Apache Hadoop é uma implementação de código aberto de duas soluções básicas BigData do Google: GFS (Google File System) e MapReduce programming paradigm é um framework completo destinado ao armazenamento e processamento de grandes blocos de dados. Hadoop é usado por grande parte dos fornecedores de serviços na nuvem, incluindo os líderes como Yahoo, Facebook e LinkedIn. Os cursos de treinamento ao vivo do Apache Hadoop demonstram, por meio de discussões e prática prática, os principais componentes do ecossistema Hadoop e como essas tecnologias podem ser usadas para resolver problemas de larga escala. O treinamento do Hadoop está disponível em vários formatos, incluindo treinamento ao vivo no local e treinamento online ao vivo e interativo. O treinamento ao vivo no local pode ser realizado nas instalações do cliente no Portugal ou nos centros de treinamento locais NobleProg no Portugal. O treinamento ao vivo remoto é realizado por meio de uma área de trabalho remota e interativa.
NobleProg -- Seu Provedor de Treinamento Local
Declaração de Clientes
O fato de que todos os dados e software estavam prontos para uso em uma VM já preparada, fornecida pelo instrutor em discos externos.
vyzVoice
Curso: Hadoop for Developers and Administrators
Machine Translated
Eu gostei principalmente do treinador dando exemplos reais ao vivo.
Simon Hahn
Curso: Administrator Training for Apache Hadoop
Machine Translated
Eu gostei genuinamente das grandes competências do Trainer.
Grzegorz Gorski
Curso: Administrator Training for Apache Hadoop
Machine Translated
Eu realmente gostei das muitas sessões práticas.
Jacek Pieczątka
Curso: Administrator Training for Apache Hadoop
Machine Translated
Gostei muito da forma interativa de aprender.
Luigi Loiacono
Curso: Data Analysis with Hive/HiveQL
Machine Translated
Foi um treinamento muito prático, gostei dos exercícios práticos.
Proximus
Curso: Data Analysis with Hive/HiveQL
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Eu fui beneficiado pela boa visão geral, bom equilíbrio entre teoria e exercícios.
Proximus
Curso: Data Analysis with Hive/HiveQL
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Gostei da interação dinâmica e “hands-on” do assunto, graças à Máquina Virtual, muito estimulante !.
Philippe Job
Curso: Data Analysis with Hive/HiveQL
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Eu me beneficiei da competência e conhecimento do treinador.
Jonathan Puvilland
Curso: Data Analysis with Hive/HiveQL
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Foi muito prático, passamos a metade do tempo realmente fazendo as coisas no Clouded / Hardtop, executando diferentes comandos, verificando o sistema e assim por diante. Os materiais extras (livros, sites, etc.) foram muito apreciados, teremos que continuar aprendendo. As instalações foram muito divertidas e muito úteis, a configuração do cluster a partir do zero foi muito boa.
Ericsson
Curso: Administrator Training for Apache Hadoop
Machine Translated
O treinador era fantástico e realmente conhecia suas coisas. Eu aprendi muito sobre o software que eu não conhecia anteriormente, o que vai ajudar muito no meu trabalho !.
Steve McPhail - Alberta Health Services - Information Technology
Curso: Data Analysis with Hive/HiveQL
Machine Translated
Os princípios de alto nível sobre Hive, HDFS ...
Geert Suys - Proximus Group
Curso: Data Analysis with Hive/HiveQL
Machine Translated
O handson. O mix de prática / theroy
Proximus Group
Curso: Data Analysis with Hive/HiveQL
Machine Translated
A Fulvio conseguiu entender o caso de negócios de nossas empresas e conseguiu se correlacionar com o material do curso quase instantaneamente.
Samuel Peeters - Proximus Group
Curso: Data Analysis with Hive/HiveQL
Machine Translated
Muitos exercícios práticos.
Ericsson
Curso: Administrator Training for Apache Hadoop
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Ferramenta de gerenciamento Ambari. Capacidade de discutir experiências práticas do Hadoop de outros casos de negócios que de telecomunicações.
Ericsson
Curso: Administrator Training for Apache Hadoop
Machine Translated
Eu pensei que ele fez um grande trabalho de alfaiataria a experiência para o público. Essa classe é projetada principalmente para cobrir a análise de dados com o HIVE, mas eu e meu colega de trabalho estamos fazendo a administração do HIVE sem responsabilidades reais de análise de dados.
ian reif - Franchise Tax Board
Curso: Data Analysis with Hive/HiveQL
Machine Translated
A VM que eu gostei muito O professor foi muito conhecedor sobre o tema, bem como outros temas, ele foi muito agradável e amigável Gostei da instalação em Dubai.
Safar Alqahtani - Elm Information Security
Curso: Big Data Analytics in Health
Machine Translated
Tópicos de treinamento e engajamento do instrutor
Izba Administracji Skarbowej w Lublinie
Curso: Apache NiFi for Administrators
Machine Translated
Comunicação com pessoas que frequentam treinamentos.
Andrzej Szewczuk - Izba Administracji Skarbowej w Lublinie
Curso: Apache NiFi for Administrators
Machine Translated
coisas práticas de fazer, também a teoria foi bem servida por Ajay
Dominik Mazur - Capgemini Polska Sp. z o.o.
Curso: Hadoop Administration on MapR
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Exercícios
Capgemini Polska Sp. z o.o.
Curso: Hadoop Administration on MapR
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utilidade dos exercícios
Algomine sp.z.o.o sp.k.
Curso: Apache NiFi for Administrators
Machine Translated
Eu achei o treinamento bom, muito informativo ... mas poderia ter sido espalhado por 4 ou 5 dias, permitindo-nos entrar em mais detalhes sobre diferentes aspectos.
Veterans Affairs Canada
Curso: Hadoop Administration
Machine Translated
Eu realmente gostei do treinamento. Anton tem muito conhecimento e expôs a teoria necessária de uma forma muito acessível. É ótimo que o treinamento tenha sido um monte de exercícios interessantes, então estamos em contato com a tecnologia que conhecemos desde o início.
Szymon Dybczak - Algomine sp.z.o.o sp.k.
Curso: Apache NiFi for Administrators
Machine Translated
Eu encontrei este curso deu uma ótima visão geral e rapidamente tocou em algumas áreas que eu nem estava considerando.
Veterans Affairs Canada
Curso: Hadoop Administration
Machine Translated
Eu realmente gostei de exercícios de trabalho com cluster para ver o desempenho dos nós no cluster e a funcionalidade estendida.
CACI Ltd
Curso: Apache NiFi for Developers
Machine Translated
Ajay era um consultor muito experiente, capaz de responder a todas as nossas perguntas e até fez sugestões sobre as melhores práticas para o projeto em que estamos envolvidos atualmente.
CACI Ltd
Curso: Apache NiFi for Administrators
Machine Translated
Parte prática. As tarefas foram bem escolhidas para as questões discutidas.
Rossmann SDP
Curso: HBase for Developers
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Subcategorias Apache Hadoop
Programa de curso Apache Hadoop
Nome do Curso
Duração
Visão geral
Nome do Curso
Duração
Visão geral
21 horas
Visão geral
Este curso é dedicado à especialistas TI que buscam soluções para guardas e processar grandes sets de dados num ambiente de sistema distribuido.
Objetivo de cursio: Conseguir conhecimento sobre Hadoop cluster administration.
Objetivo de cursio: Conseguir conhecimento sobre Hadoop cluster administration.
35 horas
Visão geral
Público:
O curso destina-se a especialistas em TI que procuram uma solução para armazenar e processar grandes conjuntos de dados em um ambiente de sistema distribuído
Go ai:
Profundo conhecimento em administração de cluster do Hadoop .
O curso destina-se a especialistas em TI que procuram uma solução para armazenar e processar grandes conjuntos de dados em um ambiente de sistema distribuído
Go ai:
Profundo conhecimento em administração de cluster do Hadoop .
28 horas
Visão geral
Audience:
This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand.
This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand.
28 horas
Visão geral
Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop ecosystem.
21 horas
Visão geral
Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase. These advanced programming techniques will be beneficial to experienced Hadoop developers.
Audience: developers
Duration: three days
Format: lectures (50%) and hands-on labs (50%).
Audience: developers
Duration: three days
Format: lectures (50%) and hands-on labs (50%).
21 horas
Visão geral
Este curso introduz HBase, e é dirigido a todos aqueles desenvolvedores que utilizarão o HBase para desenvolver aplicações, e administradores que vao manejar clusters HBase.
Vamos a guiar um desenvolvedor através da arquitetura HBase e modelagem de dados e desenvolvimento de aplicações em HBase. Também vamos discutir utilizando MapReduce com HBase, e alguns tópicos administrativos.
Vamos a guiar um desenvolvedor através da arquitetura HBase e modelagem de dados e desenvolvimento de aplicações em HBase. Também vamos discutir utilizando MapReduce com HBase, e alguns tópicos administrativos.
21 horas
Visão geral
Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. In this three (optionally, four) days course, attendees will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan cluster deployment and growth, how to install, maintain, monitor, troubleshoot and optimize Hadoop. They will also practice cluster bulk data load, get familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course finishes off with discussion of securing cluster with Kerberos.
“…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized”
— Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising
Audience
Hadoop administrators
Format
Lectures and hands-on labs, approximate balance 60% lectures, 40% labs.
“…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized”
— Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising
Audience
Hadoop administrators
Format
Lectures and hands-on labs, approximate balance 60% lectures, 40% labs.
21 horas
Visão geral
Apache Hadoop is the most popular framework for processing Big Data. Hadoop provides rich and deep analytics capability, and it is making in-roads in to tradional BI analytics world. This course will introduce an analyst to the core components of Hadoop eco system and its analytics
Audience
Business Analysts
Duration
three days
Format
Lectures and hands on labs.
Audience
Business Analysts
Duration
three days
Format
Lectures and hands on labs.
21 horas
Visão geral
Hadoop is the most popular Big Data processing framework.
14 horas
Visão geral
Audience
- Developers
Format of the Course
- Lectures, hands-on practice, small tests along the way to gauge understanding
- Developers
Format of the Course
- Lectures, hands-on practice, small tests along the way to gauge understanding
21 horas
Visão geral
This course is intended for developers, architects, data scientists or any profile that requires access to data either intensively or on a regular basis.
The major focus of the course is data manipulation and transformation.
Among the tools in the Hadoop ecosystem this course includes the use of Pig and Hive both of which are heavily used for data transformation and manipulation.
This training also addresses performance metrics and performance optimisation.
The course is entirely hands on and is punctuated by presentations of the theoretical aspects.
The major focus of the course is data manipulation and transformation.
Among the tools in the Hadoop ecosystem this course includes the use of Pig and Hive both of which are heavily used for data transformation and manipulation.
This training also addresses performance metrics and performance optimisation.
The course is entirely hands on and is punctuated by presentations of the theoretical aspects.
14 horas
Visão geral
As more and more software and IT projects migrate from local processing and data management to distributed processing and big data storage, Project Managers are finding the need to upgrade their knowledge and skills to grasp the concepts and practices relevant to Big Data projects and opportunities.
This course introduces Project Managers to the most popular Big Data processing framework: Hadoop.
In this instructor-led training, participants will learn the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems. In learning these foundations, participants will also improve their ability to communicate with the developers and implementers of these systems as well as the data scientists and analysts that many IT projects involve.
Audience
- Project Managers wishing to implement Hadoop into their existing development or IT infrastructure
- Project Managers needing to communicate with cross-functional teams that include big data engineers, data scientists and business analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This course introduces Project Managers to the most popular Big Data processing framework: Hadoop.
In this instructor-led training, participants will learn the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems. In learning these foundations, participants will also improve their ability to communicate with the developers and implementers of these systems as well as the data scientists and analysts that many IT projects involve.
Audience
- Project Managers wishing to implement Hadoop into their existing development or IT infrastructure
- Project Managers needing to communicate with cross-functional teams that include big data engineers, data scientists and business analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 horas
Visão geral
Apache Samza is an open-source near-realtime, asynchronous computational framework for stream processing. It uses Apache Kafka for messaging, and Apache Hadoop YARN for fault tolerance, processor isolation, security, and resource management.
This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.
By the end of this training, participants will be able to:
- Use Samza to simplify the code needed to produce and consume messages.
- Decouple the handling of messages from an application.
- Use Samza to implement near-realtime asynchronous computation.
- Use stream processing to provide a higher level of abstraction over messaging systems.
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.
By the end of this training, participants will be able to:
- Use Samza to simplify the code needed to produce and consume messages.
- Decouple the handling of messages from an application.
- Use Samza to implement near-realtime asynchronous computation.
- Use stream processing to provide a higher level of abstraction over messaging systems.
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
7 horas
Visão geral
Alluxio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba.
In this instructor-led, live training, participants will learn how to use Alluxio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio.
By the end of this training, participants will be able to:
- Develop an application with Alluxio
- Connect big data systems and applications while preserving one namespace
- Efficiently extract value from big data in any storage format
- Improve workload performance
- Deploy and manage Alluxio standalone or clustered
Audience
- Data scientist
- Developer
- System administrator
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use Alluxio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio.
By the end of this training, participants will be able to:
- Develop an application with Alluxio
- Connect big data systems and applications while preserving one namespace
- Efficiently extract value from big data in any storage format
- Improve workload performance
- Deploy and manage Alluxio standalone or clustered
Audience
- Data scientist
- Developer
- System administrator
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 horas
Visão geral
Tigon is an open-source, real-time, low-latency, high-throughput, native YARN, stream processing framework that sits on top of HDFS and HBase for persistence. Tigon applications address use cases such as network intrusion detection and analytics, social media market analysis, location analytics, and real-time recommendations to users.
This instructor-led, live training introduces Tigon's approach to blending real-time and batch processing as it walks participants through the creation a sample application.
By the end of this training, participants will be able to:
- Create powerful, stream processing applications for handling large volumes of data
- Process stream sources such as Twitter and Webserver Logs
- Use Tigon for rapid joining, filtering, and aggregating of streams
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training introduces Tigon's approach to blending real-time and batch processing as it walks participants through the creation a sample application.
By the end of this training, participants will be able to:
- Create powerful, stream processing applications for handling large volumes of data
- Process stream sources such as Twitter and Webserver Logs
- Use Tigon for rapid joining, filtering, and aggregating of streams
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 horas
Visão geral
Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion.
In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.
By the end of this training, participants will be able to:
- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results
Audience
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.
By the end of this training, participants will be able to:
- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results
Audience
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21 horas
Visão geral
In this instructor-led, live training in Portugal (onsite or remote), participants will learn how to deploy and manage Apache NiFi in a live lab environment.
By the end of this training, participants will be able to:
- Install and configure Apachi NiFi.
- Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes.
- Automate dataflows.
- Enable streaming analytics.
- Apply various approaches for data ingestion.
- Transform Big Data and into business insights.
By the end of this training, participants will be able to:
- Install and configure Apachi NiFi.
- Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes.
- Automate dataflows.
- Enable streaming analytics.
- Apply various approaches for data ingestion.
- Transform Big Data and into business insights.
7 horas
Visão geral
In this instructor-led, live training in Portugal, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi.
By the end of this training, participants will be able to:
- Understand NiFi's architecture and dataflow concepts.
- Develop extensions using NiFi and third-party APIs.
- Custom develop their own Apache Nifi processor.
- Ingest and process real-time data from disparate and uncommon file formats and data sources.
By the end of this training, participants will be able to:
- Understand NiFi's architecture and dataflow concepts.
- Develop extensions using NiFi and third-party APIs.
- Custom develop their own Apache Nifi processor.
- Ingest and process real-time data from disparate and uncommon file formats and data sources.
28 horas
Visão geral
Hadoop is a popular Big Data processing framework. Python is a high-level programming language famous for its clear syntax and code readibility.
In this instructor-led, live training, participants will learn how to work with Hadoop, MapReduce, Pig, and Spark using Python as they step through multiple examples and use cases.
By the end of this training, participants will be able to:
- Understand the basic concepts behind Hadoop, MapReduce, Pig, and Spark
- Use Python with Hadoop Distributed File System (HDFS), MapReduce, Pig, and Spark
- Use Snakebite to programmatically access HDFS within Python
- Use mrjob to write MapReduce jobs in Python
- Write Spark programs with Python
- Extend the functionality of pig using Python UDFs
- Manage MapReduce jobs and Pig scripts using Luigi
Audience
- Developers
- IT Professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to work with Hadoop, MapReduce, Pig, and Spark using Python as they step through multiple examples and use cases.
By the end of this training, participants will be able to:
- Understand the basic concepts behind Hadoop, MapReduce, Pig, and Spark
- Use Python with Hadoop Distributed File System (HDFS), MapReduce, Pig, and Spark
- Use Snakebite to programmatically access HDFS within Python
- Use mrjob to write MapReduce jobs in Python
- Write Spark programs with Python
- Extend the functionality of pig using Python UDFs
- Manage MapReduce jobs and Pig scripts using Luigi
Audience
- Developers
- IT Professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 horas
Visão geral
Sqoop is an open source software tool for transfering data between Hadoop and relational databases or mainframes. It can be used to import data from a relational database management system (RDBMS) such as MySQL or Oracle or a mainframe into the Hadoop Distributed File System (HDFS). Thereafter, the data can be transformed in Hadoop MapReduce, and then re-exported back into an RDBMS.
In this instructor-led, live training, participants will learn how to use Sqoop to import data from a traditional relational database to Hadoop storage such HDFS or Hive and vice versa.
By the end of this training, participants will be able to:
- Install and configure Sqoop
- Import data from MySQL to HDFS and Hive
- Import data from HDFS and Hive to MySQL
Audience
- System administrators
- Data engineers
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training, participants will learn how to use Sqoop to import data from a traditional relational database to Hadoop storage such HDFS or Hive and vice versa.
By the end of this training, participants will be able to:
- Install and configure Sqoop
- Import data from MySQL to HDFS and Hive
- Import data from HDFS and Hive to MySQL
Audience
- System administrators
- Data engineers
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
21 horas
Visão geral
Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights.
The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment.
In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises.
By the end of this training, participants will be able to:
- Install and configure big data analytics tools such as Hadoop MapReduce and Spark
- Understand the characteristics of medical data
- Apply big data techniques to deal with medical data
- Study big data systems and algorithms in the context of health applications
Audience
- Developers
- Data Scientists
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice.
Note
- To request a customized training for this course, please contact us to arrange.
The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment.
In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises.
By the end of this training, participants will be able to:
- Install and configure big data analytics tools such as Hadoop MapReduce and Spark
- Understand the characteristics of medical data
- Apply big data techniques to deal with medical data
- Study big data systems and algorithms in the context of health applications
Audience
- Developers
- Data Scientists
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice.
Note
- To request a customized training for this course, please contact us to arrange.
7 horas
Visão geral
Este curso cobre o básico sobre como utilizar a linguagem Hive SQL, para todas aquelas pessoas que querem extraír dados do Hive. O objetivo deste curso é proporcionar todas as ferramentas necessárias para que os participantes possam analizar os dados de forma clara e precisa.
21 horas
Visão geral
O Cloudera Impala é um query engine SQL MPP de código aberto feito para clusters Apache Hadoop.
Ele permite aos usuarios a abertura de queries SQL de latencia baixa para todos os dados guardados no Hadoop Distributed File System e Apache Hbase sem requerir movimento de dados ou transformacao.
Este curso vai dirigido a analistas de sistemas e cientístas de dados.
Ele permite aos usuarios a abertura de queries SQL de latencia baixa para todos os dados guardados no Hadoop Distributed File System e Apache Hbase sem requerir movimento de dados ou transformacao.
Este curso vai dirigido a analistas de sistemas e cientístas de dados.
21 horas
Visão geral
Apache Ambari is an open-source management platform for provisioning, managing, monitoring and securing Apache Hadoop clusters.
In this instructor-led live training participants will learn the management tools and practices provided by Ambari to successfully manage Hadoop clusters.
By the end of this training, participants will be able to:
- Set up a live Big Data cluster using Ambari
- Apply Ambari's advanced features and functionalities to various use cases
- Seamlessly add and remove nodes as needed
- Improve a Hadoop cluster's performance through tuning and tweaking
Audience
- DevOps
- System Administrators
- DBAs
- Hadoop testing professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led live training participants will learn the management tools and practices provided by Ambari to successfully manage Hadoop clusters.
By the end of this training, participants will be able to:
- Set up a live Big Data cluster using Ambari
- Apply Ambari's advanced features and functionalities to various use cases
- Seamlessly add and remove nodes as needed
- Improve a Hadoop cluster's performance through tuning and tweaking
Audience
- DevOps
- System Administrators
- DBAs
- Hadoop testing professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21 horas
Visão geral
This instructor-led, live training in (online or onsite) introduces Hortonworks Data Platform (HDP) and walks participants through the deployment of Spark + Hadoop solution.
By the end of this training, participants will be able to:
- Use Hortonworks to reliably run Hadoop at a large scale.
- Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
- Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
- Process different types of data, including structured, unstructured, in-motion, and at-rest.
By the end of this training, participants will be able to:
- Use Hortonworks to reliably run Hadoop at a large scale.
- Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
- Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
- Process different types of data, including structured, unstructured, in-motion, and at-rest.
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21 horas
Consultoria
Cursos de fim de semana de Hadoop, Treinamento tardiurno de Hadoop, Treinamento em grupo de Hadoop, Apache Hadoop guiado por instrutor, Treinamento de Apache Hadoop de fim de semana, Cursos de Apache Hadoop tardiurnos, coaching de Hadoop, Instrutor de Apache Hadoop, Treinador de Apache Hadoop, Cursos de treinamento de Hadoop, Aulas de Hadoop, Apache Hadoop no local do cliente, Cursos privados de Hadoop, Treinamento individual de Hadoop
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