37685 - Computational Tools (M-Z)

Learning outcomes

By the end of this course students are able to: - describe the key functions and applications of computational tools in various domains; - explain fundamental concepts such as algorithms, data structures, and computational efficiency; - use computational tools to analyze, model, and interpret data; - create clear and informative visualizations to communicate insights; - exhibit meticulousness in code writing, data handling, and documentation.

Course contents

This course provides students with basic theoretical and practical skills in Business Intelligence, Data Modeling and Data Management to support research and decision-making in business contexts. Emphasis is placed on using Spreadsheet and Database resources effectively, selecting and processing corporate data, and organizing information from diverse corporate sources. Students will learn to analyze business data using spreadsheets and Analisys Databases to compute and visualize indicators to support the decision-making process. The course also explores the computational language techniques needed to synthesize data and support strategic decisions across various corporate domains.

Structure of the course:

1 Introduction to IT Systems, Databases, ERPs, SpreadSheets

2 Basic Excel functions and limitations

3 Pivot Tables and Calculated Fields in Excel

4 Primary keys and join between tables (VLOOKUP)

5 Limits of Excel and Introduction to the Business Intelligence Workflow

6 Power Query and Power Pivot for Excel – How to overcome Excel limitations

7 DAX Introduction to the language to write measures and calculated columns

8 DAX Aggregators and introduction to Iterators

9 Introduction to Power BI Desktop to create a full corporate BI Reporting System

10 How to create a dashboard and automatically refresh data

11 DAX Table Functions, AND and OR conditions.

12 Hints on advanced calculations and nature and purpose of measures and calculated columns

Readings/Bibliography

Turban/Volonino/Wood, Information Technology for Management - International students version 10th edition), 2015, Wiley

Jelen/Alexander, Pivot Table Data Crunching Excel 2016 (2nd edition), 2015, Que Publishing

Teaching methods

The main instructional approaches used in the course are:

- Lectures in laboratory

- Problem-Based Learning on Personal Computers

Assessment methods

Though not compulsory, class attendance and participation in team-work assignments is strongly encouraged.

Component Weight (%)

Final Exam 100 %

- Exam and group project structure:

The final exam is practical at the Computer. Students have to solve different exercises on the course topics and answer two theory open questions. To each exercise a given maximum number of points is associated, and to get it the student has to solve correctly the exercise and all the steps must be justified. The theoretical maximum number of points achievable in case of a perfect exam is 33.

The evaluation of the answers of the exam depends on the correctness, completeness and rigor of the answers

- Exam policy:

Students attend a final test and will be allowed to refuse the mark

Grading scale:

< 18: failed

>=18: pass

Erasmus: at most 20 Erasmus and Overseas students, and 10 UADE students, selected in chronological order, will be admitted to the course and the exam.

Students with disability or specific learning disabilities (DSA) are required to make their condition known to find the best possibile accommodation to their needs.

Teaching tools

Tools, platforms, or resources used during the course:

- Learning platform: Virtuale (virtuale.unibo.it) contains the files developed in each lecture

- Communication tools: Virtuale and emails

- Other digital tools/software: Excel and Power BI

Office hours

See the website of Francesco Bergamaschi