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Dissertations / Theses on the topic 'Business analytics and decision science'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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1

Fors, Anton, and Emelie Ohlson. "Business analytics in traditional industries – tackling the new age of data and analytics." Thesis, Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-10450.

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Decision-making is no longer based on human preferences and expertise alone. The era of big data brings up new challenges with business analytics for organizations that want a competitive advantage. Previous research shows that a lot of studies have been made on why this era is now crucial to organizations but not how they can adapt it. In this case study there is a glimpse of how a traditional organization with an old mindset can catch up on the new technological advantages. The purpose of this study is to understand how a traditional company in Sweden is affected by analytics and if it is va

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Akpakpan, Nsikak Etim. "Analytic Extensions to the Data Model for Management Analytics and Decision Support in the Big Data Environment." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5538.

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From 2006 to 2016, an estimated average of 50% of big data analytics and decision support projects failed to deliver acceptable and actionable outputs to business users. The resulting management inefficiency came with high cost, and wasted investments estimated at $2.7 trillion in 2016 for companies in the United States. The purpose of this quantitative descriptive study was to examine the data model of a typical data analytics project in a big data environment for opportunities to improve the information created for management problem-solving. The research questions focused on finding artifac

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3

Culumber, Janene Jones. "Physician Practice Survival: The Role of Analytics in Shaping the Future." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/7009.

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This dissertation joins an ongoing discussion in the business management and information technology literature surrounding the measurement of an organization’s business analytic capability, the benefits derived from maturing the capability and the improvements being made toward maturity. The dissertation specifically focuses on the healthcare industry in the United States and more specifically independent physician practices specializing in orthopaedics. After an extensive literature review along with expertise from industry leaders and experienced academic faculty, a sur

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Dedge, Parks Dana M. "Defining Data Science and Data Scientist." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/7014.

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The world’s data sets are growing exponentially every day due to the large number of devices generating data residue across the multitude of global data centers. What to do with the massive data stores, how to manage them and defining who are performing these tasks has not been adequately defined and agreed upon by academics and practitioners. Data science is a cross disciplinary, amalgam of skills, techniques and tools which allow business organizations to identify trends and build assumptions which lead to key decisions. It is in an evolutionary state as new technologies with capabilities ar

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Pietrobon, Alberto, and Abraham Bamidele Sunday Ogunmakinwa. "Business Intelligence and Customer Relationship Management: a Direct Support to Product Development Teams." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Informatik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-15473.

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For manufacturing firms, having knowledge about customers is very important, in particular for the developers and designers of new products. A way in which software can help to build an information channel between the customers and the firm is through Customer Relationship Management (CRM) and Business Intelligence (BI) solutions. Customers’ data are captured into the Customer Relationship Management solution while Business Intelligence analyses them and provide clear processed information to the developers and designers of new products. In this study we have researched if this process occurs

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Pienaar, Celia. "Machine learning in predictive analytics on judicial decision-making." Master's thesis, Faculty of Science, 2021. http://hdl.handle.net/11427/33925.

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Legal professionals globally are under pressure to provide ‘more for less' – not an easy challenge in the era of big data, increasingly complex regulatory and legislative frameworks and volatile financial markets. Although largely limited to information retrieval and extraction, Machine Learning applications targeted at the legal domain have to some extent become mainstream. The startup market is rife with legal technology providers with many major law firms encouraging research and development through formal legal technology incubator programs. Experienced legal professionals are expected to

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Fridell, Gustav, and Chafjiri Saam Cedighi. "IT’S IN THE DATA : A multimethod study on how SaaS-businesses can utilize cohort analysis to improve marketing decision-making." Thesis, Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167620.

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Incorporating data and analytics within marketing decision-making is today crucial for a company’s success. This holds true especially for SaaS-businesses due to having a subscription-based pricing model dependent on good service retention for long- term viability and profitability. Efficiently incorporating data and analytics does have its prerequisites but can for SaaS-businesses be achieved using the analytical framework of cohort analysis, which utilizes subscription data to obtain actionable insights on customer behavior and retention patterns. Consequently, to expand upon the understandi

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Sun, Rui S. M. Massachusetts Institute of Technology. "Analytics for hotels : demand prediction and decision optimization." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111438.

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Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2017.<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 69-71).<br>The thesis presents the work with a hotel company, as an example of how machine learning techniques can be applied to improve demand predictions and help a hotel property to make better decisions on its pricing and capacity allocation strategies. To sol

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Soukieh, Tarek. "How Can Business Analytics Induce Creativity: The Performance Effects of User Interaction with Business Analytics." Cleveland State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=csu1462634733.

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10

Lo, Bobby. "Social media analytics in business intelligence applications." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/46017.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.<br>Includes bibliographical references (p. 89-93).<br>Social media is becoming increasingly important in society and culture, empowering consumers to group together on common interests and share opinions through the Internet. The social web shifts the originators of content from companies to users. Differences caused by this dynamic result in existing web analytic techniques being inadequate. Because people reveal their thoughts and preferences in social media, there are signifi

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Karlsson, Rebecka. "Data as Intelligence : A Study of Business Intelligence as Decision Support." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-21276.

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Introduction: The term Business Intelligence arose in the mid-1990s and is a growing share of the IT market. The need of Business Intelligence emerges from an increasing competition and a constantly changing and more complex business climate. Problem discussion: There are only few examples of research dealing with data-driven decision processes. How data are incorporated in decision making processes is crucial for the future use of decision support systems. The literature stress that managers must use more analytics and rationality to make better and more appropriate decisions. However, previo

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Mushore, Rutendo. "Leveraging business Intelligence and analytics to improve decision-making and organisational success." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27408.

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In a complex and dynamic organisational environment, challenges and dilemmas exist on how to maximise the value of Business Intelligence and Analytics (BI&A). The expectation of BI&A is to improve decision-making for core business processes that drive business performance. A multi-disciplinary review of theories from the domains of strategic management, technology adoption and economics claims that tasks, technology, people and structures (TTPS) need to be aligned for BI&A to add value to decision-making. However, these imperatives interplay, making it difficult to determine how they are confi

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Hellström, Elin, and My Hemlin. "Det binära guldet : en uppsats om big data och analytics." Thesis, Uppsala universitet, Informationssystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-205900.

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Syftet med denna studie är att utreda begreppen big data och analytics. Utifrån vetenskapliga teorier om begreppen undersöks hur konsultföretag uppfattar och använder sig av big data och analytics. För att skapa en nyanserad bild har även en organisation inom vården undersökts för att få kunskap om hur de kan dra nytta av big data och analytics. Ett antal viktiga svårigheter och framgångsfaktorer kopplade till båda begreppen presenteras. De svårigheterna kopplas sedan ihop med en framgångsfaktor som anses kunna bidra till att lösa det problemet. De mest relevanta framgångsfaktorer som identifi

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Sayão, Cezar. "Fatores críticos de sucesso para ferramentas de Business Analytics." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/3/3136/tde-06122017-084855/.

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Atualmente vivemos em uma sociedade com a maior quantidade de dados já disponíveis em toda a história, e ao mesmo tempo que ocorre o crescimento desta vasta quantidade de informações dispersas, os ambientes empresariais tornaram-se cada vez mais complexos e competitivos. Nos quais gestores necessitam detectar e, se possível, prever tendências para estruturar planos de ação através de análises simples e/ou, por vezes, extremamente complexas dos dados. Dessa forma, o potencial impacto nas organizações referentes à utilização dessas informações em sua gestão tem chamado a atenção tanto de executi

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Medeiros, Mauricius Munhoz de. "O impacto da capacidade de inteligência analítica de negócios na tomada de decisões na era dos grandes dados." Universidade do Vale do Rio dos Sinos, 2018. http://www.repositorio.jesuita.org.br/handle/UNISINOS/7109.

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Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-07-12T16:11:01Z No. of bitstreams: 1 Mauricius Munhoz de Medeiros_.pdf: 3956183 bytes, checksum: b542e87eedac0be0bf8f79f48709672f (MD5)<br>Made available in DSpace on 2018-07-12T16:11:01Z (GMT). No. of bitstreams: 1 Mauricius Munhoz de Medeiros_.pdf: 3956183 bytes, checksum: b542e87eedac0be0bf8f79f48709672f (MD5) Previous issue date: 2018-02-27<br>CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Este estudo investigou o impacto das capacidades de inteligência analítica de negócios na expansão das capacidade

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Basra, Rajveer Singh. "A framework for knowledge discovery within business intelligence for decision support." Thesis, Brunel University, 2008. http://bura.brunel.ac.uk/handle/2438/4457.

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Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportuni

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Dube, Qobo. "Species distribution modelling of Aloidendron dichotomum (quiver tree)." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29625.

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A variety of species distribution models (SDMs) were fit to data collected by a 15,000km road-side visual survey of Aloidendron dichotomum populations in the Northern Cape region of South Africa, and Namibia. We fit traditional presence/absence SDMs as well as SDMs on how proportions are distributed across three species stage classes (juvenile, adult, dead). Using five candidate machine learning methods and an ensemble model, we compared a number of approaches, including the role of balanced class (presence/absence) datasets in species distribution modelling. Secondary to this was whether or n

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Naghdipour, Navid Naghdipour. "New Trends in Business Intelligence : A case study on the impact of organizational demands of information and new technologies on BI." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Informatik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-25148.

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When the data warehouse concept was first introduced by IBM as a part of their new information system in 1988, the first step in the field of modern decision support systems or business intelligence was taken. Since then, academics, practitioners and solution developers have put a considerable effort in introducing new trends of these systems. Each new trend has roots in what enterprises demand from these systems. The advances in Web technologies and social media, has led to introduction of new trends such as Cloud BI and Big Data which are both cost-effective and also have the potential to ta

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19

Ojo, Michael O. "Big data analytics solutions| The implementation challenges in the financial services industry." Thesis, Robert Morris University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10111816.

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<p> The challenges of Big Data (BD) and Big Data Analytics (BDA) have attracted disproportionately less attention than the overwhelmingly espoused benefits and game-changing promises. While many studies have examined BD challenges across multiple industry verticals, very few have focused on the challenges of implementing BDA solutions. Fewer of these studies have focused directly on the financial services industry, and none have quantifiably measured the severities of the challenges. That created gaps as BDA solution implementers in the financial services industry could neither access a roadma

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20

Torres, Russell. "Organizational Competency Through Information: Business Intelligence and Analytics as a Tool for Process Dynamization." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804918/.

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The data produced and collected by organizations represents both challenges and opportunities for the modern firm. Business intelligence and analytics (BI&A) comprises a wide variety of information management technologies and information seeking activities designed to exploit these information resources. As a result, BI&A has been heralded as a source of improved organizational outcomes in both the academic and practitioner literature, and these technologies are among the largest continuous IT expenditures made over the last decade.Despite the interest in BI&A, there is not enough theorizing

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Alsadhan, Majed. "An application of topic modeling algorithms to text analytics in business intelligence." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17580.

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Master of Science<br>Department of Computing and Information Sciences<br>Doina Caragea<br>William H. Hsu<br>In this work, we focus on the task of clustering businesses in the state of Kansas based on the content of their websites and their business listing information. Our goal is to cluster the businesses and overcome the challenges facing current approaches such as: data noise, low number of clustered businesses, and lack of evaluation approach. We propose an LSA-based approach to analyze the businesses’ data and cluster those businesses by using Bisecting K-Means algorithm. In this approach

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Pesaran, Behbahani Masoud. "EBusiness analytics framework (EBAF) : to enable SMEs to gain business intelligence for competitive advantage." Thesis, Kingston University, 2014. http://eprints.kingston.ac.uk/30603/.

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Recent technological advances have resulted in increasingly larger databases. The fast and efficient useful analysis and interpretation of this data to improve business intelligence is critical to the success of all organisations. This thesis presents a new framework that utilises a new multilayer mining theory and is based on business intelligence methods, data mining techniques, online analytical processing (OLAP) and online transactional processing (OLTP). Existing decision making modelling approaches for executive information systems have three main shortcomings and limitations to differen

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Mansell, Ingrid Jane. "The role of analytics in management decision making within an organisation in the Western Cape, South Africa." Thesis, Cape Peninsula University of Technology, 2016. http://hdl.handle.net/20.500.11838/2472.

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Thesis (MTech (Business Administration))--Cape Peninsula University of Technology, 2016.<br>This mixed methods study examined specific influences on low usage of analytics among level 4 managers in a selected public sector organisation, based on SAP Business Intelligence (SAP BI) log on statistics collected between July 2012 and June 2016. Analytics provides an organisation the ability to enable its management team to make decisions based on facts, rather than assumption. The aim of this interpretivist research, grounded in a subjectivist epistemological position, was to gain an in-depth under

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Durbach, Ian N. "The treatment of uncertainty in multicriteria decision making." Master's thesis, University of Cape Town, 2003. http://hdl.handle.net/11427/15424.

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Bibliography: leaves 142-149.<br>The nature of human decision making dictates that a decision must often be considered under conditions of uncertainty. Decisions may be influenced by uncertain future events, doubts regarding the precision of inputs, doubts as to what the decision maker considers important, and many other forms of uncertainty. The multicriteria decision models that are designed to facilitate and aid decision making must therefore consider these uncertainties if they are to be effective. In this thesis, we consider the treatment of uncertainty in multicriteria decision making (M

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Najmizadehbaghini, Hossein. "Enhancing the Efficacy of Predictive Analytical Modeling in Operational Management Decision Making." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1538693/.

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In this work, we focus on enhancing the efficacy of predictive modeling in operational management decision making in two different settings: Essay 1 focuses on demand forecasting for the companies and the second study utilizes longitudinal data to analyze the illicit drug seizure and overdose deaths in the United States. In Essay 1, we utilize an operational system (newsvendor model) to evaluate the forecast method outcome and provide guidelines for forecast method (the exponential smoothing model) performance assessment and judgmental adjustments. To assess the forecast outcome, we consider

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Höcker, Filip, and Finn Brand. "‘Data over intuition’ – How big data analytics revolutionises the strategic decision-making processes in enterprises." Thesis, Internationella Handelshögskolan, Jönköping University, IHH, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48560.

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Background: Digital technologies are increasingly transforming traditional businesses, and their pervasive impact is leading to a radical restructuring of entire industries. While the significance of generating competitive advantages for businesses utilizing big data analytics is recognized, there is still a lack of consensus of big data analytics influencing strategic decision-making in organisations. As big data and big data analytics become increasingly common, understanding the factors influencing decision-making quality becomes of paramount importance for businesses. Purpose: This thesis

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Killada, Parimala. "Data Analytics using Regression Models for Health Insurance Market place Data." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1501721348961437.

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Lin, Yang. "Chinese business managers' perceptions in KM-related decision making: environmental, informational, individual, and decision-specific perspectives." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=104503.

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Knowledge Management (KM) to date has been poorly recognized, explained, and applied in China, and lack of empirical evidence has become a major barrier to the development of KM research in the Chinese academic community. The purpose of this study is to investigate the perceptions of Chinese business managers in the processes of KM-related decision making, from environmental, informational, individual, and decision-specific perspectives. A qualitative, multiple-case study strategy was used. Primary data were collected from the semi-structured interviews conducted with seventeen Chinese busines

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Mathias, Henry. "Analyzing Small Businesses' Adoption of Big Data Security Analytics." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6614.

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Despite the increased cost of data breaches due to advanced, persistent threats from malicious sources, the adoption of big data security analytics among U.S. small businesses has been slow. Anchored in a diffusion of innovation theory, the purpose of this correlational study was to examine ways to increase the adoption of big data security analytics among small businesses in the United States by examining the relationship between small business leaders' perceptions of big data security analytics and their adoption. The research questions were developed to determine how to increase the adoptio

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Espinoza, Espinoza Bertha Yrene, and Rivera Natalia Elizabeth Gutiérrez. "Sistema de información para la toma de decisiones, usando técnicas de análisis predictivo para la Empresa IASACORP International S.A." Bachelor's thesis, Universidad Ricardo Palma, 2015. http://cybertesis.urp.edu.pe/handle/urp/1271.

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En la actualidad, las empresas manejan una gran cantidad de información, el cual era inimaginable años atrás, la capacidad de recolectarla es muy impresionante. En consecuencia, para varias empresas esta información se ha convertido en un tema difícil de manejar. Diariamente, las empresas sea del sector, tipo o tamaño que sea, toman decisiones, las cuales la mayoría son decisiones estratégicas que pueden afectar el correcto funcionamiento de la empresa. Es aquí, donde ingresa una de las herramientas más mencionadas en el área de TI: Business Intelligence, este término se refiere al uso de dat

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Wegner, Trevor. "A study into the rationale, design and evaluation of a specific decision support system in compensation planning." Doctoral thesis, University of Cape Town, 1987. http://hdl.handle.net/11427/8375.

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Bibliography: leaves 285-295.<br>The application of newly developed information technology to managerial decision making has given rise to a new discipline known as Decision Support Systems (DSS). While considerable development of DSS has taken place since the mid-seventies, in such areas as applications, conceptual clarification of goals and characteristics, and developmental methodology, there are still certain areas which remain relatively unexplored.

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Malley, Mark G. "Proactive IT Incident Prevention: Using Data Analytics to Reduce Service Interruptions." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/3404.

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The cost of resolving user requests for IT assistance rises annually. Researchers have demonstrated that data warehouse analytic techniques can improve service, but they have not established the benefit of using global organizational data to reduce reported IT incidents. The purpose of this quantitative, quasi-experimental study was to examine the extent to which IT staff use of organizational knowledge generated from data warehouse analytical measures reduces the number of IT incidents over a 30-day period, as reported by global users of IT within an international pharmaceutical company headq

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Raghavan, Veeravalli. "The impact of a computer network on group decision-making: An experimental investigation." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185320.

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This dissertation investigates the performance of a problem solving group whose members are constrained to communicate only through a computer network, a situation that has become commonplace with advances in computer technology. The model of group decision making adopted specifies that the group outcome is a function of six independent variables. They are group size, the incentives offered to group members, the decision rule used to combine member inputs, the distribution of information among members, the complexity of the task, and mode of communication (face-to-face or computer network). Th

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Molin, Mattias. "Rättidiga beslut genererade från olika typer av dataanalyser : En fallstudie inom Landstinget i Värmland." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-71230.

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Syftet med denna kandidatuppsats är att, via kvalitativa intervjuer, identifiera och beskriva ett landstings process för hur patient- och sjukvårdsdata, genom olika typer av dataanalyser, kan generera rättidiga beslut. I det valda kvalitativa tillvägagångssättet skapades en semi-strukturerad intervjuguide, baserad på en analysmodell. Fem intervjuer med anställda inom fallstudieorganisationen genomfördes. För att underlätta för respondenterna och ge en tydlig helhetssyn på intervjuns innehåll, fick respondenterna innan intervjun se analysmodellen som skapats. Deskriptiv analys är den vanlig

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Tan, Shiang Yen. "Towards a framework for realizing actionable insight from complex data: A machine-augmented cognition approach to data exploration, information synthesis, and knowledge actualization." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/108958/1/Shiang%20Yen_Tan_Thesis.pdf.

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Research in data analytics has emphasized technical advancements and largely undermined the importance of user intuition and knowledge in the analytics process. This study proposed a new data analytics framework for designing and evaluating data analytics systems that harness both the flexibility of human intuition and the rigor of machine-driven analytics techniques. This study contributes to a systematic understanding of the analyst's workflow, behaviors, and information needs. It also produces a set of empirically-tested design principles that can be used to effectively support these human

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Moyer, Adam C. "Self-Evolving Data Collection Through Analytics and Business Intelligence to Predict the Price of Cryptocurrency." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1604656483616404.

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Gleeson, William Joseph. "Computer-based decision-making: The impact of personal computers and distributed databases on managers' performance." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185309.

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This study was a field experiment to test the influence of two different computer conditions on decision-making in an organizational setting. The experiment was carried out in ten mid-sized corporations. The 117 subjects contained about equal numbers of managers and non-managers. The computer conditions tested were (1) a personal computer used with a distributed data base and (2) the traditional mainframe with a central data base supplying information by printouts. The experimental problem was identical in both conditions as was the data in the data base. An additional part of the experiment w

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Nosov, Igor, and Rustam Hamraev. "Educating Bootstrapping : Financial decision making processes in Create Business Incubator." Thesis, Mälardalen University, School of Sustainable Development of Society and Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-6567.

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<p>Recently, small businesses have attracted much attention from scholars and businessmen, since the significance of these businesses estimated essential in rapid changing business environment from the perspective of wealth and job creation. Simultaneously, it is well known that most infant entrepreneurs are constrained by shortage of financial resource for development and growth of their business. Some entrepreneurs carry out the need for resources by applying the particular methods of financial bootstrapping. Therefore, a number of researches have been conducted in order to define characteri

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De, Koker Louise. "Fostering collaboration amongst business intelligence, business decision makers and statisticians for the optimal use of big data in marketing strategies." University of the Western Cape, 2019. http://hdl.handle.net/11394/6780.

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Philosophiae Doctor - PhD<br>The aim of this study was to propose a model of collaboration adaptable for the optimal use of big data in an organisational environment. There is a paucity of knowledge on such collaboration and the research addressed this gap. More specifically, the research attempted to establish whether leadership, trust and knowledge sharing influence collaboration among the stakeholders identified at large organisations. The conceptual framework underlying this research was informed by collaboration theory and organisational theory. It was assumed that effective collaborat

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Peyne, Benjamin, and Ariane Chan. "Data-driven decision making in Marketing : A theoretical approach." Thesis, Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33545.

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Customer insight is at the heart of the big data era. This revolution makesit possible to directly obtain high potential data and in large quantitiesabout customers. Thus we take note that, more than ever, a large volumeof big data is collected by companies.We observe that big data have become a necessary tool within marketing.More and more companies orient their decisions according to theinformations provided by data, with the aim of quickly having betterresults.Nevertheless, in order to integrate these big data in a better way and gaina competitive advantage, companies must face new challeng

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Brown, Mary Erin. "Data-Driven Decision Making as a Tool to Improve Software Development Productivity." Thesis, Walden University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3591716.

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<p> The worldwide software project failure rate, based on a survey of information technology software manager's view of user satisfaction, product quality, and staff productivity, is estimated to be between 24% and 36% and software project success has not kept pace with the advances in hardware. The problem addressed by this study was the limited information about software managers' experiences with data-driven decision making (DDD) in agile software organizations as a tool to improve software development productivity. The purpose of this phenomenological study was to explore how agile softw

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Hsiao, Shih-Hui. "SOCIAL MEDIA ANALYTICS − A UNIFYING DEFINITION, COMPREHENSIVE FRAMEWORK, AND ASSESSMENT OF ALGORITHMS FOR IDENTIFYING INFLUENCERS IN SOCIAL MEDIA." UKnowledge, 2016. http://uknowledge.uky.edu/busadmin_etds/8.

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Given its relative infancy, there is a dearth of research on a comprehensive view of business social media analytics (SMA). This dissertation first examines current literature related to SMA and develops an integrated, unifying definition of business SMA, providing a nuanced starting point for future business SMA research. This dissertation identifies several benefits of business SMA, and elaborates on some of them, while presenting recent empirical evidence in support of foregoing observations. The dissertation also describes several challenges facing business SMA today, along with supporting

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Liginlal, Divakaran. "Building fuzzy front-end decision support systems for new product information in global telecommunication markets: A measure theoretical approach." Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/284835.

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In today's highly competitive business environment, innovation and new product introduction are recognized as the sustaining forces of corporate success. The early phases of new product development, collectively known as the 'front-end', are crucial to the success of new products. Building a fuzzy front-end decision support system, balancing the needs for analytical soundness and model robustness while incorporating decision-maker's subjectivity and adaptability to different business situations, is a challenging task. A process model and a structural model focusing on the different forms of un

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Kruse, William John. "Utilizing collaborative technologies to create sustainable competitive advantage: Improving situation awareness to impact the decision-action cycle in the United States Navy." Diss., The University of Arizona, 2001. http://hdl.handle.net/10150/279801.

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This dissertation depicts a two-year effort to improve group situation awareness (SA) in the U.S. Navy's Third Fleet. The research contributions of this work are in three primary areas: (1) the study of behavioral, social and political factors that affect technology transition in the military, (2) the determination of the requirements for SA collaboration in the Navy, and (3) the development of a collaborative system to support distributed group SA. This research utilized the Technology Transition Model (TTM) to guide the development and fielding of a web-based, thin client prototype logging a

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Reynolds, Larry Arnold. "Managing uncertainty in environmental decision-making, the risky business of establishing a relationship between science and law." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ59660.pdf.

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Varvne, Matilda, Simon Cederholm, and Anton Medbo. "The Major Challenges in DDDM Implementation: A Single-Case Study : What are the Main Challenges for Business-to-Business MNCs to Implement a Data-Driven Decision-Making Strategy?" Thesis, Internationella Handelshögskolan, Jönköping University, IHH, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48842.

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Over the past years, the value of data and DDDM have increased significantly as technological advancements have made it possible to store and analyze large amounts of data at a reasonable cost. This has resulted in completely new business models that has disrupt whole industries. DDDM allows businesses to rely their decisions on data, as opposed to on gut feeling. Up until this point, literature is eligible to provide a general view of what are the major challenges corporations encounter when implementing a DDDM strategy. However, as the field is still rather new, the challenges identified are

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Pourshahid, Alireza. "A Framework for Monitoring and Adapting Business Processes Using Aspect-Oriented URN." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30958.

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Context: Organizations strive to improve their business processes, and adaptive business processes have recently attracted much attention in that context. However, much research in that area has a narrow focus and does not consider a comprehensive view of the organization and its goals. In addition, Business Intelligence-based monitoring methods are useful for business process improvement but they often present information in a format that is not entirely suited for decision making. Objectives: The main objectives of this thesis are to provide: • A framework to model goals, processes, perfo

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Sandema-Sombe, Christina Ndiwa. "Relationship Between Perceived Usefulness, Ease of Use, and Acceptance of Business Intelligence Systems." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/7736.

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In retail, the explosion of data sources and data has provided incentive to invest in information systems (IS), which enable leaders to understand the market and make timely decisions to improve performance. Given that users’ perceptions of IS affects their use of IS, understanding the factors influencing user acceptance is critical to acquiring an effective business intelligence system (BIS) for an organization. Grounded in the technology acceptance model theory, the purpose of this correlational study was to examine the relationship between perceived usefulness (PU), perceived ease of use (P

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Perugini, Leonardo. "Progettazione di un sistema di "Data Visualization" per l'analisi dei clienti in ambito Telecomunicazioni." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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In ambito aziendale, il valore dei processi di estrazione di conoscenza dai dati è in forte crescita grazie all’adozione di tecnologie e metodologie capaci di immagazzinare volumi molto estesi di informazioni. L’utilizzo di questi sistemi, vicini all’ambito del Data Mining, consente di condurre delle avanzate attività analitiche sui dati di business relativi a vari processi di produzione, vendita e gestione di imprese e altre organizzazioni. Le informazioni estraibili da queste analisi possono agevolare i processi decisionali, migliorando la competitività delle aziende che investono in queste

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Carlson, Olof, Viktor Thunmarker, and Mikael Zetterberg. "Exploring Swedish Hospitals’ Transition towards becoming more Data-Driven : A Qualitative Case Study of Two Swedish Hospitals." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176517.

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The Swedish health care sector must improve productivity in order to deal with anincreased demand from an aging population with limited resources. In the traditiondriven health care sector, transitioning towards becoming more data-driven has beenidentified as a potential solution. This explorative qualitative case study explores howindividual employees perceive this development at two Swedish hospitals. The resultscomplement theory by presenting propositions that explains drivers and barriers ofthe transition, but also the outcomes of it as perceived by the employees. The studyprimarily conclu

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