ICS 422: Data Processing

Description: Role of data processing in organizations, programming practices, ethics, sequential and indexed file processing, report writing, online transaction processing

Objectives

• Students understand different paradigms of processing different types of data.
• Students are able to program data-intensive applications using different data management technologies
• Students understand different approaches in data cleaning
• Students are able to program extract-transform-load processes on data
• Students are able to build and use a data warehouse for advanced data analytics
• Students understand parallel and distributed data processing strategies
• Students understand non-SQL-based data processing technologies

Course Learning Outcomes: See objectives.

Program Learning Outcomes

• a. Students can apply knowledge of computing and mathematics appropriate to the discipline
• b. Students can analyze a problem, and identify and define the computing requirements appropriate to its solution
• c. Students can design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs
• d. Students can function effectively on teams to accomplish a common goal
• e. Students have an understanding of professional, ethical, legal, security and social issues and responsibilities
• i. Students can use current techniques, skills, and tools necessary for computing practice
• j. An ability to use and apply current technical concepts and practices in the core information technologies. [BA IT only]
• k. An ability to identify and analyze user needs and take them into account in the selection, creation, evaluation and administration of computer-based systems. [BA IT only]

Prerequisites: 321 or consent.

Textbook(s): None. Readings will be drawn from articles, tutorials on the internet as well as articles from academic conference papers and journals.

Grading

• Homework Assignments (30%)
• Weekly quizzes (20%)
• Course project (50%)

Schedule

• Week 1: Overview of Data Management Technologies
• Week 2: Relational Database Systems
• Week 3: Semi-structured Database Systems
• Week 4,5: Data Warehousing
• Week 6,7: Parallel Database Systems
• Week 8,9: NoSQL Data Management Systems
• Week 10,11: Streaming Data
• Week 12,13: Map-Reduce and other parallel data processing models.
• Week 14,15: Data Mining
• Week 16: Project Presentations