Masters Programs Course Syllabus

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1 [SEMESTER].[HALF] [SCHOOL YEAR] B U S I N E S S I N T E L L I G E N C E INSTRUCTOR: MIGUEL DE CASTRO NETO CONTACT: mneto@novaims.unl.pt SHORT BIO: OFFICE HOURS: tbd GRADER: tbd CONTACT: tbd 1. COURSE DESCRIPTION AND CONTENT The main goal of the Business Intelligence course 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, Data Visualization and Performance Management. This course will include lectures and labs. The lectures will include theoretical concepts, case studies and presentations from leading BI vendors and real world BI projects. The applied component of the course (the labs) will include several computer labs where students will apply the concepts and theories presented in lectures supported by the Microsoft Business Intelligence Platform. In this context the students will have to develop a group project.

2 2. LEARNING GOALS By the end of the courses, 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; In this course success depends on a number of factors: Basic knowledge of databases / SQL; Attend classes; Work during the semester and not only when exams are about to start; Develop the course project during the semester, making the most of the practical classes; Read the suggested references. 3. COURSE STRUCTURE 1. Business Intelligence 1.1. Business Intelligence Framework 1.2. Architecture and Components of Business Intelligence ( BI ) 1.3. Creation and use of intelligence and governance of BI 1.4. Key theories and features of Business Intelligence 1.5. Competitive Intelligence 1.6. Implementation of Business Intelligence 1.7. The future of Business Intelligence 2. Data Warehousing 2.1. Definitions and concepts of Data Warehousing 2.2. The process of Data Warehousing 2.3. Data Warehousing Architectures 2.4. Data Integration and ETL processes - Extraction, Transformation and Loading 2.5. Development of Data Warehouses 2.6. Data Warehousing in real time 2.7. Administration and Security of Data Warehouses 3. Business Analytics 3.1. Introduction to the field of Business Analytics ( BA ) 3.2. Online Analytical Processing ( OLAP ) 3.3. Reports and Queries 3.4. Multidimensionality

3 3.5. Advanced Business Analytics 3.6. Data Visualization 3.7. Geographic Information Systems 3.8. Business Intelligence real-time decision support and automated Competitive Intelligence 3.9. Use, Benefits and Results of Business Analytics 4. Text and Web Mining 4.1. Text Mining Concepts 4.2. Text Mining Applications 4.3. Text Mining Process 4.4. Web Mining Concepts 4.5. Web Mining Applications 5. Business Performance Management 5.1. Introduction to Business Performance Management (BPM ) 5.2. Strategy 5.3. Planning 5.4. Monitoring 5.5. Acting and adjusting 5.6. Performance Measurement 5.7. BPM Methodologies 5.8. Architecture and applications of BPM 5.9. Performance Dashboards Business Activity Monitoring (BAM) 6. Data Visualization and Dashboard Design 6.1. Data Visualization 6.2. Data Visualizations Guidelines and Pitfalls 6.3. Dashboards 6.4. Dashboard Design Guidelines and Pitfalls 6.5. Dashboard Design Best Practices 6.6. Information Design 6.7. Bad Practices in Dashboard Design 6.8. Data Visualization Tips Laboratories 0. Project features presentation and preparation 1. SQL Server Management Studio 2. SQL Business Intelligence Development Studio 3. Microsoft Data Warehousing Tools 4. SQL Server Integration Services 5. SQL Server Management Studio - Multidimensional modelling 6. Building OLAP cubes in SQL Server Analysis Services 7. Building Data Mining models in SQL Server Analysis Services 8. Building reports in SQL Server Reporting Services Other reporting tools (Excel, Power Pivot, Power BI, etc.)

4 4. TEACHING AND LEARNING METHODS [Describes the teaching methods and tools used to enable students to achieve the abovementioned learning goals. E.g., case discussions, readings, interactions] 5. ASSESSMENT a) Project (50%) b) Final individual written 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). PROJECT ROADMAP: 1. Introductory Business Analysis 1.1. Company presentation using business descriptions and statistical data 1.2. Description of Reporting goals for that company (business needs) 2. Relational Database Database structure / explanation of how it aligns with business needs 3. Staging Area (SA) SA: development and structure / how it aligns with business needs 4. Data Warehouse (DW) DW: development and structure / how it aligns with business needs 5. Staging Area ETL Process Design & development steps / description of SA ETL Process 6. Data Warehouse ETL Process Design & development steps / description of DW ETL Process 7. Reports Presentation and description of the reports developed, including objectives and purpose of each report s principal components, as well as how it serves to meet the business needs. 8. Dashboards Presentation and description of the dashboards developed, including objectives and purpose of each dashboard s principal components, as well as how it serves to meet the business needs. 6. BIBLIOGRAPHY AND OTHER RESOURCES Sharda, Delen & Turban (2014). Business Intelligence: A Managerial Perspective on Analytics, 3rd Edition, Prentice Hall, ISBN-13: Larson, Brian (2012). Delivering Business Intelligence with Microsoft SQL Server 2012 Third Edition. Mc Graw Hill, ISBN: Inmon, William H. (2005). Building the Data Warehouse (4th Ed edition). Hungry Minds Inc,U.S., ISBN-10:

5 Kimball, R. and Ross, M. (2002). The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition). Wiley, ISBN-10: Davenport, Thomas H. and Harris, Jeanne G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business School Press, ISBN-10: Successful business intelligence : secrets to making BI a killer app. McGraw Hill. ISBN Few, Stephen (2006). Information Dashboard Design: The Effective Visual Communication of Data. Sebastopol, CA: O Reilly Media. ISBN Eckerson, Wayne W. (2006). Performance Dashboards: Measuring, Monitoring, and Managing Your Business. Hoboken, NJ: John Wiley & Sons. ISBN Additional references will be provided during the course aligned with each session content.