中国科学院大学 SCEE

Prerequisites: Data Structure, Principles of database systems, Programming
Aims & Requirements: This course is the basic course for postgraduates of Pattern Recognition and Intelligent System, also can be used as a graduate professional basic course for other majors. This course is an advanced course of database technology, focused on database design, development and programming. This course will also tell students other commonly used database technology, such as data warehousing, OLAP, cloud computing, data management technology and so on. After completing this course, students should be: (1) Proficiency in the use of database modeling methods and modeling tools; (2) Master the design method of data architecture and metadata, familiar with the use of data management tools; (3) Familiar with and master the using method of the typical database management systems; (4) Master the design
and program methods of database application; (5) Master the basic concepts of data warehousing, data warehouse modeling methods and understand the existing major commercial and open source data warehousing tools (6) Master the online analytical processing (OLAP) method and the use of typical OLAP tools; (7) Understand the new technology of cloud computing in data management. This course let students know well about the database and the commercial and open source tools, laid a good foundation for students who will make research in the field of database technology and application.

Chapter 1 Review of theoretical knowledge of relational database
Relational data model, relational algebra, data dependencies, relational database paradigm.
Chapter 2 Relational database modeling methods and modeling tools The use of ER model, EER model, Power designer, ERStudio, Erwin and the use case analysis of data model.
Chapter 3 Data architecture and metadata design Data architecture design, metadata management with international standards, metadata design and management tool (Advantage Repository, Metastage, SuperGlue, carnation, etc.), DAMA (Data Management International) introduced.
Chapter 4 Oracle database management system Oracle 10g architecture, install Oracle 10g, create an Oracle database, user security management
Chapter 5 Microsoft SQL Server database management system Microsoft SQL Server 2008 Introduction, Microsoft SQL Server 2008 installation, Create a SQL Server database, System security management.
Chapter 6 MySQL open source database management system MySQL 5.1 Introduction, The MySQL 5.1 installation, Create a MySQL database, Users and data security.
Chapter 7 Database application design and programming The database application design steps, the database application programming and programming steps, the connection between the application and database management system access methods, case studies.
Chapter 8 Data warehouse The basic concepts of data warehousing, data warehouse architecture, data warehouse model (star schema, snowflake model), data warehouse construction process and project management, mainstream ETL tool, the mainstream data warehouse products, the mainstream front-end display tools, the data warehouse application case studies.
Chapter 9 Online analytical processing (OLAP) Relations and differences between OLAP and OLTP, the OLAP analysis methods,
slice, rotate, drill, the use of the Microsoft Analysis Service, the use of Brio.
Chapter 10 Cloud computing in data management technology Large-scale data center construction and management techniques, IBM, HP, Cisco's large-scale data center solutions. Virtualization, MapReduce, BigTable, a distributed file system (Google File System, GFS; the Hadoop the File System, HDFS) and other
technologies.

Xu Jungang. Database technology lecture notes, GUCAS, 2010.

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