scholarly journals BITOUR: A Business Intelligence Platform for Tourism Analysis

2020 ◽  
Vol 9 (11) ◽  
pp. 671
Author(s):  
Alexander Bustamante ◽  
Laura Sebastia ◽  
Eva Onaindia
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Processing ◽  
Data Visualization ◽  
Business Intelligence ◽  
Data Sources ◽  
Data Driven ◽  
Decision Making Process ◽  
The Core ◽  
Processing Data

Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classical BI architecture and provides functionalities for data transformation, data processing, data analysis and data visualization. At the core of the data processing, BITOUR offers mechanisms to identify tourists in Twitter, assign tweets to attractions and accommodation sites from Tripadvisor and Airbnb, analyze sentiments in opinions issued by tourists, and all this using geolocation objects in Openstreetmap. With all these ingredients, BITOUR enables data analysis and visualization to answer questions like the most frequented places by tourists, the average stay length or the view of visitors of some particular destination.

scholarly journals Evaluation of application of new decision-making methods in selected companies: the use of business intelligence in practice

ACC Journal ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 29-40
Author(s):  
Petra Kašparová
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Business Intelligence ◽  
Questionnaire Survey ◽  
Human Life ◽  
Utilization Rate ◽  
Decision Making Process ◽  
Short Introduction ◽  
Business Decision

Growing pressure on increasing decision-making speed in all spheres of human life is one of the basic phenomena of today. Immediately after the first wave of the coronavirus pandemic, we can consider the ability of making good decisions quickly as one of the most important aspects of our being. The main objective of this article is to find out the utilization rate of several basic decision-making approaches in selected companies with an emphasis on newly used methods such as data analysis and business intelligence tools. The first part of the article presents a short introduction of the decision-making process and an overview of hitherto known and used tools facilitating the whole procedure. The submitted study of available literature leads to the presentation of own classification of the most widely used decisionmaking methods. Based on a questionnaire survey, in the second section, the pilot research examines the involvement of five different groups of methods in business decision-making, such as intuition and previous experiences, consultation with colleagues, data analysis (historical), MCDM methods and consultation with experts. Afterwards, the most common obstacles that employees must face in introducing new tools have been identified. In general, the results show that time and the associated pressure on decision-making speed play a crucial role in the decision-making process.

scholarly journals Data Storytelling with Dashboard: Accelerating Understanding Through Data Visualization in Financial Technology Company Case Study

Jurnal METRIS ◽  
2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ferdian Suprata
Keyword(s):  
Decision Making ◽  
Data Visualization ◽  
Rapid Development ◽  
Data Driven ◽  
Decision Making Process ◽  
Business Practices ◽  
Context Data ◽  
The Impact ◽  
Financial Technology

In the rapid development many organisation rely on context data to support as well as to assist its decision making process. Consequently, Business Intelligence (BI), Dashboard, and Data Visualization emerged as primary tools in early 1990s as a way to help practitioners, data analyst, and data scientist to present context data into an actionable information for decision making process. However, despite its robust and powerful tools, recent study done by Kaggle’s survey in 2017 resulted that in the last five years, many companies were not able to create effective data-driven dashboard due to complex dataset, poor dashboard design, and insufficient storytelling. Hence, understanding of who is going to use dashboard, choosing which data and metrics to visualize in the right context, knowing how to convey information, driving engagement, and persuading audiences are essential in current business practices. This study is aimed to help practitioners to understand the impact of effective dashboard can have on decision making process, to design leveraging dashboard, and to present the dashboard in storytelling. A literature study is performed to gather all relevant information resulted in guidelines for dashboard creator. Case study in financial technology company is applied to experiment and to test the guidelines for assisting dashboard creator to present data-driven insight to the stakeholder.

Game Data Science: An Introduction

2021 ◽  
pp. 1-32
Author(s):  
Magy Seif El-Nasr ◽  
Truong Huy Nguyen Dinh ◽  
Alessandro Canossa ◽  
Anders Drachen
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Collection ◽  
Data Processing ◽  
Data Science ◽  
Data Driven ◽  
Game Development ◽  
Collection Data ◽  
Support Decision Making ◽  
Over Time

This chapter introduces the topic of this book: Game Data Science. Game data science is the process of developing data-driven techniques and evidence to support decision-making across operational, tactical, and strategic levels of game development, and this is why it is so valuable. This chapter introduces this topic as well as outlines the process of game data science from instrumentation, data collection, data processing, data analysis, to reporting. Further, the chapter also discusses the application of game data science, as well as its utility and value, to the different stakeholders. The chapter also includes a section discussing the evolution of this process over time, which is important to situate the field and the techniques discussed in the book. The chapter also outlines established industry terminologies and defines their use in the industry and academia.

scholarly journals A business case for a data-driven decision-making tool to support the UNBC research enterprise.

2020 ◽  
Author(s):  
◽  
Mark Barnes
Keyword(s):  
Decision Making ◽  
Data Visualization ◽  
Business Intelligence ◽  
Resource Planning ◽  
Business Case ◽  
Data Driven ◽  
Visualization Tool ◽  
Data Driven Decision Making ◽  
Business Decisions ◽  
Design Document

Business intelligence tools allows for data-driven decision-making within organizations using historical events to predict future trends, which is especially valuable when allocating operational resources. As a research-intensive Canadian university, UNBC has seen a significant increase in activities related to supporting the research enterprise, which requires additional resources (human, capital, financial etc.) in order to effectively and efficiently advance the mission of the research community. As outlined in our Annual University Accountability Report, 2018/19 was an incredibly productive year for research with more than $14 million received in support of research. The University has seen a significant increase in the number and breadth of agencies and organizations funding research at UNBC. The administration of research awards involves both pre-award and post-award processes, which requires responsible allocation of available resources to ensure a sustainable model will be developed to achieve goals outlined by the institution’s strategic priorities and build the foundation to reach our goal of a research enterprise generating $25M in annual research revenue. Therefore, using business intelligence tools to utilize historical data to predict the necessary resourcing needs of the institution will allow UNBC to make strategic investments in research and remain competitive on the provincial, national and international stage. Informed decision-making when investing resources are critical to the success of any business. The goal of my MBA project is to gather critical information to be used in the development a data visualization and forecasting tool that will allow for informed decisions for the allocation of resources necessary to support the research mission at UNBC. The objectives of the MBA project are two-fold, which include the development of the business case for the UNBC data visualization tool (DVT) and also the completion of a design document. The information gathered6 from this project will be used in the future (post-MBA) to develop a data visualization tool that will allow for the on-going monitoring of UNBC’s progress towards putting in place the appropriate resources to reach $25M in annual research revenue. Specifically, the MBA project will consist of completing a comprehensive business case outlining the “business need” and potential solutions. Secondly, the MBA project will consist of developing a “design document” for an eventual tool that will be used to visualize research funding and labor information to inform business decisions for resource planning for the UNBC research enterprise. This design support system will be used by senior leadership within UNBC to effectively and efficiently make decisions to allocate resources.

scholarly journals Data-driven Storytelling to Support Decision Making in Crisis Settings: A Case Study

2021 ◽  
Vol 27 (10) ◽  
pp. 1046-1068
Author(s):  
Andrea Lezcano Airaldi ◽  
Jorge Andres Diaz-Pace ◽  
Emanuel Irrazábal
Keyword(s):  
Decision Making ◽  
Best Practices ◽  
Data Visualization ◽  
Data Driven ◽  
Decision Making Process ◽  
Health Crisis ◽  
General Practices ◽  
Information Comprehension ◽  
Support Decision Making

Data-driven storytelling helps to communicate facts, easing comprehension and decision making, particularly in crisis settings such as the current COVID-19 pandemic. Several studies have reported on general practices and guidelines to follow in order to create effective narrative visualizations. However, research regarding the benefits of implementing those practices and guidelines in software development is limited. In this article, we present a case study that explores the benefits of including data visualization best practices in the development of a software system for the current health crisis. We performed a quantitative and qualitative analysis of sixteen graphs required by the system to monitor patients' isolation and circulation permits in quarantine due to the COVID-19 pandemic. The results showed that the use of storytelling techniques in data visualization contributed to an improved decision-making process in terms of increasing information comprehension and memorability by the system stakeholders.

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.

scholarly journals Exploring Factors Affecting the Emergency Specialists’ Decision-Making in Case of Emergencies in Patients

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Abbasali Ebrahimian ◽  
Seyed-Hossein Hashemi-Amrei ◽  
Mohammadreza Monesan
Keyword(s):  
Decision Making ◽  
Emergency Department ◽  
Qualitative Content Analysis ◽  
Decision Makers ◽  
Decision Making Process ◽  
Factors Affecting ◽  
Emergency Situations ◽  
The Core ◽  
Semistructured Interviews ◽  
Emergency Decision

Introduction. Appropriate decision-making is essential in emergency situations; however, little information is available on how emergency decision-makers decide on the emergency status of the patients shifted to the emergency department of the hospital. This study aimed at explaining the factors that influence the emergency specialists’ decision-making in case of emergency conditions in patients. Methods. This study was carried out with a qualitative content analysis approach. The participants were selected based on purposive sampling by the emergency specialists. The data were collected through semistructured interviews and were analyzed using the method proposed by Graneheim and Lundman. Results. The core theme of the study was “efforts to perceive the acute health threats of the patient.” This theme was derived from the main classes, including “the identification of the acute threats based on the patient’s condition” and “the identification of the acute threats based on peripheral conditions.” Conclusions. The conditions governing the decision-making process about patients in the emergency department differ from the conditions in other health-care departments at hospitals. Emergency specialists may have several approaches to decide about the patients’ emergency conditions. Therefore, notably, the emergency specialists’ working conditions and the others’ expectations from these specialists should be considered.

scholarly journals Data competence maturity: developing data-driven decision making

2018 ◽  
Vol 11 (2) ◽  
pp. 139-158 ◽  
Author(s):  
Thomas G. Cech ◽  
Trent J. Spaulding ◽  
Joseph A. Cazier
Keyword(s):  
Decision Making ◽  
Secondary Education ◽  
Data Science ◽  
Data Driven ◽  
Decision Making Process ◽  
Maturity Model ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Development Data ◽  
Education Performance

Purpose The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education. Design/methodology/approach Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education. Findings The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process. Practical implications Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes. Originality/value This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.

scholarly journals International Student Mobility

2018 ◽  
pp. 15-30
Author(s):  
Rashim Wadhwa
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
International Students ◽  
International Student ◽  
Student Mobility ◽  
Internationalization Of Higher Education ◽  
Decision Making Process ◽  
Core Element ◽  
International Student Mobility ◽  
The Core

International student mobility is the core element of the internationalization of higher education. In recent years, a significant change has been observed in the outlook of individuals which is giving a boost to this phenomenon. Within this context, the present chapter analyzed the phenomenon of international student mobility through different approaches by providing critical outlook. An attempt has been made to list the important determinants which influence the decision-making process of international students.

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