Putting Big Data at the Heart of the Decision-­Making Process

2013 ◽  
pp. 153-170 ◽  
Author(s):  
Ian Thomas
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Making Process

Big Data Myth

2019 ◽  
pp. 223-237
Author(s):  
Agata Mardosz-Grabowska
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Qualitative Data ◽  
New Technologies ◽  
Marketing Management ◽  
Individual Experience ◽  
Decision Making Process

Organizations are expected to act rationally; however, mythical thinking is often present among their members. It refers also to myths related to technology. New inventions and technologies are often mythologized in organizations. People do not understand how new technologies work and usually overestimate their possibilities. Also, myths are useful in dealing with ambivalent feelings, such as fears and hopes. The text focuses on the so-called “big data myth” and its impact on the decision-making process in modern marketing management. Mythical thinking related to big data in organizations has been observed both by scholars and practitioners. The aim of the chapter is to discuss the foundation of the myth, its components, and its impact on the decision-making process. Among others, a presence of a “big data myth” may be manifested by over-reliance on data, neglecting biases in the process of data analysis, and undermining the role of other factors, including intuition and individual experience of marketing professionals or qualitative data.

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.

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.

scholarly journals DATAFICATION AS A NECESSARY STEP IN THE PROCESSING OF BIG DATA IN DECISION-MAKING TASKS OF BUSINESS

2021 ◽  
Vol 2 ◽  
pp. 75-80
Author(s):  
Martin Misut ◽  
Pavol Jurik
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Quantitative Methods ◽  
Digital Data ◽  
Classification Model ◽  
Decision Making Process ◽  
Digital Form ◽  
Suitable Alternative ◽  
The Given ◽  
The Relationship

The digital transformation of business in the light of opportunities and focusing on the challenges posed by the introduction of Big Data in enterprises allows for a more accurate reflection of the internal and external environmental stimuli. Intuition ceases to be present in the decision-making process, and decision-making becomes strictly data-based. Thus, the precondition for data-based decision-making is relevant data in digital form, resulting from data processing. Datafication is the process by which subjects, objects and procedures are transformed into digital data. Only after data collection can other natural steps occur to acquire knowledge to improve the company's results if we move in the industry's functioning context. The task of finding a set of attributes (selecting attributes from a set of available attributes) so that a suitable alternative can be determined in its decision-making is analogous to the task of classification. Decision trees are suitable for solving such a task. We verified the proposed method in the case of logistics tasks. The analysis subject was tasks from logistics and 80 well-described quantitative methods used in logistics to solve them. The result of the analysis is a matrix (table), in which the rows contain the values of individual attributes defining a specific logistic task. The columns contain the values of the given attribute for different tasks. We used Incremental Wrapper Subset Selection IWSS package Weka 3.8.4 to select attributes. The resulting classification model is suitable for use in DSS. The analysis of logistics tasks and the subsequent design of a classification model made it possible to reveal the contours of the relationship between the characteristics of a logistics problem explicitly expressed through a set of attributes and the classes of methods used to solve them.

scholarly journals A functional framework based on big data analytics for smart farming

2021 ◽  
Vol 24 (3) ◽  
pp. 1772
Author(s):  
Loubna Rabhi ◽  
Noureddine Falih ◽  
Lekbir Afraites ◽  
Belaid Bouikhalene
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
New Products ◽  
Big Data Analytics ◽  
Decision Making Process ◽  
Time Production ◽  
Smart Farming ◽  
The Future

Big <span>data in agriculture is defined as massive volumes of data with a wide variety of sources and types which can be captured using internet of things sensors (soil and crops sensors, drones, and meteorological stations), analyzed and used for decision-making. In the era of internet of things (IoT) tools, connected agriculture has appeared. Big data outputs can be exploited by the future connected agriculture in order to reduce cost and time production, improve yield, develop new products, offer optimization and smart decision-making. In this article, we propose a functional framework to model the decision-making process in digital and connected agriculture</span>.

scholarly journals BIG DATA IN THE DECISION-MAKING PROCESS IN PUBLIC POLICY: FROM ANALYSIS OF THEORIES TO EVALUATING THE EFFECTIVENESS OF PRACTICES

2021 ◽  
Vol 15 (3) ◽  
pp. 40-51
Author(s):  
S. А. Shmeleva ◽  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Public Administration ◽  
Extensive Study ◽  
Theoretical Research ◽  
The Political ◽  
Decision Making Process ◽  
Political Decision ◽  
Potential Benefits ◽  
Political Decision Making

This article analyzes the theoretical research base of the last decade on the use of big data in the decision-making process in public administration and describes the methodology proposed by Van der Voort for eval-uating the influence of the two elements on each other. Based on the analysis, it is concluded that there is an extensive study of the use of big data in public administration with an emphasis on potential benefits and threats that conditionally divides researchers into techno-optimists and techno-pessimists. Most studies are empirical in nature, however, they are fragmented and use different approaches to identify the relationships between big data and political decision making. The question arises as to how can we verify or evaluate the relationship between big data and the political decision-making process, taking into account both the dubious reliability of the data used in the process and the interests of decision-makers. The article describes the methodology proposed by Van der Voort for assessing these relationships taking into account the role of ac-tors in the political decision-making process using big data, as well as their interests and values.

Sign in / Sign up

Export Citation Format

Share Document