Analytical Study on Big Data

2018 ◽  
Vol 8 (5) ◽  
pp. 75
Author(s):  
Vivek Raich ◽  
Pankaj Maurya
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Decision Maker ◽  
Analytical Study ◽  
Large Data ◽  
Decision Makers ◽  
Continuous Increase ◽  
Analytic Methods ◽  
Data Store ◽  
Business Engineering

in the time of the Information Technology, the big data store is going on. Due to which, Huge amounts of data are available for decision makers, and this has resulted in the progress of information technology and its wide growth in many areas of business, engineering, medical, and scientific studies. Big data means that the size which is bigger in size, but there are several types, which are not easy to handle, technology is required to handle it. Due to continuous increase in the data in this way, it is important to study and manage these datasets by adjusting the requirements so that the necessary information can be obtained.The aim of this paper is to analyze some of the analytic methods and tools. Which can be applied to large data. In addition, the application of Big Data has been analyzed, using the Decision Maker working on big data and using enlightened information for different applications.

scholarly journals The impact of information technology in decision making process of companies in Kosovo

2018 ◽  
Vol 51 (1-2) ◽  
pp. 13-23
Author(s):  
Emin Qerim Neziraj ◽  
Aferdita Berisha Shaqiri
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Decision Maker ◽  
Business Process ◽  
New Technologies ◽  
Decision Makers ◽  
Decision Making Process ◽  
Or Organization ◽  
The Impact ◽  
Future Business

Before the decision makers set much higher requirements in the decision-making than ever before due to the environment of decision-makers subject to change under the influence of progress and development of new technologies, networking individual or organization inside and the outside environment, and modern means of communication enabling continuous inflow, flow and sharing of data and information. In these modern conditions the process of collecting, analyzing, selecting data and information to make informed decisions in the context of possible restrictions and the available options, and ultimately making decisions as the basis for future business or behavior, is not simplified. The use of new technologies in the decision-making process provided numerous opportunities to facilitate decisions selection. However, the decision maker should still be able to differentiate which knowledge should be used to serve in decision making, and which models, methods, tools, systems, and procedures to be used in certain situations, with the purpose of successful decision selection. In this paper, we will examine the decision making process during the business process of the companies in Kosovo.

Hotel and IT decision-maker characteristics and information technology adoption relationship in the hotel industry

2014 ◽  
Vol 5 (2) ◽  
pp. 194-206 ◽  
Author(s):  
Ahmet Bulent Ozturk ◽  
Murat Hancer
Keyword(s):  
Information Technology ◽  
Technology Adoption ◽  
Decision Maker ◽  
Hotel Industry ◽  
Education Level ◽  
Decision Makers ◽  
Rfid Technology ◽  
Job Tenure ◽  
Content Type ◽  
Intention To Adopt

Purpose – The purpose of this paper is to investigate the impact of hotel property characteristics and information technology (IT) decision-maker characteristics on radio frequency identification (RFID) technology adoption in the hotel industry. Design/methodology/approach – The data of the study were collected using the subscription list of Hospitality Financial and Technology Professionals (HFTP). A Web survey was used to collect the data of the study. An email invitation was sent out to invite the entire list of HFTP subscribers (3,080) to participate in the survey. Approximately 3,000 emails were delivered and 154 questionnaires were returned. Of 154 questionnaires, 125 were used in the study for further analyses. Analysis of variance (ANOVA) was used to determine whether hotel property characteristics (property size and chain affiliation) and IT decision-maker characteristics (age, education level and job tenure) differed on intention to adopt RFID technology. Findings – ANOVA results indicated that there were significant differences on intention to adopt RFID technology by property size and chain affiliation, IT decision-makers’ age, education level and job tenure. The results indicated that larger hotels and hotels that are part of a franchise are more likely to adopt RFID technology. In addition, IT decision-makers who are young, with high level of education and with shorter job tenure are more likely to adopt RFID technology. Originality/value – RFID technology is one of the recent technologies that gained great attention from the hotel operators in recent years. This study is one of the first studies in the hotel industry that provides valuable information to technology vendors for identifying potential RFID technology adopters in the hotel industry.

scholarly journals Big data analytics and international market selection: An exploratory study

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Jonathan Calof ◽  
Wilma Viviers
Keyword(s):  
Big Data ◽  
Decision Maker ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Organizational Factors ◽  
International Market ◽  
Decision Makers ◽  
Market Selection ◽  
Selection Decisions ◽  
The Impact

A great deal of information is available on international trade flows and potentialmarkets. Yet many exporters do not know how to identify, with adequate precision, thosemarkets that hold the greatest potential. Even if they have access to relevant information, thesheer volume of information often makes the analytical process complex, time-consuming andcostly. An additional challenge is that many exporters lack an appropriate decision-makingmethodology, which would enable them to adopt a systematic approach to choosing foreignmarkets. In this regard, big-data analytics can play a valuable role. This paper reports on thefirst two phases of a study aimed at exploring the impact of big-data analytics on internationalmarket selection decisions. The specific big-data analytics system used in the study was theTRADE-DSM (Decision Support Model) which, by screening large quantities of marketinformation obtained from a range of sources identifies optimal product‒market combinationsfor a country, industry sector or company. Interviews conducted with TRADE-DSM users aswell as decision-makers found that big-data analytics (using the TRADE-DSM model) didimpact international market-decision. A case study reported on in this paper noted thatTRADE-DSM was a very important information source used for making the company’sinternational market selection decision. Other interviewees reported that TRADE-DSMidentified countries (that were eventually selected) that the decision-makers had not previouslyconsidered. The degree of acceptance of the TRADE-DSM results appeared to be influenced byTRADE-DSM user factors (for example their relationship with the decision-maker andknowledge of the organization), decision-maker factors (for example their experience andknowledge making international market selection decisions) and organizational factors (forexample senior managements’ commitment to big data and analytics). Drawing on the insightsgained in the study, we developed a multi-phase, big-data analytics model for internationalmarket selection.

scholarly journals THE IMPACT OF MIGRATION OF SUDANESE UNIVERSITY PROFESSORS ON ECO-NOMIC DEVELOPMENT IN SUDAN, AN ANALYTICAL STUDY (2008-2012)

2020 ◽  
Vol 3 (Special Issue) ◽  
Keyword(s):  
Economic Development ◽  
Analytical Study ◽  
Decision Makers ◽  
University Professors ◽  
Continuous Increase ◽  
Economic Decision ◽  
Nomic Development ◽  
The Impact ◽  
Low Wages

This study aims to A study of the phenomenon of Sudanese university professors’ migration abroad and its impact on economic development through an analytical study that is carried out in an accurate scientific, The importance of this study comes in that the emigration of university professors abroad has become a significant and continuous increase from year to year, which prevents development in the country, and therefore this study and its results are expected to be useful for economic decision-makers in most countries, the study followed the approach Descriptive and analytical historical, and the most important results of the study are the migration of university professors, negatively affecting the economic development in Sudan, and low wages is one of the reasons for the migration of university professors.

The Origin and Development of Data Mining with Large Data

2014 ◽  
Vol 668-669 ◽  
pp. 1331-1334
Author(s):  
Hong Yu Ma ◽  
Gui Yun Zhang
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Big Data ◽  
Technology Development ◽  
Large Data ◽  
Growth Data ◽  
Information Technology Development ◽  
Special Meaning

With rapid information technology development, the accumulation of data and applications are becoming more and more urgent. Data is growing faster and faster, so "massive, explosive growth," words just can't describe today's data growth, data mining from the knowledge or information is found in the repository, which has special meaning for humans to deal with these data provide a convenient and effective way. Between big data and data mining technologies have an inseparable relationship.

scholarly journals Development of Big Data Analytics Model

2019 ◽  
Vol 4 (1) ◽  
pp. 14-25
Author(s):  
Saiful Rizal
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Big Data ◽  
Data Storage ◽  
Data Structures ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Large Data ◽  
Complex Data ◽  
Survey Paper

The development of information technology produces very large data sizes, with various variations in data and complex data structures. Traditional data storage techniques are not sufficient for storage and analysis with very large volumes of data. Many researchers conducted their research in analyzing big data with various analytics models in big data. Therefore, the purpose of the survey paper is to provide an understanding of analytics models in big data for various uses using algorithms in data mining. Preprocessing big data is the key to turning big data into big value.

scholarly journals Big Data and Analytics in Sport Management

2021 ◽  
pp. 1-6
Author(s):  
Nicholas M. Watanabe ◽  
Stephen Shapiro ◽  
Joris Drayer
Keyword(s):  
Big Data ◽  
Sport Management ◽  
Large Data ◽  
Decision Makers ◽  
Large Data Sets ◽  
Future Research ◽  
Data Sets ◽  
Management Research ◽  
Special Issue ◽  
Sport Industry

Big data and analytics have become an essential component of organizational operations. The ability to collect and interpret significantly large data sets has provided a wealth of knowledge to guide decision makers in all facets of society. This is no different in sport management where big data has been used on and off the field to guide decision making across the industry. As big data evolves, there are concerns regarding the use of enhanced analytic techniques and their advancement of knowledge and theory. This special issue addresses these concerns by advancing our understanding of the use of big data in sport management research and how it can be used to further scholarship in the sport industry. The six articles in this special issue each play a role in advancing sport analytics theory, producing new knowledge, and developing new inquiries. The implications discussed in these articles provide a foundation for future research on this evolving area within the field of sport management.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

AUTOMATIC EXCHANGE OF INFORMATION SEBAGAI BIG DATA DI BIDANG PERPAJAKAN

2018 ◽  
Vol 1 (1) ◽  
pp. 128-133
Author(s):  
Selvi Selvi
Keyword(s):  
Big Data ◽  
Developing Country ◽  
Research Method ◽  
Large Data ◽  
Economic Globalization ◽  
Literature Study ◽  
Related Literature ◽  
Exchange Of Information

Economic globalization between countries becomes commonplace. Differences in financial rules are used for many parties to practice the Basic Erosion and Shifting Profit (BEPS) which leads to state losses. In tackling it has been agreed to implement Automatic Exchange of Information (AEoI), which automatically converts data into large data in the field of taxation.The research method of this paper is a literature study which combines several related literature and global and national implications using secondary data.Drawing up the conclusion that AEoI challenges have been theoretically overcome by Indonesia as a developing country. However, practically mash has not been able to find out whether it can be overcome or not because Indonesia still has not implemented AEoI

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