Universidade Nova de Lisboa

Universidade Nova de Lisboa

NOVA Information Management School

Business Intelligence II

Code

200013

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 II 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.

Prerequisites

Business Intelligence I

Subject matter

T.1 - Business Analytics and Data Visualization
1.1 Introduction to the field of Business Analytics ( BA )
1.2 Online Analytical Processing ( OLAP )
1.3 Reports and Queries
1.4 Multidimensionality
1.5 Advanced Business Analytics
1.6 Data Visualization
1.7 Geographic Information Systems
1.8 Business Intelligence real-time decision support and automated Competitive Intelligence
1.9 Web Analytics : Web Intelligence and Web Analytics
1.10 Use, Benefits and Results of Business Analytics
 
T.2 - Data, Text and Web Mining
2.1 Concepts and Applications of Data Mining
2.2 Concepts and Applications of Text Mining
2.3 Concepts and Applications of Web Mining

T.3 - Business Performance Management
3.1 Introduction to Business Performance Management ( BPM )
3.2 Strategy
3.3 Planning
3.4 Monitoring
3.5 Acting and adjusting
3.6 Performance Measurement
3.7 BPM Methodologies
3.8 Architecture and applications of BPM 
3.9 Performance Dashboards
3.10 Business Activity Monitoring ( BAM )
 
T.4 - Information Dashboard Design
4.1 Dashboards
4.2 Dashboard Design Challenges
4.3 Dashboard Design Best Practices
4.4 Information Design
4.5 Bad Practices in Dashboard Design
4.6 Categorizing Dashboards
4.7 Typical Dashboard Data
4.8 Data Visualization Tips
 
LABORATORIES
 
L.1 - Course presentation
Project features presentation and preparation
Review of Business Intelligence I subjects

L.2 - Building OLAP cubes in SQL Server Analysis Services – Basic Level I
Building Dimensions and Hierarchies
Parent Child Hierarchies

L.3 - Building OLAP cubes in SQL Server Analysis Services - Basic Level II
Building Measures in an OLAP Cube
OLAP Cubes configuration
Perspectives
Partitions

L.4 - Building OLAP cubes in SQL Server Analysis Services – Advanced Level I
Advanced configuration OLAP Cubes
Integration of Multiple cubes
MDX – The OLAP programing language
 
L.5 – Building Data Mining models in SQL Server Analysis Services
 
L.6 – Building reports in SQL Server Reporting Services – Basic Level I
SSRS Features presentation
Building basic reports in SSRS
   Data Sources Tool
   Design Tool
   Layout Tool
 
L.7 - Building reports in SQL Server Reporting Services – Advanced Level
Advanced reports configuration
Other reporting tools
The beauty of Excel and SSAS integration
 
L.8 - Other reporting tools
Excel analytical features
Power Pivots
Power Views
Power Maps
Power BI
Data Zen

Bibliography

Turban E.; Sharda R.; Dursun D. and King D. (2011). Business Intelligence: a managerial approach. Second Edition. Prentice Hall, ISBN: 013610066X. ; Howson, C. (2008). Successful business intelligence : secrets to making BI a killer app. McGraw Hill. ISBN 978-0-07-149851-7; Few, Stephen (2006). Information Dashboard Design: The Effective Visual Communication of Data. Sebastopol, CA: O¿Reilly Media. ISBN 0596100167; Eckerson, Wayne W. (2006). Performance Dashboards: Measuring, Monitoring, and Managing Your Business. Hoboken, NJ: John Wiley & Sons. ISBN 0750661747; 0

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
b) Final Exam
Final grade calculated based on the following formula:
a) 50%
b) 50%

Courses