Top Research Papers on Big Data Analytics

Este artigo discute a precarização do trabalho sexual feminino no contexto brasileiro. Dessa forma, objetiva-se investigar como o trabalho sexual feminino realizado por mulheres cisgêneras, transgêneras e travestis se insere na lógica da precarização do trabalho, a partir das especificidades de cada vivência. Trata-se de um estudo interdisciplinar de perspectiva crítica, construído a partir de revisão bibliográfica e análise de literatura, ancorada na Sociologia do Trabalho, nos Estudos de Gênero e no Transfeminismo. A partir desse referencial, evidencia-se a urgência da regulamentação do trab...

If you are student with a disability who is requesting accommodation, please contact the Rutgers University Office of Disability Services at 848.445.6800 or by e-mail dsoffice@echo.rutgers.edu. For more details, please visit https://ods.rutgers.edu. The Office of Disability Services is located at Lucy Stone Hall, Suite A145, 54 Joyce Kilmer Ave., Piscataway, NJ 08854. To receive an accommodation, the Rutgers Office of Disability Services must approve your accommodation request.

This chapter proposes a support system that can guide the student to choose and to focus on the right course(s) based on their personal preferences, and provides the requisite information about educational frameworks and related data mining.

What is big data, how it is analysed, and some case studies illustrating the potentials and pitfalls of big data analytics are given.

This analysis illustrates that the Big Data analytics is a fast-growing, influential practice and a key enabler for the social business and is critical for success in the age of social media.

In NICT Real World Information Analytics Project, an ICT platform called xData (cross-data) platform is constructed for developing smart applications with harnessing the above technologies toward realization of smart and sustainable cities.

Benefits of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds and Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data.

In this chapter, the concepts of big data analytics along with the relevant description of different categorization, capabilities, challenges are firstly explained, and then big data Analytics techniques and methods are introduced and discussed to make the readers familiar with the way big data is applied in the enterprises.

This book extensively explores all facets of Big Data Analytics and comprehensively addresses the topic matter.

What is big data, how it is analysed, and some case studies illustrating the potentials and pitfalls of big data analytics are given.

This book deals with understanding of big data and use cases from selected business domains to understand big data, and the usage of Hadoop-related tools such as HBase, Cassandra, Pig, and Hive for big data analytics.

This chapter focuses on understanding the meaning and concept ofbig data, analytics of big data, its role in healthcare, various application areas, trends and tools used to process big data along with open problem challenges.

The basic theories, cutting-edge technologies and processing tools for big data analysis are introduced, and encountered opportunities and challenges are summarized, along with discussions about the development trend and future prospects of big dataAnalysis are discussed.

Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities.

Upon considering the analytics in the Big Data sector, predictive analytics and social media analytics are widely used for determining the pattern or trend which is about to happen.

The immense measure of organized, unstructured, and semi-organized information are produced each second around the cyber world, which should be managed efficiently.

This paper highlights new technologies and services that move the methodologies of old into the data-centric world of high volume and velocity that defines the modern information landscape.

This book explains how to make sense of your data by exploring technologies that are used to gather intelligence and looking at the future of analytics.

The definition of big data software is proposed as “software that supports the time-constrained processing of continuous information flows to provide actionable intelligence.”

Big data analytics have the potential to identify efficiencies that can be made in a wide range of sectors, and to lead to innovative new products and services, greater competitiveness and economic growth.