
Business Intelligence I
Code
200012
Academic unit
NOVA Information Management School
Credits
7.5
Teacher in charge
Miguel de Castro Simões Ferreira Neto
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
The main goal of the Business Intelligence course that we now initiate is to give the students the knowledge and competences related with decision support capacities provided by the Business Intelligence processes and the supporting Data Warehouses, including the Business Intelligence development methodologies and the nowadays available information technologies in the field of Business Analytics and Performance Management.
By the end of the courses (BI I & II), the students will be able to:
- Understand the BI process and the factors contributing to maximize business value
- know the most important Business Intelligence / Data Warehouses business applications
- Identify the analytic applications key indicators in business context
- know the most relevant approaches to Data Warehouses building
- Understand the relations between Business Intelligence and Data Warehousing
- Understand the role of analytic applications, of business performance management and visualization tools
- Know the Business Intelligence infra-structure components - people, processes and technologies
Prerequisites
Databases (SQL)
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
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
Bibliography
Sharda, Delen & Turban (2014). Business Intelligence: A Managerial Perspective on Analytics, 3rd Edition, Prentice Hall, ISBN-13: 9780133051056.
Larson, Brian (2012). Delivering Business Intelligence with Microsoft SQL Server 2012 Third Edition. Mc Graw Hill, ISBN: 0071759387
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 examination, irrespective of marks obtained in a) or b).
Courses
- Free Mover
- PostGraduate in Information Analysis and Management
- PostGraduate in Information Systems Governance
- Mobilidade Universitária
- Mobilidade Universitária
- Post-Graduation in Knowledge Management and Business Intelligence
- PostGraduate Information Systems and Technologies Management
- Laboral - Gestão do Conhecimento e Business Intelligence
- Free Mover
- PostGraduate Digital Marketing and Analytics
- PostGraduate in Smart Cities
- Specialization in Marketing Intelligence
- PostGraduate Risk Analysis and Management
- PostGraduate in Digital Enterprise Management
- Specialization in in Information Analysis and Management
- PostGraduate in Knowledge Management and Business Intelligence
- Specialization in Knowledge Management and Business Intelligence – Working Hours Format
- PostGraduate in Marketing Intelligence
- Specialization in Information Systems and Technologies Management
- Specialization in Knowledge Management and Business Intelligence
- PostGraduate in Knowledge Management and Business Intelligence
- Mobilidade Universitária
- PostGraduate Marketing Research e CRM
- Specialization in Risk Analysis and Management
- Laboral - Gestão do Conhecimento e Business Intelligence
- Specialization in Marketing Research and CRM