Big DATA / Hadoop

H2K Infosys is offering comprehensive BIG DATA online training, it is essential for those who wish to make a career in BIG DATA. It is mandatory for candidates who have knowledge on object oriented languages. 

Why H2K Infosys?

  • [Image: Oriented Training]

    100% job oriented training

  • [Image: Live Training]

    Instructor-led face-to-face live training

  • [Image: Latest Technologies]

    Huge course syllabus on latest technologies

  • [Image: Real Time

    Real-time projects to gain hands-on experience

  • [Image: Cloud Test]

    Cloud Test Lab to practice on software tools and projects

  • [Image: Recorded Class]

    Lifetime access to recorded class videos

About Course

  • Is Big Data / Hadoop the big new word on the data streets? Of-course with the nature of IT world and applications evolving data has become the key resource. Every data in the various formats that it comes can be useful for the business. However, this isn’t easy. It comes with challenges like: single machine dependency, excessive amount of processing to fit this data into traditional Databases, performance issues, systems not being immune to failures etc.

    Hadoop framework solves all this and brings in a level of efficiency and transparency into big data. Hadoop uses parallel and distributed processing to store data in multiple clusters across many systems. It is scalable, cheaper, faster, fault tolerant among various other things.

    Hadoop has a huge scope for evolution and the demand for Big Data Hadoop professionals is and will be on a rise. Our Hadoop Big DATA course is just what you need to make you one of them.

  • Hadoop is an open source computing framework that processes large data sets, in a distributed computing environment.  High volume of data can be processed with ease by using parallel computing. Parallel computing is the back bone of Hadoop. Map Reduce development infrastructure, enables us to read, write and perform basic aggregation like operation on the stored data, in batches.

  • Hadoop File System (HDFS) was made to store the huge amount of data. Companies like Yahoo, Facebook, Amazon, NYSE, LinkedIn, eBay, Sears and Walmart generate 30000 gigabytes of data every second. This data is now being used to generate various analytics. So it has to be stored. Traditional databases cannot handle data of this size. The Map Reduce infrastructure helps to run different kinds of diagnostics on them.

    • Teacher led online interactive sessions on Hadoop that covers everything starting from what is not working with the existing systems and how to achieve and maintain a practical implementation of it.
    • A detailed explanation and practical examples with special emphasis on HDFS and MapReduce.
    • Pig, Apache Hive, Apache HBase, and various other Big Data Hadoop related projects are going to be dealt with in an easy to understand manner.
    • Resume, job and interview guidance.
    • Recorded session to make reviewing easy.
    • Hands on assignments for thorough understanding of concepts.
    • Practical real time examples.
    • Study material to make the learning experience complete.
    • Offline support from the faculty via chat or email for clarifications.
  • H2Kinfosys Hadoop Big Data Training Advantages:

    • Instructor Led - Face2Face True Live Online class
    • Core Java Class videos are also free.
    • More interaction with student to faculty and student to student.
    • Practical oriented / Job oriented Training. Practice on Software Tools & Real Time project scenarios.
    • Mock interviews / group discussions / interview related questions.
    • Test Lab is in Cloud Technology - to practice on software tools if needed.
    • Pay one time fee & attending live classes multiple times until student is comfortable with every topic.
    • Work on real time project related examples.
    • The teaching methods / tools / topics we chosen are based on the current competitive job market.
    • More H2Kinfosys training Advantages.

Course Syllabus

    • What is Big Data?
    • What are the challenges for processing big data?
    • What technologies support big data?
    • What is Hadoop?
    • Why Hadoop?
    • History of Hadoop
    • Use cases of Hadoop
    • RDBMS vsHadoop
    • When to use and when not to use Hadoop
    • Ecosystem tour
    • Vendor comparison
    • Hardware Recommendations & Statistics
  • Significance of HDFS in Hadoop

    • Features of HDFS
    • 5 daemons of Hadoop
      • Name Node and its functionality
      • Data Node and its functionality
      • Secondary Name Node and its functionality
      • Job Tracker and its functionality
      • Task Tracker and its functionality
    • Data Storage in HDFS
      • Introduction about Blocks
      • Data replication
    • Accessing HDFS
      • CLI (Command Line Interface) and admin commands
      • Java Based Approach
    • Fault tolerance
    • Download Hadoop
    • Installation and set-up of Hadoop
      • Start-up & Shut down process
    • HDFS Federation
    • Map Reduce Story
    • Map Reduce Architecture
    • How Map Reduce works
    • Developing Map Reduce
    • Map Reduce Programming Model
      • Different phases of Map Reduce Algorithm
      • Different Data types in Map Reduce
      • how Write a basic Map Reduce Program
        • Driver Code
        • Mapper
        • Reducer
      • Creating Input and Output Formats in Map Reduce Jobs
        • Text Input Format
        • Key Value Input Format
        • Sequence File Input Format
      • Data localization in Map Reduce
      • Combiner (Mini Reducer) and Partitioner
      • Hadoop I/O
      • Distributed cache
    • Introduction to Apache Pig
    • Map Reduce Vs. Apache Pig
    • SQL vs. Apache Pig
    • Different data types in Pig
    • Modes of Execution in Pig
    • Grunt shell
    • Loading data
    • Exploring Pig
    • Latin commands

    • Hive introduction
    • Hive architecture
    • Hive vs RDBMS
    • HiveQL and the shell
    • Managing tables (external vs managed)
    • Data types and schemas
    • Partitions and buckets
    • Architecture and schema design
    • HBase vs. RDBMS
    • HMaster and Region Servers
    • Column Families and Regions
    • Write pipeline
    • Read pipeline
    • HBase commands
    • Introduction
    • Sqoop syntax
    • Database connection
    • Importing data
    • Introduction
    • Flume syntax
    • Database connection
    • Importing data

Sample Resumes

Please fill the contact form, we can email you the details.



5763 Reviews

Raji is my trainer. I am able to follow up with the basics of Big Data/Hadoop. Read more

The way Raji have given the hadoop course was really useful ( The examples given were real time examples). step by step explanation.This is an amazing course and provides a great learning opportunity.Very good presentation. Read more

I signed with H2K Infosys for Big Data/Hadoop. My mentor is Raji and she is very sweet, patience and have good knowledge of Big Data/Hadoop. I am enjoying learning this course. She teaches very deliberately and answers all dumb questions with smily face. I hope I will finish this course with very good knowledge. My wife also did the QA course with H2K Infosys and she was very happy. The good thing this they provide the videos once the class is over. which helps student to refresh and go through too many times till they are comfortable. Hats off H2K Infosys. Read more

I am enrolled for hadoop and Raji is the tutor. She has good teaching skills and sound theoritical knowledge of hadoop. She patiently answer all the queries we ask. Practical sessions haven't started yet . So cannot comment​ on that..!! But so far so good..!! Read more

I am attending the Hadoop/Bigdata sessions by Raji of h2kInfosys. She has very good knowledge of the technology and the training is very systematic. Her communication is very impressive and always attends to all the questions by the team. I have full confidence that by the end of the course I shall be well prepared to work in a new technology after a career break. Read more

So far it has been good. Raji is my trainer and she explains really well. Big Data course - Overall good experience. Read more

I have completed my Hadoop training in H2k Infosys and trainer was Raji. She was very helpful and very knowledgable.Thanks " Raji & H2k infosys team to make my hadoop training successful ". Read more

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