Hadoop training “Introduction to Hadoop Development” is designed for professionals who want to understand and master the fundamentals of Big Data. In today’s context, where data has become a strategic asset, knowing how to process massive volumes of information is essential. This Hadoop course offers a clear, step-by-step, and practical approach to entering the world of Hadoop and its key components.
The program covers the complete Hadoop ecosystem. Participants will discover the role of HDFS and MapReduce, and then learn how to use essential tools such as Pig, Hive, Flume, Sqoop, and YARN. The goal is to provide a practical and operational perspective, helping learners understand how to set up and manage an efficient Hadoop environment.
Module 1: Introduction to Big Data & Hadoop and its Ecosystem, Map Reduce and HDFS
Module 2: Hadoop Installation & setup
Module 3: Deep Dive in Mapreduce
Module 4: Graph Problem Solving
Module 5: Detailed understanding of Pig
Module 6: Detailed understanding of Hive
Module 7: (AVRO) Data Formats
Module 8: Introduction to Hbase architecture
Module 9: Hadoop Cluster Setup and Running Map Reduce Jobs
Module 10: Advance Mapreduce
Hadoop training meets a real need of modern businesses. Big Data has become a strategic pillar for analysis and decision-making. Hadoop enables the storage and processing of massive volumes of data by leveraging the power of distributed computing. This open-source technology is used by major digital players, as well as companies of all sizes seeking to gain value from their data.
The Hadoop ecosystem is not limited to a single framework. It brings together different tools that interact to cover the entire data lifecycle. Understanding this overall architecture is essential for anyone who wants to become skilled in this field.
HDFS is the core component. This distributed file system manages the storage of large amounts of data while ensuring fault tolerance and efficient distribution. The training details the role of each component and illustrates their concrete use. MapReduce complements this foundation by providing a programming model suited to large-scale data processing. Writing MapReduce programs makes it possible to solve complex problems related to data analysis.
Learners also explore Pig and Hive, two tools that simplify data manipulation. Pig offers an accessible scripting language, while Hive enables querying data with a language close to SQL. This dual approach makes Hadoop flexible and suitable for various profiles, whether developers or analysts.
Hadoop training emphasizes real-world use cases. Professionals learn how to process data from multiple sources, transform it, and analyze it to extract value. HBase is introduced as a solution for managing large-scale unstructured data. Avro complements this approach by facilitating data exchange and serialization. These concepts are essential for working on production projects.
Learners also study YARN, Hadoop’s resource manager. This layer ensures better cluster utilization and allows different types of workloads to run. This aspect is crucial to understanding Hadoop’s evolution into a more versatile platform.
A significant part of this training focuses on Spark. Although it is a separate framework, Spark is often used alongside Hadoop. It allows in-memory processing, much faster than MapReduce. Mastering Spark fundamentals, especially RDDs, gives participants a strong advantage in modern Big Data environments.
The use of workflow schedulers such as Oozie is also covered. These tools allow automation and orchestration of tasks within a cluster. This skill is valuable in production environments where reliability and repeatability of processes are critical.
Organizations are increasingly looking for professionals capable of working with Hadoop. Digital transformation is pushing businesses to leverage their data to optimize processes. This Hadoop training prepares participants to face these challenges. By mastering the main ecosystem tools, they become immediately operational on real-world projects.
Another advantage of this program is the variety of roles it serves. Big Data developers learn advanced programming techniques. Analysts discover user-friendly tools to query data. Architects understand how to design scalable and resilient infrastructures. Hadoop’s versatility makes it an essential skill in today’s industry.
What is the difference between Hadoop and Spark?
Spark is an in-memory processing engine, faster for certain types of analysis. Hadoop remains essential for distributed storage through HDFS.
Is Hadoop training suitable for beginners?
Yes, provided you have basic knowledge of programming and databases. The course is structured to help you progress step by step.
Which industries use Hadoop?
It is widely used in finance, healthcare, e-commerce, logistics, and any industry managing large volumes of data.
What are the benefits of HBase?
HBase enables the storage of unstructured data and can handle millions of rows with high performance.
What concrete benefits can I expect after the training?
You will be able to design and execute Big Data workflows, configure a cluster, and leverage the Hadoop ecosystem to meet real business needs.
Monday to Friday
8:30 AM to 6:00 PM
Tel. 058 307 73 00
ITTA
Route des jeunes 35
1227 Carouge, Suisse
Monday to Friday, from 8:30 am to 06:00 pm.
