Business Intelligence I

General characterization

Prerequisites

Basic knowledge in Databases (SQL). A SQL Crash course is offered to the students who don't have this previous knowledge in the beginning of the semester.

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 lectures and labs.
In the lectures will consist of theoretical concepts, case studies and presentations from leading BI vendors.
The applied component of the course will include several computer labs where students will apply the concepts and theories presented in lectures leveraging the Microsoft Business Intelligence Platform (SQL Server, SQL Business Intelligence Development Studio).
In this context the students will have to develop a project.

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

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

L.1 Business Intelligence Labs Presentation

               Microsoft BI Platform Presentation

L.2 SQL Server Management Studio

                Relational Data Bases Overview

                Relational Data base Development

L.3 SQL Business Intelligence Development Studio

                Introduction to Data Warehouse Systems.

                OLTP versus OLAP

                Metadata.

                Microsoft Data Warehousing Tools ? First Steps

L.4 SQL Server Integration Services

                ETL Process ? Basic

                Microsoft SQL Server Integration Services ? Basic

L.5 SQL Server Management Studio

                Multidimensional Models.

                Fact Tables and Dimensions

                Design and Development of Dimensional Schemas ? Data Warehousing

L.5 SQL Server Integration Services

                ETL Process ? Advanced

                Microsoft SQL Server Integration Services ? Advanced

Programs

Programs where the course is taught: