J009 Data Quality Management Seminar

Faculty of Informatics
Autumn 2017
Extent and Intensity
0/2/0. 1 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. Mouzhi Ge, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Eva Hladká, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics
Timetable
Wed 22. 11. 14:00–17:50 A220, Wed 29. 11. 14:00–17:50 A220, Mon 4. 12. 13:00–17:50 A321
Prerequisites
Database Design and Data Modelling
Basic statistics or software experience like using SAS, R, SPSS is preferred
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
This course is designed to let students learn practical and scientific knowledge of data quality management. The main objective is to exploit the techniques used in data quality management and data integration. The course will also provide theoretical knowledge of data quality management and the real-world system implementation guidelines to students such as Talend DI and DQ. The students will learn and discuss the applications according to the case studies in ETL with Talend software.
Syllabus
  • Data quality management
  • Data quality dimensions
  • Big Data quality
  • Master Data Management
  • Talend Software: DI and DQ
  • Data quality assessment
  • ETL and Data Integration
  • Data quality costs
  • Data cleansing
  • Data quality management strategy
  • Data analytics
  • A/B test in practice
  • Delone and Mclean IS model
  • Optimizing Information Value
  • Information Lifecycle Concepts
  • Data modelling in different domains
  • Data quality and smart city
Teaching methods
paper reading, discussion and student presentation
Assessment methods
the students need to perform a written exam. The writen exam consists of 7 questions, in which 6 questions are with corresponding answers and 1 question is open. In the open question, the student can design and write down their own idea, thinking, and argument about this question.

Question 1 (5%)
Question 2 (5%)
Question 3 (10%)
Question 4 (10%)
Question 5 (20%)
Question 6 (20%)
Question 7 (open question, 30%)

Answer's correctness that is more than 60% will be considered as a pass to the exam.
Language of instruction
English
Further comments (probably available only in Czech)
The course is taught only once.
The course is also listed under the following terms Autumn 2018.
  • Enrolment Statistics (Autumn 2017, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2017/J009