Business Intelligence I

Objectives

The main goal of the Business Intelligence course covered in these two semester units is to give students the knowledge and competency related with decision support capacities provided by Business Intelligence processes, along with supporting Data Warehouse structures. These skills include an awareness of the market forces advocating Digital Transformation initiatives, development methodologies underlying modern Business Intelligence strategies and architectures, along with current information technological development in the fields of Business Analytics, Advanced Data Analysis, and Business Performance Management.

General characterization

Code

200012

Credits

7.5

Responsible teacher

Duarte Nuno Antunes Caracol Barros Rodrigues

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

Basic knowledge in relational databases (SQL). An introductory-level SQL Crash course is offered at the start of the semester, to all students lacking a basic level of knowledge and experience in this subject area.

Bibliography

Ramesh Sharda, Dursun Delen, Efraim Turban (2017) Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, Pearson, ISBN-13: 978-0134633282

Larson, Brian (2017). Delivering Business Intelligence with Microsoft SQL Server 2016 Fourth Edition. Mc Graw Hill, ISBN: 9781259641497

Ralph Kimball, Margy Ross, The Data Warehouse Toolkit, 3rd Edition, 2013, Wiley Publishing

Inmon W. H., Building the Data Warehouse, 4rd Edition, 2005, Wiley Publishing

Imhoff C., Galemmo N., Geiger J., Mastering Data Warehouse Design, 2003, Wiley Publishing

Ponniah, P., Data Warehousing Fundamentals, Wiley Publishing, 2001

Teaching method

This course will include both lectures and labs.

In the lectures we will present the theoretical concepts, case studies and, possibly, some presentations from leading BI vendors. The applied component of the course will take place in the Labs, where students will be shown how to apply the concepts and theories presented in lectures, by leveraging the use of the Microsoft Business Intelligence Platform (SQL Server, SQL Server Management Studio, Visual Studio, along with limited use of Microsoft Azure cloud-based tools) as the teachers demonstrate and provide practical guidance on the joint development of a class project.

In addition, and so as to further reinforce the applied skills and methodologies that the students are learning, they will be required to implement group-based practical projects of their own choosing, as part of the assessment.

Evaluation method

The assessment includes:

a) Project (50%)

b) Final exam (50%)

To successfully complete the course students must obtain a minimum score of 9.5 in the final exam (both seasons), irrespective of marks obtained in a) or b).

Subject matter

LECTURES
T.1 Digital Transformation and Data-Driven Organizations
   T1.1 Digital Transformation
   T1.2 SMAC (convergence of Social, Mobile, Analytics and Cloud)
   T1.3 Industry 4.0
   T1.4 Data-Driven Organizations
T.2 Business Intelligence
   T2.1 Introduction to Business Intelligence
   T2.2 A Framework for Business Intelligence (BI)
   T2.3 Intelligence Creation and Use and BI Governance
   T2.4 The Major Theories and Characteristics of Business Intelligence
   T2.5 Toward Competitive Intelligence and Advantage
   T2.6 Successful Business Intelligence Implementation
   T2.7 Business Intelligence Today and Tomorrow
T.3 Data Warehousing
   T3.1 Data Warehousing Definitions and Concepts
   T3.2 Data Warehousing Process Overview
   T3.3 Data Warehousing Architectures
   T3.4 Data Integration and the Extraction, Transformation and Loading (ETL) Processes
   T3.5 Data Warehouses Development
   T3.6 Real-Time Data Warehousing
   T3.7 Data Warehouses Administration and Security Issues
T4. Data Governance
   T4.1 Principles of data governance
   T4.2 Privacy and Security - General Data Protection Regulation

LABS
LAB 01: Overview of BI I Labs and Project Presentation
LAB 02: Introduction to Data Warehousing
LAB 03: Practical Steps in Building a Data Warehouse
LAB 04: Introduction to the ETL Process
LAB 05: Continuing the ETL Process (Full Load of Staging Area)
LAB 06: Continuing the ETL Process (Enhancing the SA Full Load ETL with Logs)
LAB 07: Completing the ETL Process by Loading SA and DW
LAB 08: Add Conditional Load Possibilities to the ETL
LAB 09: Final review and Power BI exploration of DW

Programs

Programs where the course is taught: