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Detalhe da Disciplina
Curso: Mestrado em Métodos Analíticos Avançados
Unidade curricular: Big Data Analytics
Semestre: Primavera
Número de créditos: 7,5
Número de horas de aula por semana: 2.00
Objetivos da unidade curricular:

Big data is a blanket term for the non-traditional strategies and technologies needed to gather, organize, process, and obtain insights from large datasets. In this course, we will discuss the challenges created by Big Data and the state-of-the-art approaches to deal with them.

During Lectures, we will overview the complex and heterogeneous Big Data ecosystem, and the privacy and societal implications brought by these technologies. A particular emphasis will be put on understanding the components that make up the popular Hadoop ecosystem (Hadoop, Hive, Kafka, Sqoop, and Spark). During the labs, students will obtain hands-on experience with Spark in the Databricks notebook environment.

Requisitos de frequência:

It is strongly recommended that students have familiarity with Python programming language, Terminal/Shell commands, and SQL.

Classes will be delivered in English. As such students are expected to have a good level of comprehension and communication in English.

Língua de ensino: Português. Em caso de existirem alunos ou professores estrangeiros, as aulas serão dadas em Inglês.

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