BI415 – Managing Big Data
Master of Science in Business Intelligence and Data Analytics
Core Course
BI415 – Managing Big Data
Course Unit Code: BI415
Type Of Unit: Core
Level of Course Unit: Second cycle
Year of Study: First
Semester: On demand
Number of ECTS Credits: 6
Class Contact Hours: 28
Mode of Delivery
Face to Face
Prerequisites
None
Course Objectives
The advancements of IT storage, processing, computation and sensing technologies added new complexity dimensions to the widely used statistical and machine learning based techniques used so far in data analysis. Companies and organizations store huge volumes of data of a variety of formats and structures, coming in at different velocities, adding further complexities to the problem of data analysis. This course will teach the students the value that could be extracted from large datasets (Big Data) in order to improve the decision making capabilities in an enterprise. By completion of this course, the students will be equipped with both business-oriented and technical skills related to the world of Big Data. They will acquire knowledge around state-of-art tools used in Big Data analytics such as Hadoop, Pig and Hive.
Learning Outcomes
- Understand the value of Big Data, as well as fundamental properties like velocity, variety, veracity and volume.
- Understand the complexities involved in Big Data Science related projects.
- Demonstrate understanding of the different data types un-modelled, multi-structured, un-structured etc.
- Acquire technical capabilities for storing large datasets using state-of-the-art architectures and software.
- Acquire technical capabilities for querying large datasets for data mining and analytics purposes.
Course Content
Course Features
Planned learning activities and teaching methods
lectures, group work, lab work, role playing, project-based learning, homework
Assessment methods and criteria
10% Class participation
50% Individual Assignments
40% In-class examination
Language of Instruction
English
Work Placement(s)
Not applicable
Readings
Required Reading:
1. Bernard Marr. Big Data: Using Smart Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance. Wiley, 2015.
2. Tom White. Hadoop: The Definite Guide. O’Reilly (4th Edition), 2015.
Recommended Reading:
Textbooks
3. Cindi Howson. Successful Business Intelligence. Unlock the value of BI and Big Data. Mc Graw Hill Education (2nd Edition), 2013.
Research Articles:
4. Chen Hsinchun, Roger Chiang and Veda Storey. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, Vol. 36(4), p1165- 1188,2012.
5. Bart Baesens, Ravi Bapna, James Marsden, Jan Vanthienen and Leon Zhao. Transformational Issues of Big Data and Analytics in Networks Business. MIS Quarterly. Vol. 40(4), p807-818, 2016.
6. Andrew Mcafee and Erik Brynjofsson. Big data: The Management Revolution. Harvard Business Review, October 2012, 2012.
7. Maxwell Wessel. You don’t need big data – You need the Right Data. Harvard Business Review, November 2016, 2016.
English (UK) 
Ελληνικά