Course Overview
Hadoop is an Apache development that stores and processes Big Data. Hadoop stores big data in a dispersed manner, and its tools are also used to perform parallel data processing over HDFS (Hadoop Distributed File Systems). Therefore, becoming a professional in Big Data Analytics on Hadoop will be of utmost use to any professional in the field of Big Data. Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop, and best practices for HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume.
This Zoe’s Big Data Hadoop training course will empower you with the in-depth knowledge and level of training professionals require for Big Data Hadoop certifications as well as to perform Big Data management tasks efficiently. This Big Data Analytics on Hadoop Training course is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop and its associated components. Taking your first step towards big data is really challenging, which is why we believe you should become acquainted with the basics before applying Big Data concepts at your workplace.
Why This Course Is Required?
Big Data Analytics on Hadoop has become an essential capability for modern organizations, with Hadoop enabling distributed storage and parallel processing of massive datasets that range from gigabytes to petabytes using cost-effective commodity hardware. The growing exponential increase in data generation requires specialized training in Hadoop ecosystem tools including HDFS, MapReduce, Spark, Hive, and HBase, as 73% of business leaders believe data reduces uncertainty and drives better decisions, yet many struggle to utilize it effectively due to the complexity of managing large-scale data operations.
Organisations have realised the benefits of Big Data Analytics and there is now a huge demand for Big Data and Hadoop professionals. According to Forbes, the Big Data and Hadoop market is expected to reach $99.31B by 2022, growing at a CAGR of 42.1% from 2015. Without comprehensive understanding of Hadoop ecosystem components and big data processing methodologies, organizations struggle to harness the power of their data assets while missing opportunities to optimize operations and enhance customer experiences through data-driven insights.
Research demonstrates that the global Hadoop Big Data Analytics Market was valued at USD 18.5 billion in 2024 and is projected to reach USD 115.6 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 25.8% from 2025 to 2032. The growing exponential increase in data generation requires specialized training in Hadoop ecosystem tools including HDFS, MapReduce, Spark, Hive, and HBase, as 73% of business leaders believe data reduces uncertainty and drives better decisions, yet many struggle to utilize it effectively due to the complexity of managing large-scale data operations and the need for real-time processing capabilities.
Course Objectives
Upon completing this Big Data Hadoop training course successfully, participants will be able to:
- Understand Big Data Hadoop and be proficient with Hadoop, HDFS, Map Reduce, Sqoop, Impala, Apache Pig, Hive and ZooKeeper
- Sit for Big Data Hadoop certification examinations and gain real-world skills required for Big Data roles in IT companies
- Learn the fundamentals of Hadoop and YARN and write programs using them
- Set up pseudo-node and multi-node clusters on Amazon EC2 HDFS, MapReduce, Hive, Pig, Oozie, Sqoop, Flume, ZooKeeper and HBase
- Perform Hadoop administration activities like cluster managing, monitoring, administration and troubleshooting
- Configure ETL tools like Pentaho/Talend to work with MapReduce, Hive, Pig, etc.
- Use Hadoop testing applications using MRUnit and other automation tools and work with Avro data formats
- Carry out real projects using Hadoop and Apache Spark
- Gain in-depth knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) & MapReduce
- Obtain comprehensive knowledge of various tools that fall in Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
- Understand the capability to ingest data in HDFS using Sqoop & Flume, and analyse large datasets stored in the HDFS
- Study projects which are diverse in nature covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce
- Benefit from learning with a Hadoop expert throughout the program to learn industry standards and best practices
Master Big Data excellence and drive data-driven innovation—enroll today to become an expert in Big Data Analytics on Hadoop!
Training Methodology
This is an interactive Big Data Hadoop training program and will consist of the following training approaches:
- Lectures delivered by experienced Big Data and Hadoop professionals
- Seminars & Presentations featuring real-world case studies and industry examples
- Group Discussions fostering collaborative learning and knowledge sharing
- Assignments that reinforce key concepts and practical applications
- Case Studies & Functional Exercises based on actual Hadoop implementations and big data scenarios
This immersive approach fosters collaborative learning through peer interaction, group problem-solving, and knowledge sharing among participants from diverse data analytics backgrounds. The methodology emphasizes practical skill development over theoretical memorization, ensuring participants leave with immediately applicable tools and strategies.
Similar to all our courses, this program also follows the ‘Do-Review-Learn-Apply’ model, creating a structured learning journey that transforms Big Data Hadoop knowledge into operational excellence through systematic practice and implementation.
Who Should Attend?
This Big Data Hadoop training course would be suitable and useful for:
- Senior IT Professionals seeking advanced data processing capabilities
- Testing professionals working with large-scale data testing frameworks
- Mainframe professionals transitioning to modern big data platforms
- Software Architects designing data-intensive applications
- Programming Developers and System Administrators managing distributed systems
- Experienced working professionals and Project Managers overseeing data projects
- Business Intelligence, Data Warehousing and Analytics Professionals
- ETL and Data Warehousing Professionals handling large data volumes
- Data Engineers building scalable data processing pipelines
- Data Analysts & Business Intelligence Professionals requiring advanced analytics capabilities
- Database Administrators and other DB professionals managing big data systems
Organizational Benefits
Companies who send in their employees to participate in this Big Data Hadoop course can benefit in the following ways:
- Give your employees the ability to manage large data volumes using the latest tools
- Provide your workforce with flexible and cost-effective professional development opportunities
- Analyse case studies in this domain and be able to apply successful techniques in your organisation
- Comprehend the principles and practice of Big Data and the context in which this operates
Studies show that organizations implementing comprehensive Big Data Analytics on Hadoop capabilities experience significant operational improvements through enhanced scalability, cost efficiency, fault tolerance, and real-time processing capabilities that enable faster decision-making and improved customer experiences. Hadoop’s distributed architecture allows businesses to scale seamlessly from terabytes to petabytes while leveraging open-source frameworks and commodity hardware to significantly reduce costs compared to proprietary solutions. Training enables organizations to benefit from fault tolerance through data replication across multiple nodes that ensures operational continuity even during hardware failures, making it indispensable for industries dealing with large and complex datasets while enabling real-time analytics capabilities for competitive advantage.
Empower your organization with Big Data Hadoop expertise—enroll your team today and see the transformation in data processing capabilities and analytical insights!
Personal Benefits
Professionals who participate in this Big Data Hadoop training course can benefit in the following ways:
- Be up and running in the most demanding professional skills
- Progress in your career in the Big Data domain
- Benefit from a structured training with the latest curriculum as per current industry requirements and best practices
- Work on numerous practical Big Data projects using different Big Data and Hadoop tools
- Obtain the guidance of a Hadoop expert who is currently working in the industry on real-world Big Data projects and troubleshooting day-to-day challenges while implementing them
Course Outline
MODULE 1: BIG DATA
- Big Data Introduction
- Big Data Concept
- Big Data Benefits
- Data Storage & Analysis
- Querying data
- Grid computing
MODULE 2: BIG DATA HANDS-ON PRACTICE EXERCISE
- Important Note for Exercises
- Query A Public Dataset
- Creating A Dataset
- Querying A Table
- Big Table Instance
- Pub-Sub
MODULE 3: HADOOP
- Hadoop Introduction
- Hadoop Features
- HDFS Architecture
- HDFS Components
- HDFS Client
- HDFS Components
- HDFS Client creating new file
- Rack Description
- HDFS Write Operation
- Selection of Data Nodes & Node Distance
- Serialisation
- HDFS Blocks
- HDFS Caching & Failover
- HDFS Federation
- HDFS High Availability
- Hadoop Archive files
- Hadoop Releases
- Hadoop 2.0 features
MODULE 4: HADOOP EXERCISES
- Creating Cluster
- HUE HDFS File Browser
- HDFS File Browser 2
- Cloud SQL Instance
- Data Store Query
- Google Storage
MODULE 5: MAP REDUCE
- Map Reduce Introduction
- Map Reduce Phases
- Job Tracker
- Anatomy of Map Reduce Program
- Map Reduce Data Types
- Resource Manager Failure
- Submit Job
- HUE Job Designer
- HUE METASTORE MANAGER
MODULE 6: YARN
- YARN
- YARN Processing
MODULE 7: Apache HIVE
- HIVE
- HIVE Basics
- HIVE Architecture
- HIVE – Practice Exercise
- HIVE Query
MODULE 8: Apache PIG
- Apache PIG Introduction
- PIG Modes
- Comparison of PIG, HIVE, Map Reduce
- PIG
MODULE 9: IMPALA
- Data Ingestion
- Query Editors
- Components of Impala Server
- Impala Catalogue Service
- Job Designer
- IMPALA – Practice Exercise
- HUE IMPALA Query
MODULE 10: SQOOP
- Sqoop
- Sqoop Import Export
MODULE 11: UBUNTU
- Installation of Apache Hadoop 2.7.3 on Ubuntu
- Troubleshooting Guidelines
MODULE 12: CONFIGURATION MANAGEMENT
- Cluster Size Specifications
- Master Node Scenario
- Network Topology
- Cluster Setup & Installation
- Configuration Management
- HDFS Data Integrity
- Cycle of Big Data Management
- Big Data in the Cloud
Real World Examples
The impact of Big Data Analytics on Hadoop training is evident in leading implementations:
- Walmart Big Data Analytics Implementation (Global)
Implementation: Walmart harnesses the power of Hadoop to process billions of transactions daily and predict customer demand with precision, analyzing massive volumes of data to ensure optimal inventory levels during peak events like Black Friday.
Results: The implementation enabled Walmart to reduce stockouts and capture millions in additional revenue that would otherwise be lost, while providing real-time inventory updates and personalized product recommendations that ensure smooth operations and enhanced customer satisfaction across thousands of stores globally. - JPMorgan Chase Fraud Detection System (United States)
Implementation: JPMorgan Chase uses Hadoop to process vast volumes of financial data in real-time, enabling proactive risk modeling and advanced fraud detection capabilities that protect both clients and institutional assets through sophisticated analytics and machine learning algorithms.
Results: The Hadoop-powered system detects fraudulent patterns within seconds of transactions occurring, preventing potential losses that could amount to millions while safeguarding the bank’s reputation through enhanced security measures and real-time analytics capabilities that process complex financial datasets at scale. - Cerner Corporation Healthcare Analytics (Global)
Implementation: Cerner Corporation employs Hadoop to integrate and analyze electronic health records and genomic data across healthcare systems, enabling doctors to identify life-saving treatment options for rare diseases through comprehensive data analysis and advanced healthcare analytics platforms.
Results: This Hadoop implementation allows for personalized care delivery that drastically improves patient survival rates by processing complex medical datasets and providing actionable insights that support critical healthcare decision-making in real-time environments, demonstrating the life-saving potential of big data analytics in healthcare.
Be inspired by industry-leading Big Data Hadoop achievements—register now to build the skills your organization needs for data analytics excellence!
