Advanced Database Management Systems for MSBTE I Scheme (V - CO/CM/CW - 22521)

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Unit - I Database Architecture 1.1 Introduction to client-server Database Model : Two-Tier Client server model, Three-Tier Client server model. 1.2 Concurrency Control Techniques : Concurrency control protocols : Locked Based protocols, granting of locks, Two Phase Locking protocol. 1.3 Introduction to parallel databases : Parallel database system architecture, Types of parallelism, Parallel Database Implementation. 1.4 Introduction to distributed databases : Distributed database system architecture, Benefits of distributed database system, Issues with distributed database systems. Unit - II Object Based Databases and XML 2.1 Object Based Databases overview. 2.2 Complex data types. 2.3 Structured types and inheritance in SQL. 2.4 Table inheritance. 2.5 Array and multiset types in SQL. 2.6 Object identity (OI) and reference types in SQL. 2.7 XML : Introduction, structure of XML data, XML document schema, Xpath, XQuery : FLOWER Expressions, Joins, Nested Queries, Sorting of functions, Functions and types. Unit - III Advanced Database Techniques 3.1 Structured versus Unstructured Data. 3.2 NoSQL database concepts : Types of NoSQL databases, NoSQL data modelling, Benefits of NoSQL, Comparison between SQL and NoSQL database system. 3.3 NoSQL using MongoDB : Introduction to MongoDB Shell, Running the MongoDB shell, MongoDB client, Basic operations with MongDB shell, Basic Data Types, Arrays, Embedded Documents. 3.4 Querying with MongDB : find() function, specifying which keys to return, query criteria OR queries, Types of specific querying. 3.5 Aggregation Introduction : Aggregation Pipeline, Aggregation using Map reduce, Single purpose aggregation. Unit - IV Advances in Databases 4.1 Introduction to Data Warehouse : Characteristics, Types of Data Warehouse Architecture, Data Marts, Data Warehousing Lifecycle, Data Warehouse Development. 4.2 Introduction to Data Mining Techniques: Data mining technology and its relation to data warehousing, Association rules, classification and clustering, Applications of data mining. 4.3 Introduction to business Intelligence : Features, frameworks, Types and approaches for machine learning. 4.4 Introduction to Multimedia Databases, Mobile Databases and digital databases. Unit - V Big Data Management 5.1 Big Data. 5.2 Introduction to Hadoop : Building Blocks and Components, Hadoop architecture, HBase, HIVE, Solid-State Drive. 5.3 Cloudera, Oracle cloud. 5.4 Introduction to R-programming.

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Author: [Soudamini Patil, Narendra Joshi, Vrushali R. Sonar, Umesh M. Patil, Yogesh B. Patil, Rohit A. Kautkar] Pages: 164 Edition: 2019 Vendors: Technical Publications