From publicly available data to business decisions: (on the example of Lisbon)

Jonas Schweigert; Miguel de Castro Neto

From publicly available data to business decisions: (on the example of Lisbon)

Jonas Schweigert, Miguel de Castro Neto (Advisor)

NOVA Information Management School (NOVA IMS)

Research output: Thesis › Master's Thesis

Abstract

This study describes the basics of business intelligence, before it explains its standard framework. Subsequently, the paper outlines how Google Maps data can be exploited to create a dashboard in Power BI. Thereby, it applies a modified framework to a case study about venues (businesses, transportation infrastructure, and tourist attractions) in Lisbon, Portugal. Five different analysis are carried out: general KPIs, their correlation, an investigation about popular time as well as heat map and location analysis. This work concludes, that businesses and organizations of all kinds can use this information to identify trends and customer behavior to make data-driven decisions.

Original language	English
Qualification	Master of Science
Awarding Institution	NOVA School of Business and Economics (NOVA SBE)
Supervisors/Advisors	Neto, Miguel de Castro, Supervisor
Award date	25 Jan 2019
Publication status	Published - 25 Jan 2019

Keywords

Business intelligence
Decision-making
Dashboard

Access to Document

http://hdl.handle.net/10362/67986Licence: CC BY-NC

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Cite this

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AB - This study describes the basics of business intelligence, before it explains its standard framework. Subsequently, the paper outlines how Google Maps data can be exploited to create a dashboard in Power BI. Thereby, it applies a modified framework to a case study about venues (businesses, transportation infrastructure, and tourist attractions) in Lisbon, Portugal. Five different analysis are carried out: general KPIs, their correlation, an investigation about popular time as well as heat map and location analysis. This work concludes, that businesses and organizations of all kinds can use this information to identify trends and customer behavior to make data-driven decisions.

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