Databases by Ken Moody
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 
Database Management Systems Lecture Notes
This lecture note covers introduction to database, management system, Introduction to basic concepts of database systems, History of database systems, View of data, Database languages, Database architecture and relational model.
Author(s): University of Anbar
60 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
Database Systems Lecture Notes
This note is designed to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, query optimization, query processing, and transactions. Topics covered includes: The relational model, Schema design, database internals, Database operators and query processing, Indexing and access methods, Buffer pool design and memory management, Join algorithms, Query optimization, Selinger optimizer, Transactions and locking, Optimistic concurrency control, Distributed transactions, Parallel databases, Scientific databases, NOSQL , ORM, DryadLINQ, Streaming databases, database as a service.
Author(s): Prof. Samuel Madden, Prof. Robert Morris, Prof. Michael Stonebraker, Dr. Carlo Curino
NA 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
