Live Online Training
Instructor-led Hadoop & Spark environment practice.
Retail Sales Big Data Project
Load → aggregate → analyze → produce business insights.
Big Data (Hadoop, Spark)
Big Data Engineering with Hadoop & Spark Training + Placement Support
Learn to process and analyze massive datasets using Hadoop, HDFS, Hive, Spark, and Data Pipelines — build a job-ready Big Data engineering skillset.
From Basics to Advanced Big Data Processing
4,300+ Professionals Trained
Big Data powers modern analytics, AI, product intelligence, financial systems, and large-scale distributed applications. This program trains you to work with Hadoop ecosystem, HDFS, YARN, Hive, Sqoop, Spark RDD & DataFrames, Spark SQL, and real-world ETL pipelines. You will learn to extract, clean, process, analyze, and transform large datasets across distributed computing systems — preparing you for Big Data Engineer, Spark Developer, and ETL Pipeline Engineer roles.
Highly in-demand skill for enterprise analytics & data teams
Hands-on with real datasets & distributed processing workflows
Fully Practical Hadoop & Spark Lab Setup
End-to-End Data Processing Project
50+ Transformation & Analysis Tasks
Lifetime Access to Notes, Data & Recording
What You Will Learn in the Big Data (Hadoop + Spark) Program
A structured hands-on training path to manage, process, transform & analyze large-scale distributed datasets.
Big Data & Distributed Computing Concepts (Foundation)
1 Week
What is Big Data & Why It Is Needed
Types of Data (Structured / Semi-Structured / Unstructured)
Distributed Systems & Scalability Basics
Hadoop Ecosystem & HDFS (Storage Layer)
1.5 Weeks
Hadoop Architecture (NameNode/DataNode)
HDFS Commands & File System Operations
Data Replication & Fault Tolerance
YARN & Resource Management
0.5–1 Week
Job Scheduling & Resource Allocation
MapReduce Execution Workflow
Cluster Job Monitoring
Hive & SQL on Big Data (Data Querying)
1.5 Weeks
Hive Tables (Internal & External)
Partitioning & Bucketing
Writing Queries on Large Datasets
Analytic & Aggregation Reporting
Spark Core & RDD Processing
1.5 Weeks
Spark Architecture (Driver & Executors)
RDD Transformations & Actions
Lazy Evaluation & DAG Optimization
Spark SQL & DataFrames (Modern Approach)
1 Week
DataFrames & Schemas
Spark SQL Queries
Joins, Aggregations & Window Functions
ETL Data Pipeline Project on Hadoop + Spark (Job-Ready Project)
1 Week
Load & Transform Large Datasets
Run Aggregations & Analytics Queries
Optimize Jobs & Generate Final Reports
Learn from our expert authors
Big Data Engineer & Distributed Systems Mentor
10+ Years of Experience in Hadoop, Spark, Data Lakes & Enterprise ETL Systems.
Worked in Banking, Telecom, E-Commerce & Product Data Platforms.
Trained 4,300+ students into Big Data & Cloud Data Engineering roles.
Focus: Practical real-time workflows + performance thinking + interview clarity.
Speak with Mentor @ +91 9344259572
CURRICULUM BREAKDOWN
Storage & Processing Layer
- HDFS
- YARN
- MapReduce
Big Data Query Layer
- Hive
- Spark SQL
- Spark Core
- DataFrames & RDD Workloads
