_info/Syllabi/Syllabus_2008.html
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