Business Analytics: Fundamentals of Decision Making (2235.YR.000798.1)

General information

Type:	OBL	Curs:	1	Period:	S semester
ECTS Credits:	2 ECTS

Teaching Staff:

Group	Teacher	Department	Language
Year 1	Joren Gijsbrechts	Operaciones, Innovación y Data Sciences	ENG

No prerequisites needed

No previous knowledge needed

Why is learing about Business Analytics and Decision-making important?
Advanced Data Analytics is the next frontier for productivity, innovation and competition. Digitalization is fully taking place in private and public sectors generating vast amounts of relevant data. Data is the new oil of the economy, and this course is about extracting value from data.
On the other hand, there is and will be a significant shortage of analytical talent both in a technical and management positions. This course is not about becoming a data scientist but about becoming a manager that deeply understands the potential of data anlytics to solve real business needs. It will become key for managers to be able to talk the same language as data scientists. The best way to master in leading and managing Big Data teams is to fully understand what they are doing. This new skill will be needed in all stages of a company and for all different departments.
The main objective of this course is to educate yourself to be able to improve decision-making in any discipline and organization by using business analytics. We will learn how to use existing platforms to perform many data analytic tasks without requiring programming skills.

The objective of this course is therefore to introduce concepts of Big Data and business analytics, focussing in particular on the interpretation and validity of the results that are obtained as well as on how to use them to create new strategies. To this end, we will introduce RapidMiner Studio which will provide us with a platform for statistical and Machine Learning tasks. At the end of the course, students should:
- Be familiar with Big Data and Advanced Analytics.
- Be acknowledgeable of how companies are leveraging data techniques to outperform.
- Understand the very basics of statistics applied to business and decision-making
- Be able to solve business cases by applying Big Data, Advanced Analytic techniques and Machine Learning.
By the end of the course, participants are expected to have acquired the Big Data fundamentals and be capable of analyzing a Business Analytics problem. They should be able to understand, discuss and define Big Data and analytics strategies for real business situations.

1. Session 1: Business Intelligence and Data - Understand the basics of an analytics and business intelligence system - Align a business intelligence system with the strategy of the organization - Highlight the challenges of their implementation and application

2. Session 2: Taking decisions with data - How data can help to align the business of a company - How to interpret data information in companies - Take decisions with data

3. Session 3: Industry and Services 4.0 - Technologies and their value in Industry and Services 4.0 - How to address and deal with an analytics project - Challenges of Industry and Services 4.0

4. Session 4: BigData in organizations - Advantages and disadvantages of BigData - How to implement a BigData project - The value of BigData

5. Session 5: Machine learning in practice - What machine learning is - Types of machine learning - Practicing machine learning with different algorithms

The course format and methodological approach are based on a combination of explanations and practical parts with business cases, simulations and workshops. During the sessions, participants will be provided with the material needed to follow this course. The material includes both the theoretical content of the different subjects to be discussed and the data needed to practice the concepts learned.
The main objective of the course will be the resolution of a business case which will be presented at the beginning of the course.
Participants will be provided with real datasets for practice and will work in groups to solve the business case by applying quantitative methods. In each session, groups will be provided with some challenges related to it that they will have to solve before the following session.
The course is divided into five sessions to cover the following topics:
1. Business Intelligence and Data
2. Taking decisions with analytics
3. Industry and Services 4.0
4. BigData in organizations
5. Machine Learning in practice

Students will be grouped into teams to work together on practical exercises. They will be asked to solve different workshops during the course.
Students will have to make an individual assignment at the end of the course to apply all the contents and skills learned.
Students will be provided with extra help and specific tutorial sessions to maximize their findings and results.
All students will be graded using the same criteria, no matter their role.
Students may use their laptops/tablets during the lecture/practice sessions ONLY for the course activities.

ASSESSMENT BREAKDOWN

Chen, Hsinchun; Chiang, Roger H. L.; Storey, Veda C. "BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT"; MIS QUARTERLY; Pages 36-4; 2012
Chui M, Löffler M, Roberts R. "The Internet of Things"", and Roger, McKinsey Quarterly 2010 Number 2" Competing through data: Three experts offer their game plans. McKinsey Global Institute. Octubre 2011"
Davenport, Thomas H. "Big data at work: dispelling the Myths, Uncovering the Opportunities".2014. ISBN: 9781422168165"
Marr, Bernard. "Big Data: using smart Big Data, analytics and metrics to make better decisions and improve performance". 2015. ISBN: 9781118965832"
Sathi, Arvind. "Engaging customers using big data".2014. ISBN: 9781137386182

Group	Teacher	Department
Year 1	Joren Gijsbrechts	Operaciones, Innovación y Data Sciences