BUSINESS ANALYTICS

The course introduces Business Analytics methods for analyzing business needs, reading data sources and organizing information in data models, visualizing and presenting insights.
The methods will be discussed and illustrated using Business Intelligence software and some business cases.

At the end of the course, students will be expected to have acquired the skills to understand business needs, to measure a business process, to collect data from sources, to organize data in dimensions and measures, to create a business analytics (BA) application and to present the obtained results in a communicative way.
In particular, students should:
1. Knowledge and understanding:
- know the business analytics terminology and concepts;
- understand business requirements;
- understand dimensions and measures to create a data model;
- understand which is the best graphical representation of information
2. Ability to apply knowledge and understanding 
- understand the main aspects to introduce successfully BA (Business Analytics) in an organization;
- know how to create a BA application;
- know how to turn data into actionable insights using created application.
3. Communication 
- know how to present and discuss the achieved results in an effective way for business.

There are no specific prerequisites, the basic knowledge of data management software is useful.

Introduction to Business Analytics as a framework for data-driven management strategies and decisions making.
Descriptive analytics, Predictive analytics, Prescriptive analytics.
Business requirements gathering and analysis: organization aspects and processes measurements.
Data sources analysis: structured and unstructured, small and big data, geographic data, open and internal systems data.
Data organization and governance: data-warehousing and data-lake, data flows, data lineage.
Data modelling: dimensions and measures.
How to create a business intelligence app with data visualization tool as Qlik: dashboarding, analysis and reporting (DAR) methodology.
Use of visual storytelling to communicate insights
How to extend data visualization with statistical tools for predictive and prescriptive analytics
Business cases and real-world applications: examples of dashboards and balanced scorecards

VV.aa. (2018) HBR Guide to Data Analytics Basics for Managers,Harvard Business Review Press
Qlik Sense Guide: https://help.qlik.com/en-US/sense/June2019/Content/Sense_Helpsites/Guides.htm
Pagans Ferran Garcia (2015) Predictive Analytics Using Rattle and Qlik Sense, Packt Publishing

The exam consists of a development of a BA (Business Analytics) software application and results presentation using a dataset assigned by the lecturer.
The exam aims to verify that the student has acquired the concepts of Business Analytics, knows how to use software and knows how to use analytics skills to solve business needs.

Each topic will be developed by using the “Qlik Sense” business intelligence software
For some advanced statistical topics we will use R integration plug in for Qlik Sense.
To go deeper in Qlik Sense use, it’s recommended to attend also BA (Business Analytics) specific Lab.

English

written and oral