Enquiry Now !      

Hadoop, Big Data, Spark, Scala, Training, classes, placement, institute in pune
    Hadoop is most demanding tool in analytics since 2012 and because it is open source tool that is the reason many organization contributed in development and enhancement of Hadoop Hadoop is the only Open source tool for Bigdata storage and processing Technogeeks provides the real time training on Hadoop BigData technology by IT working professionals and also provide assurance for Job in today's competative world Technogeeks is one of the leading Institute on Hadoop Bigdata technologies including data science and Spark.

    Duration: 45 hours classroom program
    9 Weekends
    70+ Assignments in classroom
    4 POCs , 1 Real time Project
    Cluster Based Training

    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- 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 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
    • Map Reduce Framework and APIs

    • How Map Reduce works as Processing Framework
    • End to End execution flow of Map Reduce job
    • Different tasks in Map Reduce job
    • Why Reducer is optional while Mapper is mandatory?
    • Introduction to Combiner
    • Introduction to Partitioner
    • Programming languages for Map Reduce
    • Why Java is preferred for Map Reduce programming
    • POC based on Pig, Hive, HDFS, MR
    • NOSQL Databases and Introduction to HBase

    • Introduction to NOSQL
    • Why NOSQL if SQL is in market since several years
    • Databases in market based on NOSQL
    • CAP Theorem
    • ACID Vs. CAP
    • OLTP Solutions with different capabilities
    • Which Nosql based solution is capable to handle specific requirements
    • Examples of companies like Google, Facebook, Amazon, and other clients who are using NOSQL based databases
    • HBase Architecture of column families
    • Advanced Map Reduce and HBase

    • How to work on Map Reduce in real time
    • Map Reduce complex scenarios
    • Introduction to HBase
    • Introduction to other NOSQL based data models
    • Drawbacks of Hadoop
    • Why Hadoop can’t work for real time processing
    • How HBase or other NOSQL based tools made real time processing possible on the top of Hadoop
    • HBase table and column family structure
    • HBase versioning concept
    • HBase flexible schema
    • HBase Advanced
    • Zookeeper and SQOOP

    • Introduction to Zookeeper
    • How Zookeeper helps in Hadoop Ecosystem
    • How to load data from Relational storage in Hadoop
    • Sqoop basics
    • Sqoop practical implementation
    • Sqoop alternative
    • Sqoop connector
    • Quick revision of previous classes to fill the gap in your understanding and correct understandings
    • Flume , Oozie (Job Scheduling Tool) and YARN Framework

    • How to load data in Hadoop that is coming from web server or other storage without fixed schema
    • How to load unstructured and semi structured data in Hadoop
    • Introduction to Flume
    • Hands-on on Flume
    • How to load Twitter data in HDFS using Hadoop
    • Introduction to Oozie
    • How to schedule jobs using Oozie
    • What kind of jobs can be scheduled using Oozie
    • How to schedule jobs which are time based
    • Hadoop releases
    • From where to get Hadoop and other components to install
    • Introduction to YARN
    • Significance of YARN
    • 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
    • SPARK and Scala Basics

    • Introduction to Spark
    • Introduction to scala
    • Basics Features of SPARK and Scala available in Hue
    • Why Spark demand is increasing in market
    • How can we use Spark with Hadoop Eco System
    • Datasets for practice purpose
    • SPARK and Scala Advanced

    • Spark use cases with real time scenarios
    • Spark RDDs Transformations and Actions
    • Spark SQL, DataSets and Data Frames
    • Spark Streaming
    • Real time project use cases examples based on Spark and Scala
    • How we can reduce 
    • Additional Benefits

    • This training program contains 5 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 Section, 30 Hours of assignments, 25 hours for One Project and 50 Hrs for 2 Project, 350+ 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 .
Hadoop, Big Data, Spark, Scala, NoSQL based training.
We Cover Cloudera and Hortonworks Certification Track also in same training 
This course is designed to provide you training with Real time project Implementation in your system and after training you will also get assitance abut placement in MNCs. We provide Placement Assistance Guarantee because we have tie ups with Many Companies and HRs to provide skilled candidates to them in time.
You can also come and join the Free demo session and meet our experts on multiple skill sets because Technogeeks is the platform where Techies and Candidates can meet and can get the proper guidance about the career path and Technology track free of cost.
Hadoop BigData is one of the demanding technology in IT Industry and New Era of Hadoop Big Data is Spark and Data Science.
Now Hadoop with Spark and Data Science is the best combination for the clients to manage historical data in warehouse repository. Technogeeks is one of the leading Institute in Pune that Provides the Training and Project Combination by Real time IT Experts from different MNCs.

In Technogeeks more than 400 Candidates placed in past one year with package mor than 8 LPA and majority of the candidates got the job on Hadoop Big Data and Analytics fields.

Technogeeks provides Training by only IT working professionals. You can chek about our trainers on our google page.

We Start new batch of Hadoop Big Data including Spark, Scala and NoSQL Every Saturday.
Please reach us at contact@technogeekscs.co.in for more datils.

We Cover below mentioed projects as part of the Training:
Banking Domain Project
Healthcare Domain Project for Data Analytics

Enquiry Now !