Programele de pregătire locală, instruite de instructori Apache Hadoop demonstrează prin practica interactivă practica principalele componente ale ecosistemului Hadoop și modul în care aceste tehnologii pot fi utilizate pentru a rezolva probleme la scară largă. Instruirea Hadoop este disponibilă ca "formare live la fața locului" sau "formare live la distanță". Training-ul live la fața locului poate fi efectuat la fața locului la sediul clientului România sau în centrele de formare corporativa NobleProg din România România . Instruirea live la distanță este realizată printr-un desktop interactiv, la distanță. NobleProg - Furnizorul dvs. de formare locală
Machine Translated
Mărturii
Faptul că toate datele și software-ul erau gata de utilizare pe un VM deja pregătit, oferit de antrenor pe discuri externe.
vyzVoice
Curs: Hadoop for Developers and Administrators
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Mi-a plăcut mai mult antrenorul oferind Exemple reale live.
Simon Hahn
Curs: Administrator Training for Apache Hadoop
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M-am bucurat cu adevărat de marile competențe ale formatorului.
Grzegorz Gorski
Curs: Administrator Training for Apache Hadoop
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Mi-a plăcut cu adevărat multe sesiuni hands-on.
Jacek Pieczątka
Curs: Administrator Training for Apache Hadoop
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Îi plăcea foarte mult modul interactiv de învățare.
Luigi Loiacono
Curs: Data Analysis with Hive/HiveQL
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A fost o pregătire foarte practică, mi-a plăcut exercițiile practice.
Proximus
Curs: Data Analysis with Hive/HiveQL
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Am beneficiat de o privire de ansamblu bună, un bun echilibru între teorie și exerciții.
Proximus
Curs: Data Analysis with Hive/HiveQL
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Mi-a plăcut interacțiunea dinamică și "mâinile" pe subiect, mulțumită mașinii virtuale, foarte stimulatoare !.
Philippe Job
Curs: Data Analysis with Hive/HiveQL
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Am beneficiat de competența și de cunoștințele formatorului.
Jonathan Puvilland
Curs: Data Analysis with Hive/HiveQL
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A fost foarte practic, am petrecut jumătate din timp făcând lucruri în Clouded / Hardtop, executând comenzi diferite, verificând sistemul și așa mai departe. Materialele suplimentare (cărți, site-uri web etc.) au fost cu adevărat apreciate, va trebui să continuăm să învățăm. Instalațiile erau destul de distractive și, foarte util, setarea clusterului de la zero a fost foarte bună.
Ericsson
Curs: Administrator Training for Apache Hadoop
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Antrenorul a fost fantastic și chiar și-a cunoscut lucrurile. Am învățat multe despre software-ul pe care nu l-am cunoscut anterior și care va ajuta foarte mult la slujba mea !.
Steve McPhail - Alberta Health Services - Information Technology
Curs: Data Analysis with Hive/HiveQL
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Principiile de nivel înalt despre stup, HDFS ...
Geert Suys - Proximus Group
Curs: Data Analysis with Hive/HiveQL
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Handson. Practica mixului / theroy
Proximus Group
Curs: Data Analysis with Hive/HiveQL
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Fulvio a reușit să înțeleagă cazul afacerilor companiilor noastre și a putut să coreleze cu materialul cursului, aproape instantaneu.
Samuel Peeters - Proximus Group
Curs: Data Analysis with Hive/HiveQL
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Multe exerciții practice.
Ericsson
Curs: Administrator Training for Apache Hadoop
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Instrument de management Ambari. Posibilitatea de a discuta despre experiențele practice Hadoop din alte cazuri de afaceri decât telecom.
Ericsson
Curs: Administrator Training for Apache Hadoop
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Am crezut că a făcut o treabă bună de croitorie experiența pentru audiență. Această clasă este cea mai mare parte proiectat pentru a acoperi analiza datelor cu HIVE, dar eu și colegul meu fac administrația stup cu nici o date reale de analiză responsabilități.
ian reif - Franchise Tax Board
Curs: Data Analysis with Hive/HiveQL
Machine Translated
VM mi-a placut foarte mult Profesorul a fost foarte informat cu privire la subiect, precum și alte subiecte, el a fost foarte frumos și prietenos Mi-a plăcut facilitatea din Dubai.
Safar Alqahtani - Elm Information Security
Curs: Big Data Analytics in Health
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Temele de instruire și implicarea formatorului
Izba Administracji Skarbowej w Lublinie
Curs: Apache NiFi for Administrators
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Comunicarea cu oamenii care participă la formare.
Andrzej Szewczuk - Izba Administracji Skarbowej w Lublinie
Curs: Apache NiFi for Administrators
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lucruri practice de a face, de asemenea teoria a fost servită de Ajay bine
Dominik Mazur - Capgemini Polska Sp. z o.o.
Curs: Hadoop Administration on MapR
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Exerciții
Capgemini Polska Sp. z o.o.
Curs: Hadoop Administration on MapR
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utilitatea exercițiilor
Algomine sp.z.o.o sp.k.
Curs: Apache NiFi for Administrators
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Am găsit formarea bună, foarte informativă ... dar ar fi putut fi răspândită în 4 sau 5 zile, permițându-ne să vedem mai multe detalii despre diferite aspecte.
Veterans Affairs Canada
Curs: Hadoop Administration
Machine Translated
Mi-a plăcut foarte mult antrenamentul. Anton are multe cunoștințe și a pus teoria necesară într-un mod foarte accesibil. Este minunat că antrenamentul a fost o mulțime de exerciții interesante, așa că am fost în contact cu tehnologia pe care o știm de la bun început.
Szymon Dybczak - Algomine sp.z.o.o sp.k.
Curs: Apache NiFi for Administrators
Machine Translated
Am constatat că acest curs a oferit o imagine de ansamblu excelentă și am atins rapid anumite zone pe care nici măcar nu le aveam în vedere.
Veterans Affairs Canada
Curs: Hadoop Administration
Machine Translated
Mi-au plăcut cu adevărat exercițiile de lucru cu cluster pentru a vedea performanța nodurilor în cadrul clusterului și funcționalitatea extinsă.
CACI Ltd
Curs: Apache NiFi for Developers
Machine Translated
Ajay a fost un consultant foarte experimentat și a putut să răspundă la toate întrebările noastre și chiar a făcut sugestii cu privire la cele mai bune practici pentru proiectul în care suntem angajați în prezent.
CACI Ltd
Curs: Apache NiFi for Administrators
Machine Translated
Partea practică. Sarcinile au fost bine alese pentru aspectele discutate.
Rossmann SDP
Curs: HBase for Developers
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Hadoop Subcategories
Hadoop Course Outlines
Numele cursului
Durata
Sinoptic
Numele cursului
Durata
Sinoptic
21 hours
Sinoptic
The course is dedicated to IT specialists that are looking for a solution to store and process large data sets in distributed system environment
Course goal:
Getting knowledge regarding Hadoop cluster administration
Course goal:
Getting knowledge regarding Hadoop cluster administration
35 hours
Sinoptic
Audience:
The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment
Goal:
Deep knowledge on Hadoop cluster administration.
The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment
Goal:
Deep knowledge on Hadoop cluster administration.
28 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
This course introduces HBase – a NoSQL store on top of Hadoop. The course is intended for developers who will be using HBase to develop applications, and administrators who will manage HBase clusters.
We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course is very hands-on with lots of lab exercises.
Duration : 3 days
Audience : Developers & Administrators
We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course is very hands-on with lots of lab exercises.
Duration : 3 days
Audience : Developers & Administrators
21 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
Hadoop is the most popular Big Data processing framework.
14 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
In this instructor-led training in România, participants will learn the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems. By learning these foundations, participants will 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
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
14 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
In this instructor-led, live training in România (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 hours
Sinoptic
In this instructor-led, live training in România, 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 hours
Sinoptic
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 hours
Sinoptic
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 hours
Sinoptic
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.
35 hours
Sinoptic
This instructor-led, live training in România (online or onsite) is aimed at system administrators who wish to learn how to set up, deploy and manage Hadoop clusters within their organization.
By the end of this training, participants will be able to:
- Install and configure Apache Hadoop.
- Understand the four major components in the Hadoop ecoystem: HDFS, MapReduce, YARN, and Hadoop Common.
- Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.
- Set up HDFS to operate as storage engine for on-premise Spark deployments.
- Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
- Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.
By the end of this training, participants will be able to:
- Install and configure Apache Hadoop.
- Understand the four major components in the Hadoop ecoystem: HDFS, MapReduce, YARN, and Hadoop Common.
- Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.
- Set up HDFS to operate as storage engine for on-premise Spark deployments.
- Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
- Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.
7 hours
Sinoptic
This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive
21 hours
Sinoptic
Cloudera Impala is an open source massively parallel processing (MPP) SQL query engine for Apache Hadoop clusters.
Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache Hbase without requiring data movement or transformation.
Audience
This course is aimed at analysts and data scientists performing analysis on data stored in Hadoop via Business Intelligence or SQL tools.
After this course delegates will be able to
- Extract meaningful information from Hadoop clusters with Impala.
- Write specific programs to facilitate Business Intelligence in Impala SQL Dialect.
- Troubleshoot Impala.
Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache Hbase without requiring data movement or transformation.
Audience
This course is aimed at analysts and data scientists performing analysis on data stored in Hadoop via Business Intelligence or SQL tools.
After this course delegates will be able to
- Extract meaningful information from Hadoop clusters with Impala.
- Write specific programs to facilitate Business Intelligence in Impala SQL Dialect.
- Troubleshoot Impala.
21 hours
Sinoptic
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 hours
Sinoptic
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.
Upcoming Apache Hadoop Courses
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