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Big Data Hadoop Course — Build Data Pipelines with Spark and Hive, Live

Learn the Hadoop and Spark ecosystem through practical data workflows that build confidence for analytics and data engineering teams.

See the full syllabus, fees and what you'll build before you pay a rupee. Live online classes with a personal mentor, small batches, and projects that go straight onto your portfolio.

2.5 Months guided project path
4.8/5 learner feedback
Roadmap and outcome fit explained
Ask on WhatsApp

Classes in English, Hindi & Marathi

See the structure, mentor support and next steps in one clear conversation.

Amruta PatilEshan AloneyGaurav Jadhav
Choose with human context, not a generic catalogue grid. A learning advisor helps you compare your goal, current level, time comfort and project expectations before you decide.
2.5 Months to structured project proof
25 learner groups for feedback
4.8 learner confidence score
Know what to build before you startGet feedback before your portfolio goes publicChoose the learning mode that fits your week
Hadoop & Big Data learning path with live online support across India at SourceKode
Next cohort starts 20 June 2026 · only 25 seats
Small groups of 25 learners so mentors can review work properly.
INR 20,000 INR 32,000 38% OFF
  • Included Applied Projects
  • Included Career Context Included
  • Included Cloud Labs Access
  • Included Continued Learning Support

Free demo class before you pay · EMI options · 7-day money-back guarantee

Roadmap support is available from your first enquiry to live start.

Free roadmap check before you paySyllabus, pricing and live-start clarity in one callPortfolio proof you can explainMentor-reviewed project workLive online across India with optional Pune supportSmall groups for better feedbackFree roadmap check before you paySyllabus, pricing and live-start clarity in one callPortfolio proof you can explainMentor-reviewed project workLive online across India with optional Pune supportSmall groups for better feedback

Outcome-first learning path

Move from interest to useful Hadoop & Big Data proof

SourceKode helps you decide whether this route is worth your time, then gives you a practical path to build, practise and show work with mentor feedback. The goal is not to collect another certificate. The goal is to become easier to trust, interview and hire.

Right fit

Know it suits you before you pay

Talk to a mentor first — we check whether Hadoop & Big Data matches your background, time and goal, and tell you honestly if it doesn't.

Real projects

Build things you can show

Every module ends in a real project for your portfolio — the thing interviewers, clients and recruiters actually ask to see.

Live mentors

Never get stuck alone

Small live batches mean your doubts get answered in class, and your project work gets personal feedback before it goes public.

No surprises

Fees, dates and syllabus upfront

Exact fees with EMI options, the next batch date and the full syllabus — all before you commit a single rupee.

3 Months guided path to visible project proof
4 + big data projects you can discuss
25 learners per group for better feedback
1 clear pricing, roadmap and syllabus plan before payment
Available across India Join Hadoop & Big Data live online from anywhere in India, with optional Pune support if you prefer in-person help. Ask for the syllabus, pricing plan and live-start advice before you decide.

What does the Hadoop & Big Data course cover?

The Hadoop & Big Data path is a 3 Months, mentor-led program covering Hadoop & Big Data, Applied Projects, Career Context Included, Cloud Labs Access — built around 4+ big data projects you can show in interviews.

Who is the Hadoop & Big Data course for?

It suits intermediate learners — students, working professionals and career switchers who want practical proof, not just a certificate. We check fit on a free roadmap call before you pay.

What are the fees and next batch for Hadoop & Big Data?

Fees are INR 20,000 (from INR 32,000) with EMI options and a GST invoice. Live online in small batches of 25 — ask for the next start date and the full syllabus.

Course Overview

Master Big Data processing with the Hadoop ecosystem and handle massive datasets at scale. Learn HDFS, MapReduce, Hive, Pig, and Spark to process petabytes of data for enterprises and tech giants.

Hadoop learning path at SourceKode covers the complete Big Data stack from data storage to processing and analysis. Learn technologies used by Facebook, Yahoo, LinkedIn, and thousands of enterprises for big data analytics.

Why Learn Hadoop?

  • Big Data Era: World generates 2.5 quintillion bytes daily
  • High Demand: Big Data engineers earn ₹7-22 LPA
  • Enterprise Need: All large companies need big data processing
  • Future-Proof: Data volumes growing exponentially
  • Scalability: Process terabytes to petabytes of data
  • Open Source: Apache Hadoop - free and widely adopted

What You’ll Learn

  • HDFS: Distributed file system for big data storage
  • MapReduce: Distributed data processing framework
  • Hive: SQL queries on big data
  • Pig: Data flow scripting language
  • Spark: In-memory fast data processing
  • HBase: NoSQL database on Hadoop
  • Sqoop: Data transfer between Hadoop and RDBMS

Course Syllabus

Module 1: Big Data Fundamentals

  • What is Big Data (3Vs: Volume, Velocity, Variety)
  • Traditional vs Big Data approaches
  • Hadoop ecosystem overview
  • Linux basics for Hadoop

Module 2: HDFS

  • HDFS architecture
  • NameNode and DataNode
  • Block storage and replication
  • HDFS commands
  • File operations

Module 3: MapReduce

  • MapReduce programming model
  • Mappers and Reducers
  • Combiner and Partitioner
  • Java MapReduce programs
  • WordCount and other examples

Module 4: Hive

  • Hive architecture
  • HiveQL syntax
  • Creating tables and partitions
  • Joins and aggregations
  • User-defined functions (UDF)

Module 5: Pig

  • Pig Latin scripting
  • Data flow operations
  • Pig vs Hive
  • ETL with Pig

Module 6: Apache Spark

  • Spark architecture
  • RDDs (Resilient Distributed Datasets)
  • Transformations and actions
  • Spark SQL
  • DataFrame API
  • Spark vs MapReduce

Module 7: HBase & NoSQL

  • HBase architecture
  • CRUD operations
  • Column-family design

Module 8: Data Ingestion

  • Sqoop for data import/export
  • Flume for log data
  • Kafka basics

Projects

  1. Log Analysis with Hadoop
  2. E-commerce Data Analysis with Hive
  3. Real-time Processing with Spark
  4. Data Pipeline with full ecosystem

Career Opportunities

  • Big Data Engineer - Average: ₹7-18 LPA
  • Hadoop Developer - Average: ₹6-15 LPA
  • Data Engineer - Average: ₹8-20 LPA
  • Spark Developer - Average: ₹9-22 LPA

Companies

  • Tech Giants: Facebook, Yahoo, LinkedIn, Twitter
  • E-commerce: Amazon, Flipkart, eBay
  • Finance: Banks, financial services
  • Telecom: Airtel, Jio, Vodafone
  • Analytics: All analytics companies

Big Data Engineer Salary in India (2026)

ExperienceTypical RoleSalary Range (₹ / year)
Fresher (0–1 yr, with projects)Junior Data Engineer₹4,00,000 – ₹8,00,000
2–4 yearsBig Data / Spark Engineer₹10,00,000 – ₹22,00,000
5–8 yearsSenior Data Engineer₹25,00,000 – ₹45,00,000
8+ yearsData Architect₹45,00,000 – ₹70,00,000+

Indicative ranges for India in 2026. Data engineering is among the best-paid tech tracks because every analytics and AI initiative depends on reliable data pipelines. Hadoop/Spark + cloud is the most employable combination.

Is Big Data / Hadoop Worth Learning in 2026?

Yes — data engineering underpins analytics and AI:

  • AI needs data pipelines: every ML/AI project depends on engineered data.
  • High pay: data engineering sits near the top of the salary table.
  • Enterprise demand: banking, telecom and analytics firms hire steadily.
  • Strong pairing: combine with Data Science, Python and AWS Cloud.

Meet your mentors

Real people teach this course — and review your work

Karthik Kumar Senior Software Architect

Teaches data pipelines, cloud deployment and system design.

Priya Sharma Senior Tech Career Counsellor

Maps your portfolio to analyst, scientist and engineer roles.

  • Language English, Hindi, Marathi
  • Duration 3 Months
  • Lectures 60+ Hours
  • Projects 4+ Big Data Projects
  • Skill level Intermediate
  • Certification Yes
  • Max learners 25

Plan your next step

Get pricing, start dates, project roadmap and mentor support explained before you commit.

Small groups for proper mentor feedback
Get pricing and roadmap Call SourceKode: +91 77688 68948
  • Project work reviewed before you showcase it
  • Career, creator or business use case mapped to your goal
  • Flexible start timing with pricing clarity

Mentor-led Small groups EMI support

Get fees & the next batch date

Share four quick details and we will call you with fees, the next Saturday batch date and a roadmap. No spam.

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Outcome Stories

O

"SourceKode's Hadoop training covered the entire ecosystem: HDFS, MapReduce, Hive, Spark. The hands-on cluster setup was invaluable."

Omkar Gaikwad

Big Data Engineer at Cognizant
D

"I switched from manual testing to big data engineering after this course. The real-world data pipeline projects made my transition smooth."

Deepa Nair

Data Engineer at Zensar Technologies
2,276
Learners Trained
50+
Cities Across India
4.8/5
Google Rating
100%
Career Support

Hiring partners include TCS, Infosys, Wipro, Accenture, Capgemini, Zensar & 200+ more

Frequently Asked Questions

Is Hadoop still relevant with cloud computing?
Yes! Many enterprises run Hadoop on cloud (AWS EMR, Azure HDInsight, Google Dataproc). Hadoop skills are valuable for big data processing whether on-premise or cloud. Spark (part of Hadoop ecosystem) is growing stronger.
Do I need Java knowledge for Hadoop?
Basic Java helps for MapReduce programming, but not essential for all roles. Hive uses SQL-like queries, Pig uses scripting. We teach necessary Java basics. Many big data roles focus on Hive/Spark SQL without deep Java.
Hadoop vs Spark - which should I learn?
Learn both! Hadoop (HDFS + MapReduce) for storage and live start processing. Spark for faster in-memory processing. Our course covers the complete ecosystem including both. Spark skills are increasingly valuable.
Are Big Data jobs declining?
Traditional Hadoop Admin jobs are declining, but Big Data Engineering and Spark development are growing. Companies move to cloud but still need big data processing skills. Focus on Spark, cloud integration, and data engineering.
What companies use Hadoop in India?
Telecom (Airtel, Jio), E-commerce (Flipkart, Amazon), Banking (HDFC, ICICI), Analytics firms (Mu Sigma, Fractal), and IT services. Big data skills open doors to data engineering roles across industries.
Big Data Engineer vs Data Scientist - which is better?
Different roles! Big Data Engineers build data pipelines and infrastructure (₹7-20 LPA). Data Scientists do analysis and ML (₹8-30 LPA). Both are in demand. Engineers need less math, Scientists need more statistics/ML.
Is Big Data and Hadoop still worth learning in 2026?
Yes. The ecosystem has shifted toward Spark and cloud data platforms, but the core skills — distributed storage, processing and building data pipelines — are in steady demand across banking, telecom and large analytics teams. Most roles now blend Hadoop/Spark with cloud (AWS/Azure), which this course prepares you for.
What is the Big Data Engineer salary in India in 2026?
Freshers typically start at ₹4–8 LPA, engineers with 2–4 years of experience earn ₹10–22 LPA, and senior big-data or data engineers reach ₹25–45 LPA. Pairing Hadoop/Spark with cloud and Python lifts pay the fastest.
Learning path check

Want to know if Hadoop & Big Data is the right next step?

We will help you compare syllabus depth, project proof, pricing and live-start fit so you can decide with confidence.

Small groups for feedback Live online across India; optional Pune support EMI and roadmap support