Talend Big Data Course Overview

Talend Big Data Course Overview

The Talend Big Data course is a comprehensive program designed to equip learners with the skills needed to handle large-scale data using Talend's powerful suite of tools. This course covers a range of topics starting with Talend Data Integration (DI) basics, where learners will understand the context of data integration, work with files and databases, and learn how to process data efficiently. As they progress, they will delve into advanced DI concepts including version control with SVN, remote job execution, and performance tuning.

The course then transitions into Big Data fundamentals, introducing students to the Hadoop ecosystem and how to interact with HDFS and Hive. Learners will apply their knowledge through practical use cases, gaining hands-on experience.

In the modules focusing on Spark Batch and Spark Streaming, participants will learn to leverage the power of Apache Spark for real-time data processing and analytics. They will explore use cases like sentiment analysis, download analysis, and various logs processing scenarios, thereby gaining critical insights into Big Data analytics and streaming.

Upon completion, learners will be well-prepared to harness Talend for Big Data challenges, paving the way for careers as data integration specialists or Big Data engineers.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 40 Hours)
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  • Live Online Training (Duration : 40 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To successfully undertake the Talend Big Data course at Koenig Solutions, students are expected to meet the following minimum prerequisites:


  • Basic understanding of data processing concepts and ETL (Extract, Transform, Load) processes.
  • Familiarity with database concepts, including SQL and data modeling.
  • Knowledge of core programming concepts and experience with a programming language (Java is preferred, as Talend is Java-based).
  • Basic understanding of big data concepts and distributed computing principles.
  • Familiarity with Hadoop ecosystem components such as HDFS and Hive is beneficial but not mandatory.
  • Experience working with any data integration tool is a plus, but not required.
  • Comfortable using a Windows or Linux-based operating system for software installation and basic navigation.

These prerequisites are designed to ensure that learners have the foundational knowledge needed to grasp the course content effectively and to minimize the learning curve associated with the advanced topics covered in the Talend Big Data course.


Target Audience for Talend Big Data

The Talend Big Data course equips participants with the skills to manage and analyze massive datasets using Talend's robust data integration tools.


  • Data Engineers
  • Data Architects
  • Data Analysts
  • ETL Developers
  • Business Intelligence Professionals
  • Hadoop Developers
  • Data Scientists
  • IT Professionals seeking Big Data expertise
  • Software Developers working on data integration projects
  • System Administrators managing Big Data environments
  • Technical Project Managers overseeing data-driven projects
  • DevOps Engineers involved in data processing workflows


Learning Objectives - What you will Learn in this Talend Big Data?

Introduction to Talend Big Data Course Learning Outcomes:

Gain comprehensive skills in Talend for Big Data, including data integration, processing, and real-time data handling using Hadoop, Hive, and Spark frameworks.

Learning Objectives and Outcomes:

  • Understand the fundamentals of data integration within Talend's ecosystem and its application in big data contexts.
  • Acquire the ability to navigate and utilize Talend Data Integration for tasks involving files and databases.
  • Learn to create and manage metadata within the Talend repository to streamline development processes.
  • Develop proficiency in processing and transforming data with Talend components and job designs.
  • Master the use of contexts and variables to build dynamic and flexible data integration jobs.
  • Build standalone executables and Docker images to deploy and manage Talend jobs efficiently.
  • Implement error handling and job controlling mechanisms for robust data integration solutions.
  • Integrate web services into Talend jobs to extend functionality and data connectivity.
  • Explore advanced Talend features like version control with SVN, remote job execution, and resource monitoring.
  • Harness the power of Big Data technologies by connecting to Hadoop clusters, processing data in HDFS, and implementing batch and streaming data processing with Spark.