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Hadoop Development Classes in Pune

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We Invite you to attend Demo Class, absolutely Free. We are Happy to guide you Step by Step regarding this job oriented Course and job Placement Benefits After Completing the Course.

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Hadoop

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Career Opportunities

After completion of this course, you will be able to apply for these Jobs.

Big Data Engineer

Hadoop Developer

System Administrator

Tech Support Engineer

Most Popular Employer Name for Employees with a Big Data Hadoop Certification

Mu Sigma

Accenture

Capgemini

InfoSys Limited

IBM India Private Limited

Igate Global Solutions Ltd.

Tata Consultancy Services Limited

Salary Growth Rates for Freshers

Overview

Introduction to Hadoop Course

Big Data is the data which can not be processed by traditional database systems i.e.Mysql,Sql.
Big data consist of data in the structured ie.Rows and Coloumns format ,semi-structured i.e.XML records and Unstructured format i.e.Text records,Twitter Comments. Hadoop is an software framework for writing and running distributed applications that processes large amount of data.Hadoop framework consist of Storage area known as Hadoop Distributed File System(HDFS) and processing part known as MapReduce programming model. 

Proficiency After Training

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Master the HDFS (Hadoop Distributed File System) with YARN architecture

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storage and resource management with HDFS & YARN

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Dive in knowledge in MapReduce

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Database creation in Hive and Impala

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Spark Application development

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Learn Pig and how to use

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Flume architecture, Understand the Difference between HBase and RDBMS

Hadoop Training in Pune

Hadoop Distributed File System is a filesystem designed for large-scale distributed data processing under framework such as Mapreduce.
Hadoop works more effectively with single large file than number of smaller one. Hadoop mainly uses four input formats-FileInput Format,KeyValueTextInput Format,TextInput Format,NLineInput Format. Mapreduce is Data processing model consist of data processing primitives called Mapper and Reducer.  Hadoop supports chaining MapReduce programs together to form a bigger job.We will explore various joining technique in hadoop for simultaneously processing multiple datasets.Many complex tasks need to be broken down into simpler subtasks,each accomplished by an individual Mapreduce jobs.

Hadoop Classes in Pune

From the citation data set, you may be interested in finding ten most cited patents. A sequence of two Mapreduce jobs can do this.

Hadoop clusters which support for Hadoop HDFS,MapReduce ,Sqoop ,Hive ,Pig , HBase , Oozie , Zookeeper, Mahout , NOSQL , Lucene/Solr,Avro,Flume,Spark,Ambari Hadoop is designed for offline processing and analysis of large-scale data.
Hadoop is best used as a write-once, Read-many-times type of datastore.
With the help of Hadoop, large dataset will be divided into smaller (64 or 128 MB)blocks that are spread among many machines in the clusters via Hadoop Distributed File System.

The key functions of Hadoop are,
1)approachable-Hadoop runs on Huge clusters of appropriate Hardware apparatus.
2)Powerful-Because it is intentional to run on clusters of appropriate Hardware apparatus, Hadoop is an architect with the presumption of repeated hardware malfunctions. It can handle most of such failures.
3)Resizable-Hadoop measures sequentially to hold large data by including more nodes to the cluster.
4)Simple-Hadoop allows users to speedily write well-organized parallel codes.

What is Hadoop Development?

There are mainly two teams when it comes to Big Data Hadoop. One team consists of Hadoop Administrators and the second one is Hadoop Developers. So, the common question which comes in mind is what are their roles and responsibilities.

To know their roles and responsibilities we need to know what is Big Data Hadoop. With the evolution of the internet and the increase in the smartphone industry and with the easy access to the internet the amount of data that is generated on a daily basis has also been increased. This data can be anything, for example, your daily online transaction, you feed activity on social media sites, the amount of time you spend on a particular app, etc. So the data can be generated from anywhere in the form of logs.

Now with this amount of data that is generated on a daily basis, we cannot rely on the traditional RDBMS to process our data as the SLA for the traditional RDBMS is very high. And access to old data that is in the archives cannot be processed in real-time.

Hadoop provides a solution to these entire problems. You can put all your data in the Hadoop Distributed File System and can access and process the data in real-time, whether the data is generated today or the data is 10 years old, it does not matter, you can process the data easily in real-time.

Let me explain the above situation with a real-time example. Suppose you are a customer od XYZ telecom company from the past 10 years, so every call record will be stored in the form of logs. Now that Telecom Company wants to introduce new plans for its customers for a particular age group and for that they want to access the logs of each and every customer who falls under that age group. The main problem arises now that this data has been stored in traditional RDBMS and only 40% of the data can be processed in real-time and rest 60% cannot be processed in real-time as this data is stored in the form of archives and the company cannot wait too long to get the data from the archives and then process it.

The data available for processing in real-time is 40% and if the company takes a decision on the 40% data available then the success rate of that decision will be 40% and the company cannot take that risk. Now if all this data is stored in Hadoop Distributed File System then the access to 100% data is in real-time and we can process 100% data.

The above example has cleared your doubts about why is Big Data Hadoop required in industry and is so much in demand. Now we will discuss the two teams related to Big Data Hadoop to make things work. One in Hadoop Admin team and other is Hadoop Development team

Hadoop Administrator Team:

  • This team is responsible for the maintenance of the Cluster in which the data is stored.
  • This team is responsible for the authentication of the users that are going to work on the cluster.
  • This team is responsible for the authorization of the users that are going to work on the cluster.
  • This team is responsible for the troubleshooting, that means if the cluster goes down then it is their job to get back the cluster to running state.
  • This team deploys, configures and manages the services present in the cluster.

Basically Hadoop Admin team looks after the cluster, is responsible for the good health of the cluster, security of cluster and managing the data. But what to do with the data, a company does not want to spend this amount of money in just storing the data.

Now comes the Hadoop Development team. You might have remembered in the above example when we discussed the real-time access. This real-time access to the data will help the Hadoop Development team to process the data. Now,

What is data processing?

The data which comes to the cluster is raw data. Raw Data means it can be structured, unstructured, semi-structured data or binary data. We need to filter that data that is of use and process the data to generate some insights so that business decisions can be made. All the work, filtering the data the processing it falls under the Hadoop Development team.

Hadoop Development Team:

  • This team is responsible for ETL, which means to extract, transform and load. 
  • This team performs analysis of data sets and generate insights.
  • This team performs high-speed querying.
  • Reviewing and managing Hadoop log files.
  • Defining Hadoop Job flows.

As a Hadoop Developer you need to know about the basic architecture and working of the following services.

  • Apache Flume
  • Apache Pig
  • Apache Sqoop
  • Apache Hive
  • Apache Impala
  • Spark
  • Scala
  • HBase

Apache Flume and Apache Sqoop are ETL Tools. These are the basic tools in HDFS that are used to get the data in the cluster. Apache Hive is a data warehouse and is used to run queries on the data set using Hive QL. Impala is also used for the queries. Spark is used for High-speed processing of data set. HBase is a database. The above-mentioned points were the introduction about the services and what are their uses in the Hadoop Cluster.

 

Who Can Do this Course?

W

Freshers

W

BE/ Bsc Candidate

W

Any Engineers

W

Any Graduate

W

Any Post-Graduate

W

Working Professionals

Training Module

Fast Track Batch

Highlights

Session: 4 Hrs per day + Practical

Duration: 1 Month

Certification: Yes

Training Type: Classroom

Study Material: Latest Book

Days: Monday to Friday

Practical & Labs: Regular

Personal Grooming: Flexible Time

 

Regular Batch

Highlights

Session: 2 Hrs per day

Duration: 2 Months

Certification: Yes

Training Type: Classroom

Study Material: Latest Book

Days: Monday to Friday

Practical & Labs: Regular

Personal Grooming: Flexible Time

 

Weekend Batch

Highlights

Session: 3 Hrs per day

Duration: 2.5 Months

Certification: Yes

Training Type: Classroom

Study Material: Latest Book

Days: Saturday & Sunday

Practical & Labs: As Per Course

Personal Grooming: Flexible Time

 

Testimonial

Shubham Mahalkar

Seven Mentor is the best training institute in Pune for Big Data Hadoop. It was a nice experience. Did a many real time projects. Good teaching. I have learnt various tools like pig, hive, hbase and many more with a lot of real world examples.I’m satisfy with my Hadoop training and also the extra knowledge that seven mentor provides. The faculty available here is very supportive. Thank you sevenmentor

Sourabh Goswami

Best experience to learn hadoop from SevenMentor, very nice trainer and facilities. Infrastructure is also good. Trainer is very helpful and always solved our doubts. Very good understanding of clustering and multinode installation. Hadoop admin syllabus helped me a lot in my project. Thank you Sevenmentor. Guys worth to join and very cost effective.

Renu Pujari

Pune for Big Data Hadoop. It was a nice experience. Did a many praticals in Lab.Practical training…labs are well equipped.advance training in development is good..

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Frequently Asked Questions

How About the Placement Assistance?

All the Courses Are Merged With Placement Assistance

Is The Course Fees In My Budget?

We Are Committed For Lowest Course Fees in the Market

Do you Provide Institutional Certification After the course?

Yes! We do provide Certification straight after completion of the Course

Do you have any refund policy?

Sorry! We don’t refund fees in any Condition.

How about the Discount offer on this Course?

Yes, this Course has heavy Offer discount in fees if you pay in One Shot/ Group Admission!

I Am Worried About Fees Installment Option If Any?

Don’t Worry! We Do Have Flexible Fees Installment Option

Do We Get Practical Session For This Course?

Yes! This Course Comes With Live Practical Sessions And Labs

Is the Course Comes With Global Certification?

Sure! Most of our Course Comes with Global Certification for which you have to give Exam at the End of the Course

Will your institute conduct the Exam for Global Certification?

Yes we do have different Exam Conducting Department where you can apply for certain course’s Exam

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For any inquiry related to course, we have opened our portal, accept the requests, We assure to help within time.

Placement Department

we have Separate placement department Who are Continuously work on Company tie-ups and Campus requritment process

Money for a quality and Value

we have a policy under which we care for 100% job Assistance for each course until you got your dream job, Hence anyone can apply for learning with Quality

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We have US Based In-house Company under SevenMentor Roof, thus candidate will get Live project working Environment.

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