Accelerating Data Analysis in Simulation Neuroscience with Big Data Technologies

The Big Data technologies and the potential of their application in the music industry are reviewed in the article. The main questions raised concern the perspectives of the Big Data usage in the sociological and marketing research, the audience data analysis and the musical preferences of the audience. The Big Data allow to discover new artists and to find new ways of stimulating the audience’s loyalty. The author attempts to answer the question: how does the Big Data change the music industry? The possibility of using the Big Data to forecast the audience’s behavior is being reviewed. The examples of the Big Data technologies usage in the marketing research for the music industry are exposed. The author underlines the importance of this technology for sociologists and market researchers and brings into the light the problems of the Big Data usage. The attention is drawn to the development of the new sphere of musical data science and to the necessity of broadening the professional competencies of sociologists and music market researchers.

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An overview of big data analysis

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v9i4.2359 ◽

2020 ◽

Vol 9 (4) ◽

pp. 1646-1653

Author(s):

Fabio Arena ◽

Giovanni Pau

Keyword(s):

Big Data ◽

Data Analysis ◽

Customer Service ◽

Big Data Analytics ◽

Short Review ◽

Big Data Analysis ◽

Digital World ◽

Big Data Technologies ◽

Definition Of ◽

Smart Cars

Big data represents one of the most profound and most pervasive evolutions in the digital world. Examples of big data come from Internet of Things (IoT) devices, as well as smart cars, but also the use of social networks, industries, and so on. The sources of data are numerous and continuously increasing, and, therefore, what characterizes big data is not only the volume but also the complexity due to the heterogeneity of information that can be obtained. The fastest growth in spending on big data technologies is happening within banking, healthcare, insurance, securities and investment services, and telecommunications. Remarkably, three of those industries lie within the financial sector, which has many particularly serviceable use cases for big data analytics, such as fraud detection, risk management, and customer service optimization. In fact, the definition of big data analysis refers to the process that encompasses the gathering and analysis of big data to obtain useful information for the business. This paper focuses on delivering a short review concerning the current technologies, future perspectives, and the evaluation of some use cased associated with the analysis of big data.

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9.1. Big data analytics

Audit and Financial Analysis ◽

10.38097/afa.2020.84.50.037 ◽

2020 ◽

Author(s):

В.Т. Чая ◽

Н.И. Чупахина

Keyword(s):

Machine Learning ◽

Big Data ◽

Data Analysis ◽

Data Analytics ◽

Big Data Analytics ◽

Big Data Analysis ◽

Digital Economy ◽

Big Data Technologies

В связи с развитием технологий цифровой экономики возрастает по экспоненте и объем оцифрованной информации. Но информация имеет ценность, только если она анализируется определенным образом. Большие же объемы информации привычными методами анализировать невозможно. Речь уже идет о больших данных и технологиях больших данных. В статье описаны особенности больших данных. Рассмотрены методы и инструменты анализа больших данных. Подробно рассматривается такой метод решения задач на основе больших данных, как машинное обучение. In connection with the development of digital economy technologies, the volume of digitized information is growing exponentially. But information has value only if it is analyzed in a certain way. It is impossible to analyze large amounts of information using the usual methods. We are already talking about big data and big data technologies. The article describes the features of big data. Methods and tools for big data analysis are considered. Such a method of solving problems based on big data as machine learning is considered in detail.

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A Survey of Big Data Technologies and How Semantic Computing Can Help

International Journal of Semantic Computing ◽

10.1142/s1793351x14500056 ◽

2014 ◽

Vol 08 (01) ◽

pp. 99-117 ◽

Cited By ~ 5

Author(s):

Jennifer Kim ◽

George Wang ◽

Sang Tae Bae

Keyword(s):

Big Data ◽

Data Analysis ◽

Semantic Analysis ◽

Big Data Analysis ◽

Different Types ◽

Big Data Technologies ◽

Semantic Computing

In this article, we survey different types of big data techniques such as Hadoop, NoSQL, and R and how semantic computing can be utilized to improve these methods. We explain the terms big data and semantic analysis. We discuss how big data analysis and semantic analysis are utilized in different domains such as healthcare and business.

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Impact of CDR data analysis using big data technologies for the public: An analysis

2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS) ◽

10.1109/icaccs.2017.8014651 ◽

2017 ◽

Cited By ~ 1

Author(s):

Suja C Nair ◽

M. Sudeep Elayidom ◽

Sasi Gopalan

Keyword(s):

Big Data ◽

Data Analysis ◽

The Public ◽

Big Data Technologies

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THE FUTURE OF SMART INDUSTRY: TECHNOLOGIES, MACRO-TRENDS AND APPLICATION AREAS

DYNA INGENIERIA E INDUSTRIA ◽

10.6036/10342 ◽

2021 ◽

Vol 96 (6) ◽

pp. 561-562

Author(s):

MIKEL NIÑO

Keyword(s):

Machine Learning ◽

Cloud Computing ◽

Big Data ◽

Data Analysis ◽

Internet Of Things ◽

Machine Learning Algorithms ◽

The Internet ◽

Big Data Technologies ◽

Smart Industry ◽

The Internet Of Things

The Smart Industry has been developing has been developing at an accelerated pace since the beginning of the last decade, driven by of the last decade, driven by the by the emergence of technologies such as the Internet of Things, Compute of Things, Cloud Computing and Big Data Cloud Computing and Big Data technologies, as well as their connection and Big Data technologies, as well as their connection with machine learning algorithms for predictive data analysis [1] of data [1].

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