DATA SCIENCE AND MANAGING BIG DATA
- Course
- BUSN555 - DATA SCIENCE AND MANAGING BIG DATA
- Department
- Master of Business Administration - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
- Keywords
- -
Course Description
-
DATA SCIENCE AND MANAGING BIG DATA
Evaluation Tools (Active Term)
No evaluation items have been defined.
Course outcomes
- 01 Basics of Data Analytics and the concept of Big Data
- 02 To Understand Patterns, Causes Alghorithms
- 03 Data Management and How to Prepare Data
- 04 Getting Graphics and Seeing Data
- 05 By real life applications, deepening of the understanding
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Orientation to the course/ Introduction |
| Week 2 | What is the Big Idea |
| Week 3 | Looking for Patterns and Causes |
| Week 4 | Algorithms - Managing Complexity |
| Week 5 | The Cycle of Data Management |
| Week 6 | Preparing the Data |
| Week 7 | New Statistics and Hodoop |
| Week 8 | Regression Analysis |
| Week 9 | Mid-Term Exam |
| Week 10 | Getting Graphic and Seeing the Data |
| Week 11 | Expected Value Approach |
| Week 12 | Quantifying Quality |
| Week 13 | Braketology |
| Week 14 | Overfitting, Anomalies and Breaking Trends |
| Week 15 | Security Issues and the Future of Big Data |
Reference Books & Course Materials
- 01 Big Data. Hurwitz, Nugent, Hlper, Kaufman. 2013, Wiley
- 02 Harness The Power of Big Data. Zikopoulos, 2013, McGraw Hill
- 03 Hadoop. Roos, Zikopoulos, Melynyk, Brown, Coss. 2014. Wiley
- 04 All the PPTs and other material conveyed through MOODLE
Learning Outcomes
- L01 Basics of Data Analytics and the concept of Big Data
- L02 To Understand Patterns, Causes Alghorithms
- L03 Data Management and How to Prepare Data
- L04 Getting Graphics and Seeing Data
- L05 By real life applications, deepening of the understanding
Program Outcomes
- Demonstrate advanced knowledge of core concepts and theoretical frameworks in Management Information Systems, and apply them to develop innovative models that reflect current advancements in the field.
- Analyze complex organizational problems and design integrated information systems solutions by applying advanced MIS knowledge and synthesizing multiple theoretical perspectives.
- Develop and manage database systems and data-driven applications that ensure effective storage, retrieval, and use of organizational data in real-world contexts.
- Utilize data analytics, business intelligence tools, and data visualization techniques to extract actionable insights and support strategic, data-driven decision-making.
- Evaluate and apply emerging technologies such as AI, IoT, and Blockchain to drive digital transformation, enhance organizational performance, and formulate original research inquiries.
- Conduct independent and collaborative research using appropriate methodologies, and communicate findings effectively through scholarly writing and presentations suited to diverse audiences.
- dentify and address ethical, legal, and societal implications in the research, development, and use of information technologies, adhering to scientific and professional standards.
- Collaborate effectively in multidisciplinary teams and demonstrate leadership in addressing complex technology-driven challenges.
- Apply project management methodologies and tools to plan, execute, and monitor IT projects within organizational settings.
- Develop and integrate information systems that align with organizational goals and strategies, supporting innovation and sustainable growth.
- Perform comprehensive systems analysis and design, including requirements gathering, modeling, prototyping, and evaluating enterprise system architectures such as ERP, CRM, and SCM.
- Assess and mitigate organizational information security risks by applying appropriate principles, technologies, and best practices in cybersecurity.
Po-Lo Matrix
| LO | Average | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| L01 | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L02 | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L03 | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L04 | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L05 | - | - | - | - | - | - | - | - | - | - | - | - | - |