Big Data, Hadoop and its Architecture

The objective of this program is to provide participants with a comprehensive understanding of Big Data concepts and the Hadoop ecosystem. The course focuses on storing, processing, and analyzing large-scale datasets efficiently using Hadoop and its components. Participants will learn how to design scalable data architectures and implement distributed data processing solutions for real-world business scenarios.

Description

1. Learning Outcomes

Understand the fundamentals of Big Data, its challenges, and use cases across industries.
Learn the Hadoop ecosystem including HDFS, MapReduce, YARN, Hive, Pig, and HBase.
Design and implement distributed storage and processing systems for large datasets.
Apply MapReduce programming for batch processing of Big Data.
Use Hive and Pig for querying and analyzing structured and semi-structured data.
Integrate Hadoop with other Big Data tools for analytics and reporting.
Optimize performance and ensure reliability in distributed data processing environments.

2. Program Highlights & Key Features

Hands-on exercises with HDFS, MapReduce, Hive, and Pig.
Expert-led sessions on Hadoop architecture, cluster setup, and data processing workflows.
Case studies covering finance, healthcare, e-commerce, and telecom Big Data challenges.
Training on data ingestion, storage, and retrieval in distributed systems.
Exposure to emerging trends like Spark integration, cloud-based Hadoop, and real-time Big Data analytics.

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