Syllabus M.C.A. (Sem-IV), Paper-IV Advanced Database Techniques 1. Parallel and Distributed databases Architecture for Parallel databases Parallelizing Individual operations Parallel query Evaluation Introduction to DDBMS Architecture of DDBs Storing data in DDBs Distributed catalog management Distributed query processing Distributed concurrency control and recovery Transaction Processing 2. Data warehousing Data Marts Getting data into the warehouse Extraction Transformation Cleansing Loading Summarization Meta data Data warehousing & ERP Data warehousing & KM Data warehousing & CRM 3. Planning & Project Management How is it different? Life-cycle approach The Development Phases Dimensional Analysis Dimensional Modeling Star Schema Snowflake Scheme 4. OLAP
2 OLAP Architecture Relational OLAP Multidimensional OLAP Relational vs. Multidimensional OLAP Web based OLAP Major features & functions Drill-Down and Roll-Up Slice-and-Dice or Rotation Implementation techniques for OLAP Join Indexes 5. Data Mining Introduction Data mining algorithms, Clustering, Classification, association rules. Knowledge discovery: KDD process Decision trees Neural Networks Search Engines Characteristics Functionality Architecture Ranking of Web pages The search engine Industry The Enterprise Search Case Study: The analysis of a large scale hyper textual search engine. 6. Object Databases Systems Introduction User-defined ADTs Structured types Object, object identity and references Inheritance Database design for ORDBMS New Challenges in implementing ORDBMS Storage & access methods Query processing & Optimization OODBMS
3 Comparison between OODBMS and ORDBMS 7. Database Security Term Work: Term work/Assignment: Each candidate will submit a journal in which at least 10 assignments based on the above syllabus and the internal test paper. Test will be graded for 10 marks and assignments will be graded for 15 marks. References: 1. Raghu Ramakrishnan, Johannes Gerhke, “Database Management Systems” McGraw Hill. 2. Decision support & database system –Efrem G. Mallach. 3. Datawarehousing fundamental – Paulraj Ponniah Wiley. 4. Introduction to data mining with case studies – G.K. Gupta. 5. Elmasri and Navathe, “Fundamentals of Database Systems”, Person Education. 6. Korth, Silberchatz, Sudarshan, “Database System Concepts” Mc Graw Hill. 7. Peter Rob and Coronel, “Database Systems, Implementation and Management”, Thomson Learning. 8. Data Warehousing (OLAP) S. Nagabhushana New Age. Design,
4 1 PARALLEL AND DISTRIBUTED DATABASES Unit Structure: 1.1 Architectures for Parallel Databases 1.2 Parallel Query Evaluation 1.2.1 Data Partitioning 1.2.2 Parallelizing Sequential Operator Evaluation Code 1.3 Parallelizing Individual Operations 1.3.1 Bulk Loading and Scanning 1.3.2 Sorting 1.3.3 Joins 1.4 Distributed Databases 1.4.1 Introduction to DBMS 1.4.2 Architecture of DDBs 1.5 Storing data in DDBs 1.5.1 Fragmentation 1.5.2 Replication 1.5.3 Distributed catalog management 1.5.4 Distributed query processing 1.6 Distributed concurrency control and recovery 1.6.1 Concurrency Control and Recovery in Distributed Databases 1.6.2 Lock management can be distributed across sites in many ways 1.6.3 Distributed Deadlock 1.6.4 Distributed Recovery A parallel database system is one that seeks to improve performance through parallel implementation of various operations such as loading data, building indexes, and evaluating queries. In a distributed database system, data is physically stored across several sites, and each site is typically managed by a DBMS that is capable of running independently of the other sites.