LogisticBusiness Intelligence

No prior knowledge is required.  

The assessment methodology allows students to develop practical and research skills in specific areas of Business Analytics, which students perceive as relevant to their training, to the organization where they are working, or sector where they want to develop their future career, always of an applied nature.
In order to take advantage of it, a practical work / hands-on approach with the use of a data set to guarantee data quality and use a data visualization tool, which is aimed at applying the acquired knowledge to the elaboration of a set of visualization elements that allow decision-making based on data. The final classification, CF, is obtained by performing this work.

It is intended that students, at the end of this UC:
– know the fundamental concepts and trends associated with BI and BI in Logistics;
– know the components of a BI system, methodologies for its implementation, use, and management, particularly in theLogistics area;
– use Self Service BI tools to visualize data in logistics;
– understand the relevance of using data warehouses in logistics;
– Anticipate trends in BI in logistics and allow the connection between this UC and the following Curricular Units.

P1 – Business Intelligence and Logistics Integration
P2 – Components of a Business Intelligence System
P3 – Identification of patterns in logistic data and reporting of trends
P4 – Data Warehouse Applications in Logistics
P5 – Methodologies for implementing a Business Intelligence project
P6 – New BI trends in Logistics

NAO

• Tipi, N. (2021). Supply Chain Analytics and Modelling: Quantitative Tools and Applications. Kogan Page.
• Vandeput, N. (2021). Data Science for Supply Chain Forecasting, 2nd Edition. De Gruyter.
• Few, S.(2019).The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data, AnalyticsPress.
• Pochiraju, B., & Seshadri, S. (Eds.).(2019).Essentials of Business Analytics: An Introduction to the Methodology and its applications (Vol. 264). Springer.
• Stefanovic, N., & Stefanovic, D.(2009).Supply chain business intelligence: technologies, issues, and trends. In Artificial intelligence an international perspective (pp. 217-245). Springer, Berlin, Heidelberg.
• Chae, B., & Olson, D. L.(2013).Business analytics for supply chain: A dynamic-capabilities framework. International, Journal of Information Technology & Decision Making, 12(01), 9-26.
• Grabińska, A., & Ziora, L.(2019).The application of Business Intelligence systems in logistics. review of selected practical examples. System Safety: Human-Technical Facility-Environment, 1(1).