Online Hadoop Training in Kenya

This instructor-led, live training in Kenya (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. Over the course of three (or optionally four) days, participants will explore the business advantages and practical applications of Hadoop and its ecosystem. The curriculum covers cluster deployment planning, scaling strategies, as well as installation, maintenance, monitoring, troubleshooting, and optimization techniques. Attendees will engage in hands-on practice with bulk data loading, become acquainted with various Hadoop distributions, and learn to install and manage ecosystem tools. The course 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

Target Audience

Hadoop system administrators

Course Format

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

Informatica with Big Data (BDM) is a specialized course aimed at empowering data professionals to develop, manage, and analyze large datasets by leveraging the latest technologies and architectures in the Big Data landscape. The curriculum covers the entire lifecycle, including data ingestion, integration, cleansing, curation, analytics, and the exposure and consumption of big data services.
During this course, learners will explore solutions that process large datasets using Big Data technologies and architectures such as Apache Hive, Apache Hadoop, and Apache Spark. Practical experience will be provided with Informatica tools like Bloombox, Big Data Management, and iData Fabric to deepen understanding of big data technologies including Map Reduce and Hadoop. Upon completion, learners will be equipped to create end-to-end data solutions using Informatica and its associated Big Data tools.

Apache NiFi is an open-source platform designed for flow-based data integration and event processing. It facilitates the automated, real-time routing, transformation, and mediation of data between diverse systems, featuring a web-based interface and granular control capabilities.

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

Upon completing this training, participants will be equipped to:

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows originating from various sources and destined for different sinks.
• Implement logic for flow automation, routing, and data transformation.
• Optimize performance, monitor operational metrics, and resolve technical issues.

Course Format

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

Course Customization Options

• To request tailored training for this course, please get in touch with us to arrange the details.

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