Tag Archives: Big Data

A Big Data Analysis with Machine Learning techniques in Accounting dataset from the Greek banking system (Published)

The effects of the 2008 financial crisis undoubtedly caused problems not only to the banking sector but also to the real economy of the developed and the developing countries in almost all around the globe. Besides, as is widely known, every banking crisis entails the corresponding cost to the economy of each country affected by it, which results from the shakeout and the restructuring of its financial system. The purpose of this research is to investigate the consequences of the financial crisis and the COVID-19 health crisis and how these affected the course of the four systemic banks (Eurobank, Alpha Bank, National Bank, Piraeus Bank) through the analysis of ratios for the period of 2015-2020.

Citation: Georgios L. Thanasas , Leonidas Theodorakopoulos , Spyridon Lampropoulos  (2022) A Big Data Analysis with Machine Learning techniques in Accounting dataset from the Greek banking system, European Journal of Accounting, Auditing and Finance Research, Vol.10, No. 8, pp.1-9,

Keywords: Big Data, COVID-19, Ratios, accounting data, financial crisis

Salient Issues in Marketing Analytics (Published)

Citation: Linus Osuagwu  (2022) Salient Issues in Marketing Analytics, British Journal of Marketing Studies, Vol. 10, Issue 1, pp.32-46,

Abstract: The paper utilized materials from relevant extant literature and cognate experience to discuss marketing analytics with regard to its tools, relationship with big data, applications and challenges, and proposes research direction in cognate areas. Specifically, the paper posits that marketing analytics has some salient issues such as equivocal conceptualizations, strong connections with big data, myriad of tools and applications, in addition to associated challenges. These stated salient issues may not be exhaustive enough to represent all the cognate issues associated with marketing analytics, especially in contemporary times. This is a major limitation of the paper which can be addressed in future research efforts. Therefore, relevant empirical research streams are suggested in the paper to investigate these salient and other cognate marketing analytics issues in different contexts, including sectors, business types, and countries. The insights from the paper are likely to have practical and theoretical implications and relevance for marketing managers, organizational researchers and data scientists, among others, regarding marketing analytics tools, applications, connections with big data, and implementation challenges.

Keywords: Big Data, Marketing, Marketing Analytics, data analytics, machine learning tools

An Improved Land Mapping and Geographical Information Management System Using Geodatabase (Published)

With data constantly increasing at a tremendous speed, it is crucial to have better knowledge of how information is manipulated and stored for subsequent retrieval and use. The data storage geodatabase strategy is introduced as dependable alternative based on acknowledged relational database concepts, which form foundation of selected database handling system. Simple but well-defined tables composed of distinctive features selected to store and handle spatial data and rule-base for every topographical dataset. In this paper, we developed an improved land mapping and Geographical Information System (GIS) using geodatabase. The study provides an enhanced approach to storing and managing data using a geodatabase, contributing to further research into alternative way of handling big data. Development of a web application that interacts with geodatabase for big data storage without the need of running multiple servers or enterprise class software. Thus this research is useful for those who have need for efficient data storage and management in today’s world of data size and complexities. By storing data within a geodatabase, one can draw from the benefits that come with its data management capabilities to leverage spatial information.

Keywords: Big Data, Geodatabase, NoSQL, ORDBMS, PostgreSQL, RDBMS, SQL

Opinion Mining In Big Data: Trend of Thinking for Big Data Era (Published)

This ear with the rapidly growing of internet and network using there are a huge data that have been introduced, Big Data are now on the double expanding rabidly in all domains, including opinion and sentiment analysis, for there are many social media and other websites that offer chances to provide the visitors and customers to post their opinion which usually contains valuable information that could be helpfully for several issues. And there are different methods and techniques that proposed to face this huge data and the big social data to make it more beneficial for several fields. This Paper   introduces the big data and the most common it is usage and challenge, and it also investigate the sentiment analysis and it is common techniques and thinking about it is futures. This paper also thinking about the future of big data and opinion mining is clearly discussed and thinking about the future of big data and opinion mining. And the paper will discuss the challenges that facing the big data and opinion mining. 

Keywords: Big Data, Data mining, Social media, opinion mining

Big Data: Technology, Opportunities and Challenges (Published)

Dealing with large amount of data and running analytics on those data is becoming challenging with rapidly increase in various types of data. Big data is the technology which deals with such large amount of data analytics. It covers wide range of application areas from managing data of social networking sites to the large amount of data on ecommerce portals for decision making. In this paper an attempt is made to present a review of State of Art technology in Big Data, its importance, major benefits and challenging in this domain.

Keywords: Big Data, HDFS, Hadoop, Hive, MapReduce, Medical Image Processing, Remote Sensing, Security