Big Data and Hadoop course from DataFlair is a great blend of in-depth theoretical knowledge and strong practical skills via implementation of real life projects to enable you head start and grab top Big Data jobs in the industry.
40+ Hrs of instructor-led sessions
100+ Hrs of practicals & assignments
5 Real-time big data projects
Lifetime access to course with support
Job oriented course with job assistance
★★★★★Reviews | 14329 Learners
Offers: Get Apache Storm & Java courses free with instructor-led Course
About Big Data Hadoop Course
Big Data Hadoop online training course is designed by certified experts as per industry standards and need to make you quite apt to grab top jobs and start your career as Big Data developer as thousands of other professionals have already done by joining this Hadoop course.
Become Hadoop Big Data expert by learning core Big Data technology and gain hands on knowledge of Hadoop along with its eco-system components like HDFS, Map-Reduce, Hive, Pig, HBase, Sqoop, Flume, Yarn and Apache Spark through this Hadoop course. For extensive hands-on, individual topics are explained using multiple workshops. The online Big data and Hadoop certification course also covers real life use-cases, multiple POCs, live Hadoop project and create foundation of Apache Spark for distributed data processing.
Objectives of Big Data Hadoop online Training
- Bring shift in your career as Big data has brought in IT world
- Grasp the concepts of HDFS and Map Reduce
- Become adept in latest version of Apache Hadoop
- Develop complex Game-Changing MapReduce Application
- Data analysis using Pig and Hive
- Play with NoSQL database – Apache HBase
- Acquire understanding of ZooKeeper service
- Data loading using Apache Sqoop and Flume
- Enforce best practices for Hadoop development and deployment
- Master handling of large data-set using Hadoop ecosystem
- Work on live project on Big Data analytics to get hands-on Experience
- Comprehend other Big Data technologies like Apache Spark
Upcoming Batch Schedule
|17 Dec – 11 Jan||09.00 PM – 11.00 PM IST
7.30 AM – 09.30 AM PST
|22 Dec – 27 Jan||8.00 PM – 11.00 PM IST
09.30 AM – 12.30 PM EST
|14 Jan – 8 Feb||09.00 PM – 11.00 PM IST
7.30 AM – 09.30 AM PST
|12 Jan – 17 Feb||10.00 AM – 01.00 PM IST
08.30 PM – 11.30 PM PST
|9 Feb – 17 Mar||8.00 PM – 11.00 PM IST
09.30 AM – 12.30 PM EST
Why you should learn Big Data and Hadoop
Average salary of Big Data Hadoop Developers is $135k -Indeed
There will be a shortage of 1.5M Big Data experts by 2018 -McKinsey
What will you get from this Big Data Course
40+ hrs of live online instructor-led Hadoop sessions by industry veterans
Industry renowned Big Data certification to boost your resume
100+ hrs of Hadoop practicals, workshops, labs, quiz and assignments
Personalized one to one career discussion directly with the trainer
Real life Big Data case studies and live hadoop project to solve real problem
Mock interview & resume preparation to excel in Hadoop interviews
Lifetime access to Hadoop course, recorded sessions and study materials
Premium job assistance and support to step ahead in Big Data career
Discussion forum for resolving your queries and interacting with fellow batch-mates
Auto Upgradation of the course and study material in the LMS to latest versions
Who should go for this online Hadoop Course
YOU, yes you should go for this Big Data and Hadoop online course if you want to take a leap in your career as Hadoop developer. This course will be useful for:
- Software developers, Project Managers and architects
- BI, ETL and Data Warehousing Professionals
- Mainframe and testing Professionals
- Business analysts and Analytics professionals
- DBAs and DB professionals
- Professionals willing to learn Data Science techniques
- Any graduate focusing to build career in Big Data
Pre-requisites to attend Hadoop online course
Nothing can stop you from starting your career in Big Data. As such no prior knowledge of any technology is required to learn Big Data and Hadoop. In case you feel any need to revise your Java concepts, Java course will be provided in your LMS as complimentary with our Big Data and Hadoop tutorial course.
Big Data & Hadoop Course Curriculum
- What is Big Data
- Necessity of Big Data in the industry
- Paradigm Shift - why industry is shifting to Big Data tools
- Different dimensions of Big Data
- Data explosion in industry
- Various implementations of Big Data
- Different technologies to handle Big Data
- Traditional systems and associated problems
- Future of Big Data in IT industry
- Why Hadoop is at the heart of every Big Data solution
- Introduction to Hadoop framework
- Hadoop architecture and design principles
- Ingredients of Hadoop
- Hadoop characteristics and data-flow
- Components of Hadoop ecosystem
- Hadoop Flavors – Apache, Cloudera, Hortonworks etc.
Setup and Installation of Single-Node Hadoop Cluster
- Setup of Hadoop environment and pre-requisites
- Installation and configuration of Hadoop
- Work with Hadoop in pseudo-distributed mode
- Troubleshooting the encountered problems
Setup and Installation of Hadoop multi-node Cluster
- Setup Hadoop environment on the cloud (Amazon cloud)
- Install Hadoop pre-requisites on all the nodes
- Configuration of Masters and Slaves on Cluster
- Play with Hadoop in distributed mode
- What is HDFS - Hadoop Distributed File System
- HDFS daemons and its Architecture
- HDFS data flow and its storage mechanism
- Hadoop HDFS Characteristics and design principles
- Responsibility of HDFS Master – NameNode
- Storage mechanism of Hadoop meta-data
- Work of HDFS Slaves – DataNodes
- Data Blocks and distributed storage
- Replication of blocks, reliability and high availability
- Rack-awareness, Scalability and other features
- Different HDFS APIs and terminologies
- Commissioning of nodes and addition of more nodes
- Expand the cluster in real-time
- Hadoop HDFS web UI and HDFS explorer
- HDFS Best Practices and hardware discussion
- What is MapReduce - Processing layer of Hadoop
- Need of distributed processing framework
- Issues before MapReduce and its evolution
- List processing Concepts
- Components of MapReduce – Mapper and Reducer
- MapReduce terminologies key, values, lists etc.
- Hadoop MapReduce execution flow
- Mapping data and reducing them based on keys
- MapReduce word-count example to understand the flow
- Execution of Map and Reduce together
- Control the flow of mappers and reducers
- Optimization of MapReduce Jobs
- Fault-tolerance and data locality
- Work with map-only jobs
- Introduction to Combiners in MapReduce
- How MR jobs can be optimized using Combiners
- Anatomy of MapReduce
- Hadoop MapReduce data-types
- Develop custom data-types using Writable & WritableComparable
- What is InputFormats in MapReduce
- How InputSplit is unit of work
- How Partitioners partition the data
- Customization of RecordReader
- Move data from mapper to reducer – shuffling & sorting
- Distributed Cache and job chaining
- Different Hadoop case-studies to customize each component
- Job scheduling in MapReduce
- Need of adhoc SQL based solution – Apache Hive
- Introduction and architecture of Hadoop Hive
- Play with Hive shell and run HQL queries
- Hive DDL and DML operations
- Hive execution flow
- Schema Design and other Hive operations
- Schema on read vs Schema on write in Hive
- Meta-store management and need of RDBMS
- Limitation of default meta-store
- Using serde to handle different types of data
- Optimization of performance using partitioning
- Different Hive applications and use cases
- Need of high level query language - Apache Pig
- How pig complements Hadoop with scripting language
- What is Pig
- Pig execution flow
- Different Pig operations like filter and join
- Compilation of pig code into MapReduce
- Comparison between Pig vs MapReduce
- NoSQL Databases and their need in the industry
- Introduction to Apache HBase
- Internals of HBase architecture
- HBase master and slave model
- Column-oriented, 3 dimensional, schema-less datastore
- Data modeling in Hadoop HBase
- Store multiple versions of data
- Data high-availability and reliability
- Comparison between HBase vs HDFS
- Comparison between HBase vs RDBMS
- Data access mechanism
- Work with HBase using shell
- Need of Apache Sqoop
- Introduction and working of Sqoop
- Import data from RDBMS to HDFS
- Export data to RDBMS from HDFS
- Conversion of data import / export query into MapReduce job
- What is Apache Flume
- Flume architecture and aggregation flow
- Understand Flume components like data Source and Sink
- Flume channels to buffer the events
- Reliable & scalable data collection tool
- Aggregate streams using Fan-in
- Separate streams using Fan-out
- Internals of agent architecture
- Production architecture of Flume
- Collect data from different sources to Hadoop HDFS
- Multi-tier flume flow for collection of volumes of data using avro
- Need and evolution of Yarn
- What is Yarn and its eco-system
- Yarn daemon architecture
- Master of Yarn – Resource Manager
- Slave of Yarn – Node Manager
- Resource request from Application master
- Dynamic slots called containers
- Application execution flow
- MapReduce version 2 application over Yarn
- Hadoop Federation and Namenode HA
- Introduction to Apache Spark
- Comparison between Hadoop MapReduce vs Apache Spark
- Spark key Features
- RDD and various RDD operations
- RDD Abstraction, interface and creation of RDDs
- Fault Tolerance in Spark
- Spark Programming model
- Data Flow in Spark
- Spark Ecosystem, its Hadoop compatibility & integration
- Installation & Configuration of Spark
- Process Big Data using Spark
Big Data & Hadoop Projects
Weblogs are web server logs, where web servers like apache records all the events along with remote-IP, time-stamp, requested-resource, referral, user-agent, etc. The objective is to analyze the weblogs and generate insights like user navigation pattern, top referral sites, highest/lowest traffic-time, etc.
Sentiment analysis is the analysis of people’s opinions, sentiments, evaluations, appraisals, attitudes and emotions in relation to entities like individuals, products, events, services, organizations and topics by classifying the expressions as negative / positive opinions
Analyze the US crime data and find most crime-prone area along with crime time and its type. The objective is to analyze the crime data and generate crime patterns like time, district, crime-type, latitude, longitude, etc. So that additional security measures can be taken in crime prone area.
IVR Data Analysis
Analyze IVR (Interactive Voice Response) data and generate various insights. The IVR call records are analyzed to optimize to IVR system so that maximum calls are completed at IVR and there will be minimum need for Call-center.
Titanic Data Analysis
Titanic was one of the biggest disasters in the history of mankind, which happened due to natural events and human mistakes. The objective is to analyze Titanic data sets and generate various insights related to age, gender, survived, class, emabrked, etc.
Amazon Data Analysis
Amazon data-sets contains user-reviews of different products, services, star-ratings, etc. The objective of the project is to analyze the users’ review data, companies can analyze the sentiments of the users regarding their products and use it for betterment of the same.
Extensive hands-on practicals
No of Projects
Discussion Forum Access
Complementary Job Assistance
Resume & Interview Preparation
Interaction in Live class
Personalized career guidance
Yes, in recordings & in LMS
Through discussion forum
Yes, post course completion
Java, with lifetime access
Live Online with Trainer
Yes, live with instructor & in LMS
Yes, with support
In regular sessions
Yes, post course completion
Java & Storm, with lifetime access
100% interactive classes
Yes, from instructor
On completion of Big Data Hadoop training course, DataFlair’s job grooming program will help you in resume building and interview preparation. Mock interviews and resume referrals will make you job ready to excel in the interviews.
Build a favourable impression with the resume that stands out.
Get connected with top employers to boost your career prospects.
Make yourself job ready with multiple in-depth mock interviews.
Get ready to work from day one with multiple projects & best practices
Companies you could land up with
Corporate Clients /
Offers made to
Hours of classes
Hadoop Training FAQs
If you miss any session, you need not worry as recordings will be uploaded in LMS immediately as the session gets over. You can go through it and get your queries cleared from the instructor during next session. You can also ask him to explain the concepts that you did not understand and were covered in session you missed. Alternatively you can attend the missed session in any other batch running parallely.
Instructor will help you in setting virtual machine on your own system at which you can do practicals anytime from anywhere. Manual to set virtual machine will be available in your LMS in case you want to go through the steps again. Virtual machine can be set on MAC or Windows machine also.
All the sessions will be recorded and you will have lifetime access to the recordings along with the complete Hadoop study material, POCs, Hadoop project etc.
To attend online Hadoop training, you just need a laptop or PC with a good internet connection of around 1 MBPS (But the lesser speed of 512 KBPS will also work). The broadband connection is recommended but you can connect through data card as well.
If you have any doubt during any session, you can get it cleared from the instructor immediately. If you get queries after the session, you can get it cleared from the instructor in the next session as before starting any session, instructor spends around 15 minutes in doubt clearing. Post training, you can post your query over discussion forum and our support team will assist you. Still if you are not comfortable, you can drop mail to instructor or directly interact with him.
Recommended is minimum of i3 processor, 20 GB disk and 4 GB RAM in order to learn Hadoop although students have learnt Hadoop on 2 GB RAM as well.
Our training includes multiple workshops, POCs, project etc. that will prepare you to the level that you can start working from day 1 wherever you go. You will be assisted in resume preparation. The mock interview will help you in getting ready to face interviews. We will also guide you with the job openings matching to your resume. All this will help you in getting your dream Big Data job in the industry.
You will be skilled with the practical and theoretical knowledge that industry is looking for and will become certified Hadoop professional who is ready to take Big Data Projects in top organizations.
DataFlair has blend of students from across the globe. Apart from India, we provide Hadoop training in US, UK, Singapore, Canada, UAE, France, Brazil, Ireland, Indonesia, Japan, Sri Lanka, etc to cover the complete globe.
Both voice and chat will be enabled during the Big Data Hadoop training sessions. You can talk with the instructor or can also interact via chatting.
This is completely online training with a batch size of 8-10 students only. You will be able to interact with trainer through voice or chat and individual attention will be provided to all. The trainer ensures that every student is clear of all the concepts taught before proceeding ahead. So there will be complete environment of classroom learning.
Yes, you will be provided DataFlair Certification. At the end of this course, you will work on a real time Project. Once you are successfully through the project, you will be awarded a certificate.
You can feel free to contact us by placing a CALL at +91 8451097879 OR dropping your queries on our email at firstname.lastname@example.org
Big data is the latest and the most demanding technology with continuously increasing demand in the Indian market and abroad. Hadoop professionals are among the highest paid IT professionals today with salary $135k (source: indeed job portal). You can check our blog related to Why should I learn Big Data?
You will be doing real-time Hadoop projects in different domains like retail, banking, and finance, etc. using different technologies like Hadoop HDFS, MapReduce, Apache Pig, Apache Hive, Apache HBase, Apache Oozie, Apache Flume and Apache Sqoop.
The Hadoop course from DataFlair is 100% job oriented that will prepare you completely for interview and Big Data job perspective. Post Big Data course completion, we will provide you assistance in resume preparation and tips to clear Hadoop interviews. We will also let you know for Hadoop jobs across the globe matching your resume.
Yes, you can attend the Hadoop demo class recording on our Big data Hadoop course page itself to understand the quality and level of Big Data training we provide and that creates the difference between DataFlair and other Hadoop online training providers.
Hadoop is one of the hottest career options available today for all the software engineers to boost their professional career. In the US itself there are approximately 12,000 jobs currently for Hadoop developers and demand for Hadoop developers are increasing day by day rapidly far more than the availability.
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Hadoop Tutorial – A Comprehensive Guide
This Hadoop tutorial provides thorough introduction of Hadoop. The tutorial covers what is Hadoop, what is the need of Hadoop, why hadoop is most popular, Hadoop Architecture, data flow, Hadoop daemons, different flavours, introduction of Hadoop components like hdfs, MapReduce, Yarn, etc.