Hadoop Training in Botswana

This instructor-led, live training in Botswana (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 stands as the leading framework for processing Big Data across server clusters. This course, spanning three days with an optional fourth day, equips attendees with a comprehensive understanding of the business advantages and use cases associated with Hadoop and its ecosystem. Participants will learn to plan for cluster deployment and scalability, as well as how to install, maintain, monitor, troubleshoot, and optimise Hadoop systems. Practical skills include performing bulk data loads on clusters, exploring various Hadoop distributions, and installing and managing tools within the Hadoop ecosystem. The course concludes with a focus on securing the cluster using Kerberos.

\u201c...The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organised\u201d
\u2014 Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising

Audience

Hadoop administrators

Format

A blend of lectures and hands-on labs, with an approximate split of 60% lectures and 40% practical laboratory work.

Informatica with Big Data (BDM) is a specialized course aimed at empowering data professionals to develop, manage, and analyze large datasets by leveraging the most current technologies and architectures in the Big Data domain. The course covers the entire lifecycle, from data ingestion, integration, cleansing, and curation, through to data analytics and the exposure and consumption of big data services.
In this course, participants will explore solutions that process large datasets using Big Data technologies and architectures such as Apache Hive, Apache Hadoop, and Apache Spark. The course also provides hands-on experience with Informatica tools like Bloombox, Big Data Management, and iData Fabric, facilitating a deeper understanding of big data technologies like MapReduce and Hadoop. By the conclusion of this course, learners will be equipped to create end-to-end data solutions using Informatica and its associated Big Data offerings.

Apache NiFi is an open-source, flow-based data integration and event-processing platform. It enables automated, real-time data routing, transformation, and system mediation between disparate systems, with a web-based UI and fine-grained control.

This instructor-led, live training (onsite or remote) is aimed at intermediate-level administrators and engineers who wish to deploy, manage, secure, and optimize NiFi dataflows in production environments.

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

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows from varied sources and sinks.
• Implement flow automation, routing, and transformation logic.
• Optimize performance, monitor operations, and troubleshoot issues.

Format of the Course

• Interactive lecture with real-world architecture discussion.
• Hands-on labs: building, deploying, and managing flows.
• Scenario-based exercises in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

In this instructor-led, live training in Botswana, 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.