scholarly journals IMPLEMENTATION OF BUSINESS INTELLIGENCE ON BANKING, RETAIL, AND EDUCATIONAL INDUSTRY

2013 ◽  
Vol 7 (2) ◽  
pp. 65 ◽  
Author(s):  
Arta Moro Sundjaja
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Business Process ◽  
Business Intelligence ◽  
Large Data ◽  
Daily Basis ◽  
Decision Making Process ◽  
Data Set ◽  
Large Data Set

Information technology is useful to automate business process involving considerable data transaction in the daily basis. Currently, companies have to tackle large data transaction which is difficult to be handled manually. It is very difficult for a person to manually extract useful information from a large data set despite of the fact that the information may be useful in decision-making process. This article studied and explored the implementation of business intelligence in banking, retail, and educational industries. The article begins with the exposition of business intelligence role in the industries; is followed by an illustration of business intelligence in the industries and finalized with the implication of business intelligence implementation.

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.

scholarly journals Relations between IT Architecture and Information Quality in DW and BI Environments

2012 ◽  
Author(s):  
Samuel Otero Schmidt ◽  
Edmir P. Vasques Prado ◽  
Hiroo Takaoka
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Research Method ◽  
Information Quality ◽  
Decision Making Process ◽  
Research Model ◽  
It Architecture

The organizations are investing more in information technology to collect, store and process vast amounts of information. Generally this information has no standard and repeated data, which hinders the decision making process. The cause of the difficulties is related to Information Quality (IQ) that has technical characteristics related to the architecture used in Data Warehouse (DW) and Business Intelligence (BI) environments. Based on the existing literature and insights from the author a research model was created to identify the relations between components of DW/BI architecture and IQ dimensions. We used the case study as research method. This research makes contributions to better understand IT architecture for DW/BI.

scholarly journals Data Cleaning Techniques for Large Data Sets

2020 ◽  
Vol 8 (6) ◽  
pp. 4453-4456
Keyword(s):  
Decision Making ◽  
Data Science ◽  
Missing Values ◽  
Data Cleaning ◽  
Large Data ◽  
Large Data Sets ◽  
Decision Making Process ◽  
Data Sets ◽  
Multiple Sources ◽  
Data Set

In today’s emerging era of data science where data plays a huge role for accurate decision making process it is very important to work on cleaned and irredundant data. As data is gathered from multiple sources it might contain anomalies, missing values etc. which needs to be removed this process is called data pre-processing. In this paper we perform data preprocessing on news popularity data set where extraction , transform and loading (ETL) is done .The outcome of the process is cleaned and refined news data set which can be used to do further analysis for knowledge discovery on popularity of news . Refined data give accurate predictions and can be better utilized in decision making process

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.

Climatology of nutrient distributions in the South China Sea based on a large data set derived from a new algorithm

2021 ◽  
pp. 102586
Author(s):  
Chuanjun Du ◽  
Ruoying He ◽  
Zhiyu Liu ◽  
Tao Huang ◽  
Lifang Wang ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Large Data ◽  
The South China Sea ◽  
The South ◽  
Data Set ◽  
China Sea ◽  
Large Data Set

scholarly journals Spike detection: Inter-reader agreement and a statistical Turing test on a large data set

2017 ◽  
Vol 128 (1) ◽  
pp. 243-250 ◽  
Author(s):  
Mark L. Scheuer ◽  
Anto Bagic ◽  
Scott B. Wilson
Keyword(s):  
Large Data ◽  
Turing Test ◽  
Spike Detection ◽  
Data Set ◽  
Large Data Set

Main large data set features detection by a linear predictor model

2014 ◽  
Author(s):  
Carlos Enrique Gutierrez ◽  
Prof. Mohamad Reza Alsharif ◽  
Mahdi Khosravy ◽  
Prof. Katsumi Yamashita ◽  
Prof. Hayao Miyagi ◽  
...  
Keyword(s):  
Large Data ◽  
Data Set ◽  
Linear Predictor ◽  
Large Data Set ◽  
Predictor Model

Governance Problems in Closely Held Corporations

2011 ◽  
Vol 46 (4) ◽  
pp. 943-966 ◽  
Author(s):  
Venky Nagar ◽  
Kathy Petroni ◽  
Daniel Wolfenzon
Keyword(s):  
Ownership Structure ◽  
Large Data ◽  
Minority Shareholders ◽  
Return On Assets ◽  
Data Set ◽  
Large Data Set ◽  
Ownership Rights ◽  
Shared Ownership

AbstractA major governance problem in closely held corporations is the majority shareholders’ expropriation of minority shareholders. As a solution, legal and finance research recommends that the main shareholder surrender some control to minority shareholders via ownership rights. We test this proposition on a large data set of closely held corporations. We find that shared-ownership firms report a substantially larger return on assets and lower expense-to-sales ratios. These findings are robust to institutionally motivated corrections for endogeneity of ownership structure. We provide evidence on the presence of governance problems and the effectiveness of shared ownership as a solution in settings characterized by illiquidity of ownership.

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