Hadoop Analyst

Introduction To Hadoop Ecosystem

Why we need Hadoop
> Why Hadoop is in demand in market now a days
> Where expensive SQL based tools are failing
> Key points , Why Hadoop is leading tool in current It Industry
> Definition of BigData Hadoop nodes
> Introduction to Hadoop Release-1
> Hadoop Daemons in Hadoop Release-1> Introduction to Hadoop Release-2> Hadoop Daemons in Hadoop Release-2> Hadoop Cluster and Racks> Hadoop Cluster Demo> How Hadoop is getting two categories Projects-> New projects on Hadoop> Clients want POC and migration of Existing tools and Technologies on Hadoop Technology> How Open Source tool (HADOOP) is capable to run jobs in lesser time which take longer time in> Hadoop Storage – HDFS (Hadoop Distributed file system)> Hadoop Processing Framework (Map Reduce / YARN)> Alternates of Map Reduce> Why NOSQL is in much demand instead of SQL> Distributed warehouse for HDFS> Most demanding tools which can run on the top of Hadoop Ecosystem for specific requirements in specific scenarios> Data import/Export tools

Hadoop Installation and Basic Hands on Cluster

Hadoop installation> Introduction to Hadoop FS and Processing Environment’s UIs> How to read and write files> Basic Unix commands for Hadoop> Hadoop FS shell> Hadoop releases practical> Hadoop daemons practical

Introduction to Pig (ETL Tool)

Pig Introduction> Why Pig if Map Reduce is there?> How Pig is different from Programming languages> Pig Data flow Introduction> How Schema is optional in Pig> Pig Data types> Pig Commands – Load, Store , Describe , Dump> Map Reduce job started by Pig Commands> Execution plan

Pig Advanced with Scenarios

Pig- UDFs> Pig Use cases> Pig Assignment> Complex Use cases on Pig> XML Data Processing in Pig> Structured Data processing in Pig> Semi-structured data processing in Pig> Pig Advanced Assignment> Real time scenarios on Pig> When we should use Pig> When we shouldn’t use Pig> Live examples of Pig Use cases
Hive Warehouse for Distributed Storage
Hive Introduction> Meta storage and meta store> Introduction to Derby Database> Hive Data types> HQL> DDL, DML and sub languages of Hive> Internal , external and Temp tables in Hive> Differentiation between SQL based Datawarehouse and Hive

Advanced concepts in Hive

Hive releases> Why Hive is not best solution for OLTP> OLAP in Hive> Partitioning> Bucketing> Hive Architecture> Thrift Server> Hue Interface for Hive> How to analyze data using Hive script> Differentiation between Hive and Impala> UDFs in Hive> Complex Use cases in Hive> Hive Advanced Assignment> Real time scenarios of Hive> POC on Pig and Hive , With real time data sets and problem statements

Hue, Hadoop Releases comparison, Hadoop Real time scenarios

Introduction to Hue> How Hue is used in real time> Hue Use cases> Real time Hadoop usage> Real time cluster introduction> Hadoop Release 1 vs Hadoop Release 2 in real time> Hadoop real time project> Major POC based on combination of several tools of Hadoop Ecosystem> Comparison between Pig and Hive real time scenarios> Real time problems and frequently faced errors with solution

Additional Benefits

This training program contains 2 POCs and Two real time projects with problem statements and data sets> This training is based on multi node Hadoop Cluster machines> We provide you several data sets which you can use for further practices on Hadoop> 42 Hours Classroom Section30 Hours of assignments25 hours for One Project and 50 Hrs for 2 Project350+ Interview Questions> Administration and Manual Installation of Hadoop with other Domain based projects will be done on regular basis apart from our normal batch schedule .We do have projects from Healthcare , Financial , Automotive ,Insurance , Banking , Retail etc , which will be given to our students as per their requirements .