Online Hadoop Training in Czech Republic

This instructor-led, live training in Czech Republic (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets.

By the end of this training, participants will be able to:

• Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
• Understand the features, core components, and architecture of Spark and Hadoop.
• Learn how to integrate Spark, Hadoop, and Python for big data processing.
• Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
• Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
• Use Apache Mahout to scale machine learning algorithms.

Apache Hadoop is the leading framework for processing Big Data across server clusters. This course, lasting three days (with an optional fourth day), covers the business advantages and practical use cases of Hadoop and its surrounding ecosystem. Attendees will learn how to plan cluster deployment and expansion, as well as how to install, maintain, monitor, troubleshoot, and optimize Hadoop environments. Practical exercises include bulk data loading into clusters, exploring various Hadoop distributions, and installing and managing tools within the Hadoop ecosystem. The curriculum concludes with a discussion on securing clusters using 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

A blend of lectures and hands-on labs, with an approximate balance of 60% lectures and 40% labs.

Apache NiFi is an open-source platform for data integration and event processing that operates on a flow-based model. It facilitates automated, real-time routing, transformation, and mediation of data between disparate systems, supported by a web-based user interface and granular control mechanisms.

This instructor-led live training, available either onsite or remotely, targets intermediate-level administrators and engineers looking to deploy, manage, secure, and optimize NiFi dataflows within production environments.

Upon completion of this course, participants will be equipped to:

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows originating from and terminating at various sources and sinks.
• Implement logic for flow automation, routing, and transformation.
• Optimize performance, monitor system operations, and resolve issues.

Course Format

• Interactive lectures combined with discussions on real-world architectures.
• Practical labs focused on building, deploying, and managing data flows.
• Scenario-based exercises conducted in a live laboratory environment.

Course Customization Options

• For customized training arrangements, please contact us.

In this instructor-led, live training in Czech Republic, 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.