Upon successful completion of this course, students are expected to be able to: explain the role of databases in organizations and information systems; use SQL to construct, secure and access the database; explain and apply formal languages associated with the relational database model, including relational algebra, and relational calculus; develop a relational database using database design methodology three main phases: conceptual, logical, and physical design; use formal technique for producing a set of normalized relations that support the data requirements of an enterprise; explain and use the advanced SQL programming language in a DBMS environment; use and develop a distributed DBMSs along with its transaction management and replication techniques; explain and use data warehouse concepts, such as ETL, Data mart and the dimensional approach; relate and implement database managements system in the web technology and mobile environment; define the discipline and process of data mining and CRISP-DM methodology; explain and apply the various data mining techniques; perform methods of data preprocessing and data reduction; and analyze and model data, addressing ethical and technical issues in data mining.
This course introduces the concept of information modeling, which emphasizes the importance of grouping the information into specific categories before it is transferred to the actual database design. Later in this course, an implementation phase is discussed to ensure the students are well aware of any implications that might develop from improper information modeling. In addition, this course also aims to introduce students to the concept of database design by predicting the use of future retrieval systems. Students understand that both a consideration of the data model and awareness of the retrieval system to be applied are required in designing a database. Consequently, new concepts are introduced, such as query processing and optimization, transaction processing concepts, and concurrency control techniques. This will lead students to understand the method of database tuning, functional dependencies, and normalization for RDB that will help them to understand further courses. This course also covers selected issues related to databases such as advanced SQL programming language (SQL/PSM and PL/SQL), cursor and stored procedures, techniques in transaction management, distributed DBMSs and replication, as well as data-warehousing concepts. The implementation of web technology and databases along with mobile databases will also be highlighted. This course also provides an introduction to the concepts and common practices in the field of data mining. Students will be exposed to the various data-mining techniques that can be used to describe, analyze, and model data. Weka, a leading data-mining software, will also be introduced and used to apply various data-mining techniques to solve business problems.
Pre-requisite(s): Applied Research and Linear Algebra
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