Public University of Navarre



Academic year: 2023/2024
NULL_VALUE
Course code: 710502 Subject title: Business Intelligence
Credits: 4 Type of subject: Year: NULL_VALUE Period: 1º S
Department: Gestión de Empresas
Lecturers:
MARTIN MARTIN, OSCAR (Resp)   [Mentoring ]

Partes de este texto:

 

Module/Subject matter

Competitive intelligence and Business Analytics/ Business intelligence.

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Contents

Part 1: Introduction
  • Introduction to competitive intelligence, business analytics, and their relationship with international trade.
Part 2: Techniques and Tools for Data Collection, Analysis, and Presentation
  • Databases and Information Systems. Design principles and Tools.
  • Tools for business analytics (introducing RStudio/Excel + Power BI -> pending selection of final toolbox).
  • Gathering external data: surveys.
  • Gathering other external data: panels, user-generated content...
  • Exploratory data analysis: basic descriptive statistics.
  • Exploratory data analysis: data visualization.
  • Optimization Models (solver).
  • Regression Analysis.
  • Regression Analysis - Extensions.
  • Machine learning and AI Models.
  • Communicating with data: Dashboard design.
Part 3: Use of Business Analytics Tools in the Global Environment. Hands-on Project
  • Applied example: Competitive intelligence.
  • Applied example: Supply chain analysis, demand prediction.
  • Applied example: Customer behavior - Segmentation.
  • Applied example: Analysis of user-generated content.
  • Applied example: Financial metrics.
Part 4: Examples of Succeeding and Failing in Using Business Analytics in International Business
  • Case study 1.
  • Case study 2.

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General proficiencies

Not applicable.

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Specific proficiencies

Not applicable.

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Learning outcomes

RA04     Evaluate the sustainability of business activity in the field of international business from a perspective of social responsibility.            

RA05     Evaluate relevant data to issue judgments that include a reflection and analysis of social, scientific, or ethical factors that affect the performance of companies in the international field.

RA06     Compile information to analyze problems and propose competitive and corporate strategies appropriate to the international context.

RA07     Identify potential business opportunities in the international field.

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Methodology

Activity In class (hours) Outside of the classroom (hours)
Activity 1: Exploratory Data Analysis on a Case Study. 15 24
Activity 2: Analytics and Visualization on a Case Study. 15 24
Activity 3: Optimization, Regression and ML 8 16
Activity 4: Theoretical-practical evaluation test. 2 0
Total 40 60

 

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Languages

English.

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Evaluation

Learning outcome Assessment activity Weight (%) It allows test resit Minimum required grade
R05, R06 Activity 1 20 NO No
R04, R07 Activity 2 20 NO No
R05, R06 Activity 3 10 NO No
R04, R05, R06, R07 Activity 4 50 Yes 5

 

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Agenda

Week Session Description of the content (in class, 2h sessions) Outside of the classroom  
1 1 Introduction to competitive intelligence, business analytics and its relationship with international trade. NO  
1 2 Databases and Information Systems. Design principles and Tools NO  
1 3 Tools for business analytics NO  
1 4 Gathering external data: surveys NO  
1 5 Gathering other external data: panels, user generated content NO  
1 6 Exploratory data analysis: basic descriptive statistics NO  
1 7 Exploratory data analysis: data visualization NO  
1 8 Communicating with data: Dashboard design NO  
2 9 Optimization Models (solver) NO  
2 10 Regression Analysis NO  
2 11 Regression Analysis - Extensions  NO  
2 12 Machine learning and AI Models NO  
3 13 Applied example: Competitive intelligence NO  
3 14 Applied example: Supply chain analysis, demand prediction NO  
3 15 Applied example: Customer behavior - Segmentation NO  
3 16 Applied example: Analysis of user generated content NO  
3 17 Applied example: Financial metrics NO  
3 18 Case study 1 NO  
3 19 Case study 2 NO  
3 20 Examen NO

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Experimental practice program

Not applicable.

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Bibliography

Access the bibliography that your professor has requested from the Library.


- Arora, Ishmeet & Chaudhari, Apurva. (2023). Analysis of Twitter Data for Business Intelligence. 
- Khoshbakht, Farhad & Quadri, S.. (2023). Big Data Framework for Analytics Business Intelligence.- Post, Gerald V., and Albert Kagan (2012) "Business Intelligence." International Journal of Business Intelligence Research 3, no. 3 (July 2012): 16¿28.
- Laberge, Robert (2011) The Data Warehouse mentor. Practical Data Warehouse Business Intelligence Insights .Mc Graw Hill
- Christopher Adamson (2006) Mastering Data Warehouse Aggregates: Solutions for Star Schema Performance. Wiley. ISBN-13: 978-0471777090.
- Jill Dyché & Evan Levy (2006) Customer Data Integration: Reaching a Single Version of the Truth (SAS Institute Inc.). Wiley. ISBN-13: 978-0471916970
- Maurizio Rafanelli Editor (2003), Multidimensional Databases. Problems and Solutions. Idea Group Inc.


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Location

Campus Arrosadía.

Professors who are not from UPNA:

  • Alejandro Echeverría Rey
  • Iñaki Oroz

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