Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. Gartner defines Big Data as high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. According to IBM, 80% of data captured today is unstructured, from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, to name a few. All of this unstructured data is Big Data.

Topics Covered

1.Introduction to Hadoop & Big Data What is Big Data What is Hadoop Hadoop Architecture Concepts Why Hadoop Where is Hadoop used/use cases How to setup Hadoop Advantages/Disadvantages of Hadoop 2.Basics Hadoop Components HDFS Map Reduce 3. HDFS Architeture Concepts HDFS and its components What are HDFS Daemons What is NameNode NameNode features & functionality What is DataNode DataNode features & functionality What is JobTracker How JobTracker works What is TaskTracker How TaskTracker works Reading files from HDFS Writing files to HDFS Rack Aware concepts 4. "MapReduce Architeture & DesignConcepts" What is a Client Lab: How it works What is a Job Lab: How it works What is MapReduce Lab: How it works Simple MapReduce Algorithm Sample Lab: How it works Complex MapReduce Algorithm Sample Lab: How it works MapReduce using Eclipse Integration Lab: How it works Deploy MapReduce on Hadoop Setup Hadoop How to Debug MapReduce What is Map Chaining Lab: How it works Testing Fundamentals Input/OutputFormatters & RecordReaders What is Job Scheduling How to configure Explore Apache MapReduce WebUI MapReduce Combiners & Partitioners Sorting & Searching in HDFS MapReduce DistributedCache What are Counters Lab: How it works 5. Hadoop Administration Concepts Lab: HDFS user commands Lab: HDFS admin commands Administrative procedures Lab: Understanding dfsadmin & mradmin Lab: Understanding Healthcheck & safemode Lab: Configuring Schedulers Lab: Configuring Queues 6. Hive & it concepts Hive Fundamentals Hive Architecture Hive Installation & setup HQL concepts Lab: HQL Integration with Hadoop CLI & Thrift modes Lab: How it works What is UDF Lab: How it works 7. Pig & its concepts Pig Fundamentals Pig Architecture Pig Installation & setup Lab: How it works What is Pig UDF Lab: How it works 8. Hbase Introduction to Hbase Hbase Basics Column Families Scans Hbase Architecture Hbase Rest Client Hbase Thrift Client Hbase Web UI Hbase Admin Hbase Schema Definition Hbase CRUD Ops 9. Flume What is Flume Installation & Setup Lab: How it works 10. SQOOP Introduction to SQOOP 11. OOPS Concepts Why OOPs What is OOPs Designing Objects & Classes Encapsulation Polymorphism Inheritance Abstraction OO Design 12. Core Java Concepts Java Basics What is Serialization Introduction to Generics Introduction to Collections I/O Concepts 13. Functional Programming Introduction 14. Linux Basics Fundamentals

Who should attend

Any one who is looking for software field

Pre-requisites

No need trainer will go through it

What you need to bring

Based on the requirement

Key Takeaways

Mock interviews will be conducted Interview Questions will be given Case study for Practice Real Time Projects Discussion and CV Preparation 100% assistance for each candidate till they get a job