In this course, you will learn basic analytic methods and analyse case studies on organizations that successfully deploy these techniques. The main part of the course will focus on mastering Excel skills and the 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 Prerequisites
- Basic computer skills. - Students should bring their own laptops for the practical part of the course
Teaching Methods
- Flipped classes - Lectures - In-class practical exercises - Case study discussion
Assessment Methods
Attending students: - Written exam (practical skills only)
Texts
Required software: [details and instructions will be provided in class] - MS Excel (latest version, student license is enough) - JASP (https://jasp-stats.org/) Complementary readings: - Panneerselvam R., Business Statistics Using Excel: A Complete Course in Data Analytics (English Edition) (2023) Routledge. - 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.
Contents
During the course, we will cover several topics: - Introduction to Business Analytics - Decision-making biases - Types of Business Analytics - Sources of data - Data visualisation - Problem-solving with Business Analytics The main focus is on Excel skills such as: - Formatting - Functions - Worksheet and Workbook Management - Visualization, Sorting, and Filtering Data - Summarizing Data with Pivot Tables - Comprehensive analysis
