Lecture Notes On DBMS
In computerized information system data is the basic resource of the organization. So, proper organization and management for data is required for organization to run smoothly. Database management system deals the knowledge of how data stored and managed on a computerized information system. In any organization, it requires accurate and reliable data for better decision making, ensuring privacy of data and controlling data efficiently. The contents include: Introduction, Disadvantages of file oriented approach, Database, Why Database, Database Management System(DBMS), Function of DBMS, Advantages of DBMS and disadvantage of DBMS, Database Basics, Three level architecture of DBMS, Database users, Database language, Database structure.
Author(s): Dr. Subhendu Kumar Rath, BPUT, Odisha
127 Pages 
Database Management Systems Lecture Notes
Objective of this note is to understand the basic concepts and the applications of database systems, the basics of SQL and construct queries using SQL and explains the relational database design principles.
Author(s): Malla Reddy College Of Engineering and Technology
329 Pages
Lecture Notes on Fundamental of Database Management Systems
Database is a collection of interrelated data and set of programs can access that system. The contents include: Conceptual Modeling, Relational Approach,Basic Sql Query and Normalization, Transaction Management, Concurrency Control.
Author(s): Ms. K Radhika Assistant Professor, Ms. P Navya Assistant Professor, Department of Computer Science Engineering,Institute of Aeronautical Engineering
95 Pages
The contents include: What is DBMS, The relational data model, Entity-Relationship (E/R)modelling, Relational algebra and relational calculus, SQL, Case Study - Cancer registry for the NHS –challenges, Schema refinement I, Schema refinement II, Schema refinement III and advanced design,On-line Analytical Processing (OLAP), Case Study - Cancer registry for the NHS -Experiences, XML as a data exchange format.
Author(s): Ken Moody, Computer Laboratory, University of Cambridge,UK
88 Pages
This note covers the following topics: Introduction, inductive learning, Decision trees, Rule induction, Instance-based learning, Bayesian learning, Neural networks, Model ensembles, Learning theory, Clustering and dimensionality reduction.
Author(s): Pedro Domingos
NA Pages
This book explains you how to use this document oriented database as a standalone application framework or with high volume, distributed applications.
Author(s): J. Chris Anderson, Jan Lehnardt and Noah Slater
NA Pages
Database Systems The Complete Book
This book covers the following topics: Databases, Automata, Compilers, Operating Systems, Introductory Java, Data Structures, and Data Mining.
Author(s): Hector Garcia Molina, Jeff Ullman and Jennifer Widom
NA Pages
