Enrollment year
2019/2020
Academic discipline
ING-INF/05 (DATA PROCESSING SYSTEMS)
Department
DEPARTMENT OF ECONOMICS AND MANAGEMENT
Course
INTERNATIONAL BUSINESS AND ENTREPRENEURSHIP
Curriculum
Digital Management
Period
1st semester (28/09/2020 - 22/12/2020)
Lesson hours
22 lesson hours
Activity type
WRITTEN AND ORAL TEST
Prerequisites
Basic computer skills.
Bringing your own laptop is required for the practical part of the course.
Learning outcomes
In this course you will learn basic analytic methods and analyze case studies on organizations that successfully deployed these techniques. The mian part of the course will focus on mastering Excels skills and application of BA techniques
Upon successful completion of this course you will be able to:
- name challenges to decision making and understand how business analytics help to overcome them
- identify, evaluate, and capture business analytic opportunities that create value
- use MS Excel to analyse and present the data in an EFFICIENT way.
Course contents
During the course, we will cover several topics:
- Introduction to Business Analytics
- Decision-making biases
- Types of Business Analytics
- Sources of data
- Problem-solving with Business Analytics
The main focus will be put on Excel skills:
- Formatting
- Functions
- Worksheet and Workbook Management
- Visualization, Sorting, and Filtering Data
- Summarizing Data with Pivot Tables
- Comprehensive analysis
Teaching methods
Flipped class
Lectures
In-class practical exercises
Case study discussion
(Depending on the development of the COVID-19 epidemy and the sanitary norms, this can change. Part of the course or all the lessons may be delivered online.
In any event, class materials and recordings will be delivered online, permitting students in remote locations to follow the course).
Reccomended or required readings
Required software:
[details and instructions will be provided in class]
- MS Excel (latest version, student license is enough)
- reimageIT (access through RedShelf)
- Slack (used for communication and course anouncements)
- POPin
Complementary readings:
- Marr, B., (2017) Data Strategy, Kogan Page.
- Rudder, C., (2014) Dataclysm. Who We Are When We Think No One’s Looking, Fourth Estate Ltd.
- C. Nussbaumer Knaflic, C., (2015) Storytelling with Data, Wiley.
Assessment methods
Attending students:
Written exam (practical skills only), case study analysis and class discussion.
Non-attending students:
Written exam.
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