The Full Knowledge of Big Data in the Integration of Inter-Organizational Information

2017 ◽  
Vol 9 (1) ◽  
pp. 16-31 ◽  
Author(s):  
Thiago Poleto ◽  
Victor Diogho Heuer de Carvalho ◽  
Ana Paula Cabral Seixas Costa
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Decision Making Process ◽  
Data Repositories ◽  
Modeling And Analysis ◽  
Incremental Change ◽  
Working Together ◽  
Full Knowledge ◽  
Using Data

Big Data is a radical shift or an incremental change for the existing digital infrastructures, that include the toolset used to aid the decision making process such as information systems, data repositories, formal modeling, and analysis of decisions. This work aims to provide a theoretical approach about the elements necessary to apply the big data concept in the decision making process. It identifying key components of the big data to define an integrated model of decision making using data mining, business intelligence, decision support systems, and organizational learning all working together to provide decision support with a reliable visualization of the decision-related opportunities. The concepts of data integration and semantic also was explored in order to demonstrate that, once mined, data must be integrated, ensuring conceptual connections and bequeathing meaning to use them appropriately for problem solving in decision.

The Full Knowledge of Big Data in the Integration of Inter-Organizational Information

Web Services ◽  
2019 ◽  
pp. 803-821
Author(s):  
Thiago Poleto ◽  
Victor Diogho Heuer de Carvalho ◽  
Ana Paula Cabral Seixas Costa
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Decision Making Process ◽  
Data Repositories ◽  
Modeling And Analysis ◽  
Incremental Change ◽  
Working Together ◽  
Full Knowledge ◽  
Using Data

Big Data is a radical shift or an incremental change for the existing digital infrastructures, that include the toolset used to aid the decision making process such as information systems, data repositories, formal modeling, and analysis of decisions. This work aims to provide a theoretical approach about the elements necessary to apply the big data concept in the decision making process. It identifies key components of the big data to define an integrated model of decision making using data mining, business intelligence, decision support systems, and organizational learning all working together to provide decision support with a reliable visualization of the decision-related opportunities. The concepts of data integration and semantic also was explored in order to demonstrate that, once mined, data must be integrated, ensuring conceptual connections and bequeathing meaning to use them appropriately for problem solving in decision.

Models of decision support in socio-cyber-physical systems

2019 ◽  
pp. 55-70 ◽  
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Situation Awareness ◽  
Cyber Physical Systems ◽  
Emergent Behavior ◽  
Emergent Properties ◽  
Decision Making Process ◽  
Physical Systems ◽  
Decision Support Models ◽  
Common Goals

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.

Multivariable Automatisierungsentscheidungen*/Multivariate automation decisions – A tool for cost-benefit assessments as a basis for decision-making

2019 ◽  
Vol 109 (03) ◽  
pp. 134-139
Author(s):  
P. Burggräf ◽  
J. Wagner ◽  
M. Dannapfel ◽  
K. Müller ◽  
B. Koke
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Environmental Conditions ◽  
Cost Benefit ◽  
Decision Support Tool ◽  
Decision Making Process ◽  
Support Tool ◽  
Cost And Benefit ◽  
Benefit Evaluation ◽  
Level Of Automation

Der wachsende Bedarf an Wandlungsfähigkeit führt zu einer höheren Frequenz in der Umplanung von Montagesystemen und erfordert eine kontinuierliche Überprüfung und Anpassung des Automatisierungsgrades. Um auch die komplexen Umgebungsbedingungen abzubilden, sollen nicht-monetäre Faktoren in den Entscheidungsprozess eingebunden werden. Um die Entscheidung zu unterstützen, stellt dieser Beitrag ein Tool zur Identifizierung und Bewertung von Automatisierungsszenarien mittels einer Nutzwert-Aufwand-Analyse vor.   The increasing need for adaptability in assembly leads to a higher planning frequency of the system and requires continuous checks and adaptations of the appropriate level of automation. To account for the complex environmental conditions, non-monetary factors are included in the decision-making process. This paper presents a decision support tool to identify and evaluate automation scenarios by means of cost and benefit evaluation.

scholarly journals Analysis of Decision Making Process in Moneyball: The Art of Winning an Unfair Game

The Winners ◽  
2015 ◽  
Vol 16 (1) ◽  
pp. 57
Author(s):  
Mochamad Sandy Triady ◽  
Ami Fitri Utami
Keyword(s):  
Decision Making ◽  
Excellent Result ◽  
Data Driven ◽  
Decision Making Process ◽  
Data Driven Decision Making ◽  
General Manager ◽  
Use Of Data ◽  
Bottom Position ◽  
Using Data ◽  
Baseball Team

Billy Beanes’s success in using data-driven decision making in baseball industry is wonderfully written by Michael Lewis in Moneyball. As a general manager in baseball team that were in the bottom position of the league from the financial side to acquire the players, Beane, along with his partner, explored the use of data in choosing the team’s player. They figured out how to determine the worth of every player.The process was not smooth, due to the condition of baseball industry that was not common with using advanced statistic in acquiring   players. Many teams still use the old paradigm that rely on experts’ judgments, intuition, or experience in decision making process. Moneyball approached that using data-driven decision making gave excellent result for Beane’s team. The team won 20 gamessequently in the 2002 season and also spent the lowest cost per win than other teams.This paper attempts to review the principles of Moneyball – The Art of Winning an Unfair Game as a process of decision making and gives what we can learn from the story in order to win the games, the unfair games.

scholarly journals Uncertainties in complex dynamic environments

2014 ◽  
Vol Volume 2 ◽  
Author(s):  
Hasmik Atoyan ◽  
Jean-Marc Robert ◽  
Jean-Rémi Duquet
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
User Interfaces ◽  
Dynamic Environments ◽  
Decision Making Process ◽  
Uncertain Information ◽  
Complex Environments ◽  
Complex Dynamic ◽  
Different Types ◽  
Machine Systems

The utilization of Decision Support Systems (DSS) in complex dynamic environments leads the human operator almost inevitably to having to face several types of uncertainties. Thus it is essential for system designers to clearly understand the different types of uncertainties that could exist in human-machine systems of complex environments, to know their impacts on the operator's trust in the systems and decision-making process, and to have guidelines on how to present uncertain information on user interfaces. It is also essential for them to have an overview of the different stages, levels, and types of system automation, and to know their possible impacts on the creation of different types of uncertainties. This paper investigates these topics and aim at helping researchers and practitioners to deal with uncertainties in complex environments.

scholarly journals Sistem Pendukung Keputusan Penyeleksian Colour Guard Pada Marching Band Ginada Dengan Menggunakan Metode Vikor Dan Borda

2020 ◽  
Vol 2 (1) ◽  
pp. 35-48
Author(s):  
Nurjannah ◽  
Dito Putro Utomo
Keyword(s):  
High School ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Body Language ◽  
Routine Activity ◽  
Decision Making Process ◽  
Marching Band

Decision support system for selecting color guard with VIKOR and Borda methods. It has been made as a tool to select color guard at the Sei Rampah High School. The criteria used in the decision support system for color guard selection are: height, weight, agility, stamina, and body language. Color guard selection activities are a routine activity every year, so GINADA marching band coach Sei Rampah hereby selects to select permanent members in the marching band. Decision Support System in an organization can be seen as important in supporting the smooth running of activities and achieving an organizational goal. SPK can come in various forms, ranging from simple forms of data processing to complex application forms, and can also be used to accelerate and improve the quality of the decision-making process in the organization.

scholarly journals Support of decision-making under risk by a risk-averse decision-maker

2020 ◽  
Vol 13 ◽  
Author(s):  
Andrzej Łodziński
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Maker ◽  
The State ◽  
Decision Making Process ◽  
Discrete Problem ◽  
Risk Averse ◽  
Control Parameters ◽  
Decision Making Under Risk ◽  
State Of The Environment

The paper presents the decision support under risk by the risk averse decision maker. Decision making under risk occurs when the result of the decision is not unequivocal and depends on the state of the environment. The decision making process is modeled with the use of multi-criteria optimization. The decision is made by solving the problem with the control parameters that determine the decision maker's aspirations and the evaluation of the solutions received. The decision maker asks the parameter for which the solution is determined. Then, evaluate the solution received accepting or rejecting it. In the second case, the decision maker gives a new parameter value and the problem is solved again for the new parameter. The work includes an simple discrete problem of decision support under risk

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