Big Data Insights (Thematic Weekend)

Transcription

1 CEU Business School Big Data Insights (Thematic Weekend) Instructor: Achilles Georgiu (See last page for bio sketch) Class meets (day and time): according to the A1MBA Calendar Classroom: see schedule for details Instructor s Office: Room 214 CEU Business School, Frankel Leó út Office hours: upon prior agreement GeorgiuA@business.ceu.edu Program Manager: Adrienn Olson: olsona@business.ceu.edu Student Services Manager : Aniko Juhasz: juhasza@business.ceu.edu 1. PREREQUISITIES None: computer literacy and basic office software skills are assumed. 2. REQUIRED TEXT & READINGS AND WHERE AVAILABLE A Reading Pack (RP) for this course has been compiled by the instructor. Additional readings, papers and up-to-date articles will be provided as needed. All reading materials will be available on Moodle. Recommended reading / watching: Big Data: Big today, normal tomorrow (ITU-T Technology Watch Report) Explaining Big Data The AI Revolution: How Far Away Are Our Robot Overlords? 3. COURSE DESCRIPTION AND OBJECTIVES Every organisation increasingly recognizes the value of voluminous data and appropriate business analytics. The skills necessary to analyze and act upon insights from data are dispersed among managers, economic analysts, computer engineers and statisticians. Business analytics, especially involving Big Data, can help organizations make smarter and more effective decisions, including, for example, finding ways to increase sales and to cut costs. 1

2 This course will be made up of interactive conceptual presentations and a workshop series with guests who are also teaching in MSc in Business Analytics program. The aim of this course is to give students high level insights based on current and future trends around Big Data and to provide fundamental knowledge and understanding of how Big Data is changing the business environment. 4. MAIN TOPICS Big Data and Data explosion Moving to the new Era of Cognitive computing Industry, development trends, business competitiveness due to Big Data Business Analytics, Smart Systems and Predictive Analytics Generation-D Enterprises and the Chief Data Officers 5. INTENDED LEARNING OUTCOMES Core Learning Area Interpersonal Communication Skills. Technology Skills Cultural Sensitivity and Diversity Quantitative Reasoning Critical Thinking Ethics and Responsibility Management Knowledge and Skills Learning Outcome Students will be able to communicate future trends and business impact of BigData and Cognitive technology Students will understand the structure of smart systems and their impact on industries across the globe Students will have increased understanding and acceptance of moving to the new Era of Homo Informaticus Students will see real world examples how BigData can drive small and larger organizations to success Students will be encouraged to question the applicability of Business Analytics in their everyday business success Students will be motivated to consider the possibilities behind BigData by gaining enough insights Non-specialist managers will have basic knowledge and skills to take better business decisions without relying on untested hypotheses 6. HOW THE CLASS SESSIONS WILL BE CONDUCTED Each class will be a combination of lectures and interactive sessions, incl. guest speaker presentations, student team debates and open discussions. Often students will be asked to briefly summarize in class one of the topics presented. A number of real world examples, cases, and articles will be used to demonstrate the topics discussed. Invited guest speakers will strengthen the real business life focus of the course. 2

3 7. POLICY ON THE AVAILABILITY OF LECTURE NOTES Lecture notes and Power Point presentations will be provided on the day of classes and not in advance. They will be made available in the e-learning system (Moodle) and reside there for the remaining duration of the course. 8. POLICY ON CLASS ATTENDANCE Regular and punctual attendance at every class session is a requirement of all degree programs at CEU Business School. Each class covers material not found in the readings. Furthermore, participation in class discussions is an important part of the learning experience for all students as well as a factor in grading. Any absence may affect your grade. If illness or another unusual circumstance requires missing a class, please do your best to inform me (or, if I cannot be reached, the Program Coordinator) in advance. A grade of AF (Administrative Fail) may be assigned for failure to regularly attend a course, to drop the course in time, or to complete requirements on time. This is a general CEU regulation that the Business School also follows. The AF grade earns no credit, 0 points, and affects your GPA in the same way as a regular F grade. 9. GRADING Due to the structure of the course the grading will be Pass / Fail. In order to pass the participant should be present on all six sections of the course (evidence: signup sheet). Students should actively participate during the class and write a short reflection afterwards. Class activities include: Evidence of preparation, Contributions to class discussion, Bringing real life examples, based on own working experience, Active participation during debates Debate sessions include: In addition, a key objective of the course is to develop the soft skills of students during the debate sessions. Debate teams will be formed at the beginning of the course. Each team will be responsible for the preparation and participation in a debate the last session of the course. The team sizes and number of debates will depend on the number of students in the class. Individual reflection paper: Students will have to send a short reflection paper (1.5-2 pages up to 4000 characters) to the instructor not later than 3 weeks after the last session. Students will have the possibility to choose one of two topics. The topics to be reflected will be presented at the closing part of the course. 3

4 10. ACADEMIC INTEGRITY The Business School expects all students to adhere to the fundamental principles of academic integrity in any and all behaviours associated with their course work and otherwise, as stated in the CEU Honor Code (see Student Handbook). Attempted cheating of all forms is treated extremely seriously and can result in dismissal from the School and University. 11. BRIEF BIO OF THE INSTRUCTOR Achilles Georgiu, director of the MSc in IT Management program and Adjunct lecturer of IT Management and Leadership courses at the MBA programs at CEU Business School. Besides MSc degrees in Computer Sciences and Informatics Management, he has more than 18 years of international and multicultural experience from the field and ample knowledge of standard IT management and control frameworks with special focus on human motivation, team building and performance management. He worked for several international companies and is currently working at IBM as a Senior Consultant and Services Sales representative. 12. COURSE OUTLINE AND SESSION ASSIGNMENTS See final page for details. 4

5 No. Topic and Activities Reading for class session / Homework 1 Course Introduction Agenda, expectations, introduction of Big Data insights (Thematic Weekend). Moving to the new Era of Cognitive computing where Big Data is becoming the new natural recourse. What is Big Data, how can we use it in our everyday life? Chief Data Officer, Generation-D Enterprises 2 Building Smart Systems How smart systems can change industries across the globe? What is the direct and indirect impact of the huge data explosion to our world? We will discover and discuss some real live examples 3 Defining the Cognitive Era How organizations can effectively and efficiently anticipate, assess, introduce, and leverage the huge amount of data. How to make knowledge from the huge amount of data and information, which is mostly noise? How to turn Big Data into our advantage and not seeing it as unscaleable mountain? 4 The role for economic theory in big data business analytics Predictive analytics, and big data, in particular, offer the promise of better business decisions without relying on untested hypotheses. In this block we will argue that there is a role for economic theory in setting up business analytics projects and implementing subsequent business decisions. By showing some examples where purely data-driven decisions have gone awry. 5 Understanding a newborn s cry Lullabond is a mobile / smart watch application that allows you to better understand what your newborn s cry means. Backed with a self-improving algorithm, it gives accurate results for the typical crying reasons such as hunger, tiredness, wet diapers, gas, and several more. How Tesla uses big data to improve products and services A brief overview about different ways of using big data in car industry by going through real life examples. 6 Analysing online comments - Big data in practice In this session we introduce the principles and challenges of collecting huge amount of online and social content. We examine how automated textual data analysis methods (sentiment and semantic analysis) can help to use this data in business decisions. Finally with short case studies we go through online media monitoring and analysis use cases 7 Corporate wisdom Cognitive technology in practice The power of collective intelligence enables enterprises transforming their passive knowledge into practical advice. Companies need to learn how build their own virtual consultant easily taught by their community. 8 Debate Session Student teams will present their debate topics received during the first session of the course. Closing, Wrap Up, Lessons learned Guest: György Bögel Professor of Management at CEU Business School Guest: Norbert Sepp Adjunct Lecturer of Technology Innovation at CEU Business School Guest: Miklos Koren Associate Professor CEU Guest: Gábor Veres Enterpreneur Guest: Péter Boros, Team Manager Purchase - Business Lease Group B.V. Guest: Péter Szekeres - Research Lead, Neticle Technologies Guest: Gergely Szertics CEO Analogy 5