Hadoop Administration Certification Training

Deep dive into Hadoop with practical examples and become an expert Hadoop Administrator

  • Get a deeper knowledge of Big data Hadoop and its core components
  • Hands-on Hadoop Admin activities including Cluster Configuration and Monitoring
  • Get experiential knowledge of Hadoop architecture and its ecosystem
  • Learn how to work with CDH and its administration tool Cloudera Manager
  • Projects including banking & government sectors, e-commerce websites, etc

Why learn Hadoop Administration?

Apache Hadoop™ is an effective and dynamic data platform that simplifies and allows for the distributed processing of large data sets across clusters of computers and servers. Hadoop is the perfect choice for organizations that have to deal with the challenges involved in handling vast amounts of structured and unstructured data.  The Hadoop framework is used for analyzing data and helping them to make informed business decisions that are based on the insights gleaned from the data. 

This ever-increasing data and the need to analyse it for favourable business outcomes has in turn increased the demand for professionals skilled in Hadoop and data analysis. A Hadoop Administrator’s primary responsibility is to manage the deployment and maintenance of Hadoop clusters. In other words, a Hadoop admin ensures smooth operation of Hadoop clusters, problem mitigation, safety and improved performance. 
A training in Hadoop Administration will help prepare you for the demands of the industry. New innovations in technology have made it mandatory for IT professionals to be on par with the latest developments. A Hadoop Administrator training will ensure that there is no skill gap between what you know and what the industry wants, thus making you a valuable employee. Furthermore, the demand for data analysts has seen a meteoric rise in the past few years, thus making certified Hadoop Administrators a niche resource. 

Benefits

Hadoop is the perfect solution for the challenges faced by vast amounts of unstructured data that are a goldmine when analysed. Hadoop certification benefits not just the holder but also the organizations who hire them.

A Hadoop Administrator certification benefits an individual in the following ways:

  • Become an in-demand resource who can manage Hadoop clusters and help the organization with big data analysis.
  • The Hadoop Market is expected to reach $99.31 billion by 2022 attaining a 28.5% CAGR. This is great news for those in the data analytics field
  • Exposure to multiple industries like Healthcare, consumer, banking, energy, manufacturing, etc.
  • A Certified Hadoop Administrator can earn an average salary of $123,169 per year as per ZipRecruiter.

Here are some of the reasons why Hadoop administrators can benefit your organization:

  • Efficient and reliable professionals will help to manage large Hadoop clusters in the organization
  • They take care of the day-to-day workings of Hadoop clusters and ensure data safety
  • Excellent knowledge of Hadoop architecture helps to plan Hadoop clusters in an organized way
  • Hadoop administrators make the work safe and secure
  • Hadoop Administrators can help in the maintenance of highly scalable storage platforms

As technologies are becoming more complex and the demand for data processing is on the rise, having a certificate in Hadoop Administration can bring an array of opportunities for you!

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What you will learn

Prerequisites

There are no specific prerequisites for the Hadoop Administration Training, but a basic knowledge of Linux command-line interface will be beneficial.

Who should attend the Hadoop Administration course?

  • DevOps Engineers
  • Architects
  • Project Managers
  • Linux / Unix Administrators
  • Database Administrators
  • Windows Administrators
  • Infrastructure Administrators
  • System Administrators
  • Analytics Professionals
  • Senior IT professionals
  • Data Management Professionals
  • Testing and Mainframe professionals
  • Business Intelligence Professionals
  • Anyone who wants to build the carrier in the Distributed World of Big Data

KnowledgeHut Experience:

Instructor-led Live Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the latest training!

Learn through Doing

Learn theory backed by practical case studies, exercises, and coding practice. Get skills and knowledge that can be applied effectively.

Mentored by Industry Leaders

Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and feedback on your final projects from professional developers.

Real-Time Projects With Industry Standards

Automatic Scaling up the Data Node

Based on the alerts in the cluster, automatically a new datanode should add on the fly when it reaches a limit.

Tool upgradation of Hadoop Ecosystem

Hadoop ecosystem tools installation and upgradation from end to end.

Curriculum

Learning Objective :

Understanding what is Big Data and its solution for traditional Problems. You will learn about  Hadoop and its core components and you will know how to read and write happens in HDFS. You will also know the roles and responsibilities of a Hadoop Administrator.

Topics :

  • Introduction to big data
  • Limitations of existing solutions
  • Common Big Data domain scenarios
  • Hadoop Architecture
  • Hadoop Components and Ecosystem
  • Data loading & Reading from HDFS
  • Replication Rules
  • Rack Awareness theory
  • Hadoop cluster Administrator: Roles and Responsibilities.

Hands-on:

Writing and Reading the Data from hdfs, how to submit the job in Hadoop 1.0 and YARN.

Learning Objectives: 

Understanding different Configuration files and building Hadoop Multi Node Cluster. Differences in Hadoop 1.0 and Hadoop 2.0. You will also get to know the architecture of Hadoop 1.0 and Hadoop2.0(YARN).

Topics

  • Working of HDFS and its internals
  • Hadoop Server roles and their usage
  • Hadoop Installation and Initial configuration
  • Different Modes of Hadoop Cluster.
  • Deploying Hadoop in a Pseudo-distributed mode
  • Deploying a Multi-node Hadoop cluster
  • Installing Hadoop Clients
  • Understanding the working of HDFS and resolving simulated problems.
  • Hadoop 1 and its Core Components.
  • Hadoop 2 and its Core Components.

Hands-on:

Creating Pseudo and Fully Distributed Hadoop Cluster. Changing different configuration Properties while submitting the Jobs and different hdfs admin commands.

Learning Objectives: 

Understanding the various properties of Namenode, Data node, and Secondary Namenode. You will also learn how to add and decommission the data node to the cluster. You will also learn Various Processing frameworks in Hadoop and its Architecture in the context of Hadoop administrator and schedulers.

Topics:

  • Properties of NameNode, DataNode and Secondary Namenode
  • OS Tuning for Hadoop Performance
  • Understanding Secondary Namenode
  • Log Files in Hadoop
  • Working with Hadoop distributed cluster
  • Decommissioning or commissioning of nodes
  • Different Processing Frameworks
  • Understanding MapReduce
  • Spark and its Features
  • Application Workflow in YARN
  • YARN Metrics
  • YARN Capacity Scheduler and Fair Scheduler
  • Understanding Schedulers and enabling them.

Hands-on:

Changing the configuration files of Secondary Namenode. Add and remove the data nodes in a Distributed Cluster. And also Changes Schedulers in run time while submitting the jobs to YARN.

Learning Objectives: 

You will learn regular  Cluster Administration tasks like balancing data in the cluster, protecting data by enabling trash, attempting a manual failover, creating backup within or across clusters

Topics: 

  • Namenode Federation in Hadoop
  • HDFS Balancer
  • High Availability in Hadoop
  • Enabling Trash Functionality
  • Checkpointing in Hadoop
  • DistCP and Disk Balancer.

Hands-on:

Works with Cluster Administration and Maintenance tasks. Runs DistCP and HDFS Balancer Commands to get even distribution of the data.

Learning Objectives:

You will learn how to take Backup and recovery of data in master and slaves. You will also learn about allocating Quota to the master and slaves files.

 Topics:

  • Key Admin commands like DFSADMIN
  • Safemode
  • Importing Check Point
  • MetaSave command
  • Data backup and recovery
  • Backup vs Disaster recovery
  • Namespace count quota or space quota
  • Manual failover or metadata recovery.

Hands-on:

Do regular backup using MetaSave commands. You will also run commands to do data Recovery using Checkpoints.

Learning Objective:

You will understand about Cluster Planning and Managing, what are the aspects you need to think about when planning a setup of a new cluster.

 Topics :

  • Planning a Hadoop 2.0 cluster
  • Cluster sizing
  • Hardware
  • Network and Software considerations
  • Popular Hadoop distributions
  • Workload and usage patterns
  • Industry recommendations.

Hands-on:

Setting up a new Cluster and scaling Dynamically. Login to different Hadoop distributions online.

Learning Objectives:

You will get to know about the Hadoop cluster monitoring and security concepts. You will also learn how to secure a Hadoop cluster with Kerberos.

 Topics :

  • Monitoring Hadoop Clusters
  • Authentication & Authorization
  • Nagios and Ganglia
  • Hadoop Security System Concepts
  • Securing a Hadoop Cluster With Kerberos
  • Common Misconfigurations
  • Overview on Kerberos
  • Checking log files to understand Hadoop clusters for troubleshooting.

Hands-on:

Monitor the cluster and also authorization of Hadoop resource by granting tickets using Kerberos.

Learning Objectives:

You will learn how to configure Hadoop2 with high availability and upgrading. You will also learn how to work with the Hadoop ecosystem.

Topics :

  • Configuring Hadoop 2 with high availability
  • Upgrading to Hadoop 2
  • Working with Sqoop
  • Understanding Oozie
  • Working with Hive.
  • Working with Pig.

Hands-on:

Login to the Hive and Pig shell with their respective commands. You will also schedule OOZIE Job.

Learning Objectives:

You will see how to work with CDH and its administration tool Cloudera Manager. You will also learn ecosystem administration and its optimization.

Topics:

  • Cloudera Manager and cluster setup
  • Hive administration
  • HBase architecture
  • HBase setup
  • Hadoop/Hive/Hbase performance optimization.
  • Pig setup and working with a grunt.

Hands-on:

Install CDH and works with Cloudera Manager. Install new parcel in CDH machine.

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FAQS

Hadoop Administration Course

There are no prerequisites to take up Hadoop Administration training, but a basic knowledge of the Linux command line interface will be more helpful to get the Hadoop concepts easily.

Individuals with basic knowledge of Linux can attend. Knowledge of algorithms and other computer science topics is a bonus. Existing knowledge of Hadoop is not required. This training is ideal for:

  • Fresher’s Who Would like to build a career in the Distributed computing World
  • Those who want to learn administration tasks like Hadoop Admin responsibilities
  • DevOps Engineer and Architects
  • Analytics Professionals
  • Senior IT professionals
  • Testing and Mainframe professionals
  • Data Management Professionals
  • Business Intelligence Professionals
  • Project Managers
  • Graduates looking to build a career in Big Data Analytics

The Hadoop Administration training does not have any restrictions although participants would benefit if they’re familiar with basic programming languages.

Workshop Experience

All of the training programs conducted by us are interactive in nature and fun to learn as a great amount of time is spent on hands-on practical training, use case discussions, and quizzes. An extensive set of collaborative tools and techniques are used by our trainers which will improve your online training experience.

The Hadoop Administration training conducted at KnowledgeHut is customized according to the preferences of the learner. The training is conducted in three ways:

  • Online Classroom training: You can learn from anywhere through the most preferred virtual live and interactive training   
  • Self-paced learning: This way of learning will provide you lifetime access to high-quality, self-paced e-learning materials designed by our team of industry experts
  • Team/Corporate Training: In this type of training, a company can either pick an employee or entire team to take online or classroom training. Flexible pricing options, standard Learning Management System (LMS), and enterprise dashboard are the add-on features of this training. Moreover, you can customize your curriculum based on your learning needs and also get post-training support from the expert during your real-time project implementation.

The sessions that are conducted are 30 hours of live sessions, with 60 hours MCQs and Assignments.

Course Duration information:

Online training: 

  • Duration of 15 sessions.
  • 2 hours per day.

Weekend training: 

  • Duration of 4 Weeks.
  • Class held 2 days per week on Saturday,  Sunday.
  • Note: Each session will be of 3 hours.

Corporate training: 

  • Depends on company concerns.

Yes, our lab facility at KnowledgeHut has the latest version of hardware and software and is very well-equipped. We provide Cloudlabs so that you can get a hands-on experience of the features of Hadoop Administration. Cloudlabs provides you with real-world scenarios can practice from anywhere around the globe. You will have an opportunity to have live hands-on coding sessions. Moreover, you will be given practice assignments to work on after your class.

Here at KnowledgeHut, we have Cloudlabs for all major categories like cloud computing, web development, and Data Science.

This Hadoop Administration training course has three projects, viz Automatic Scaling up the Data Node, Tool upgradation of Hadoop Ecosystem

  • Automatic Scaling up the Data Node: Based on the alerts in the cluster, automatically a new datanode should add on the fly when it reaches a limit.
  • Tool upgradation of Hadoop Ecosystem: Hadoop ecosystem tools installation and upgradation from end to end.

The Learning Management System (LMS) provides you with everything that you need to complete your projects, such as the data points and problem statements. If you are still facing any problems, feel free to contact us.

After the completion of your course, you will be submitting your project to the trainer. The trainer will be evaluating your project. After a complete evaluation of the project and completion of your online exam, you will be certified as a Hadoop Administrator.

Online Experience

We provide our students with Environment/Server access for their systems. This ensures that every student experiences a real-time experience as it offers all the facilities required to get a detailed understanding of the course.

If you get any queries during the process or the course, you can reach out to our support team.

The trainer who will be conducting our Hadoop Administration certification has comprehensive experience in developing and delivering Big Data applications. He has years of experience in training professionals in Big Data. Our coaches are very motivating and encouraging, as well as provide a friendly learning environment for the students who are keen about learning and making a leap in their career.

Yes, you can attend a demo session before getting yourself enrolled for the Hadoop Administration training.

All our Online instructor-led training is an interactive session. Any point of time during the session you can unmute yourself and ask the doubts/ queries related to the course topics.

There are very few chances of missing any of the Hadoop Administrator training session at KnowledgeHut. But in case you miss any lecture, you have two options:

  • You can watch the online recording of the session
  • You can attend the missed class in any other live batch.

The online Hadoop Administration course recordings will be available to you with lifetime validity.

Yes, the students will be able to access the coursework anytime even after the completion of their course.

Opting for online training is more convenient than classroom training, adding quality to the training mode. Our online students will have someone to help them any time of the day, even after the class ends. This makes sure that people or students are meeting their end learning objectives. Moreover, we provide our learners with lifetime access to our updated course materials.

In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.

This will be live interactive training led by an instructor in a virtual classroom.

We have a team of dedicated professionals known for their keen enthusiasm. As long as you have a will to learn, our team will support you in every step. In case of any queries, you can reach out to our 24/7 dedicated support at any of the numbers provided in the link below: https://www.knowledgehut.com/contact-us

We also have Slack workspace for the corporates to discuss the issues. If the query is not resolved by email, then we will facilitate a one-on-one discussion session with one of our trainers.

Finance Related

We accept the following payment options:

  • PayPal
  • American Express
  • Citrus
  • MasterCard
  • Visa

KnowledgeHut offers a 100% money back guarantee if the candidates withdraw from the course right after the first session. To learn more about the 100% refund policy, visit our refund page.

If you find it difficult to cope, you may discontinue within the first 48 hours of registration and avail a 100% refund (please note that all cancellations will incur a 5% reduction in the refunded amount due to transactional costs applicable while refunding).  Refunds will be processed within 30 days of receipt of a written request for refund. Learn more about our refund policy here.

Typically, KnowledgeHut’s training is exhaustive and the mentors will help you in understanding the concepts in-depth.

However, if you find it difficult to cope, you may discontinue and withdraw from the course right after the first session as well as avail 100% money back.  To learn more about the 100% refund policy, visit our Refund Policy.

Yes, we have scholarships available for Students and Veterans. We do provide grants that can vary up to 50% of the course fees.

To avail scholarships, feel free to get in touch with us at the following link:
https://www.knowledgehut.com/contact-us

The team shall send across the forms and instructions to you. Based on the responses and answers that we receive, the panel of experts takes a decision on the Grant. The entire process could take around 7 to 15 days


Yes, you can pay the course fee in instalments. To avail, please get in touch with us at https://www.knowledgehut.com/contact-us. Our team will brief you on the process of instalment process and the timeline for your case.

Mostly the instalments vary from 2 to 3 but have to be fully paid before the completion of the course.

Visit the following page to register yourself for the Hadoop Administration Training:

https://www.knowledgehut.com/big-data/hadoop-administration-training/schedule/

You can check the schedule of the Hadoop Administration Training by visiting the following link:

https://www.knowledgehut.com/big-data/hadoop-administration-training/schedule/

We have a team of dedicated professionals known for their keen enthusiasm. As long as you have a will to learn, our team will support you in every step. In case of any queries, you can reach out to our 24/7 dedicated support at any of the numbers provided in the link below: https://www.knowledgehut.com/contact-us

We also have Slack workspace for the corporates to discuss the issues. If the query is not resolved by email, then we will facilitate a one-on-one discussion session with one of our trainers.


Yes, there will be other participants for all the online public workshops and would be logging in from different locations. Learning with different people will be an added advantage for you which will help you fill the knowledge gap and increase your network.

Hadoop Administration FAQ's

Hadoop Administration

A Hadoop administrator administers and manages the set of Hadoop clusters. A Hadoop administrator’s responsibilities include setting up Hadoop clusters, backup, recovery and maintenance of the clusters. Good knowledge of Hadoop architecture is required to become a Hadoop administrator. Some of the key responsibilities of a Hadoop Administrator are: 

  • Takes care of the day-to-day running of Hadoop Clusters. 
  • Makes sure that Hadoop cluster is running all the time. 
  • Responsible for managing and reviewing Hadoop log files. 
  • Responsible for capacity planning and estimating the requirements. 
  • Implementation of ongoing Hadoop infrastructure. 
  • Cluster maintenance along with the creation and removal of nodes. 
  • Keeping an eye on Hadoop cluster security and connectivity. 
  • Tuning the performance of Hadoop clusters. 
  • Managing and reviewing the log files of Hadoop. 

Hadoop mainly consists of three layers:  

  • HDFS (Hadoop Distributed File System): the place where all the data is stored,  
  • Application layer (on which the MapReduce engine sits): to process the stored data, and 
  • YARN: which allocates the resources to various slaves. All of these are operating on Master and Slave nodes. 

Hadoop is an open-source framework written in Java that enables the distributed processing of large datasets. Hadoop is not a programming language. 

Hadoop developers are needed to develop or program applications whereas administrators are required to run those applications. Let’s see how Hadoop developer and administrator differ from each other in terms of roles and responsibilities:  

A few responsibilities of Hadoop Administrator: 

  • Installing Hadoop in a Linux environment
  • Runningand maintaininga Hadoop cluster 
  • Ensuringthat a Hadoop cluster is running all the time 
  • Creation and removal of a new node in a cluster environment
  • Implementingand administeringHadoop infrastructure continuously 

A few responsibilities of Hadoop developer: 

  • To load data using ETL tools from various platforms into the Hadoop platform
  • Deciding a file format that would be most effective for a task
  • Cleaning data using user-defined functions or streaming API based on the requirements
  • Definingthe job flow in Hadoop 
  • Maintaining, scheduling, and managinglog files.

Following is a list of different components of the Hadoop ecosystem: 

  • HDFS 
  • MapReduce 
  • YARN 
  • Hive 
  • Apache Pig 
  • Apache HBase 

Hadoop can store and process many unstructured datasets that are distributed across various clusters using simple program models. It breaks up unstructured data and distributes it into several parts for side by side data analysis. Rather than relying on one computer, the library is designed for detecting and handling failures of the application layer, thereby delivering a high-quality service on top of a cluster of computers. On top of these, Hadoop is an open-source framework available to everyone. 

Hadoop is a framework that is mainly written in the Java programming language, with some native code in C and command-line utilities written as shell scripts. Since MapReduce Java code is common any programming can be used with Hadoop. 

The best language to use for Hadoop is a matter of personal choice. Python helps when doing quick and simple programs. While the number of functions can be reduced using other languages like Python and Scala, there are some advanced features of Hadoop that are only available via Java API. Often, the programmer would be required to dig deep into the coding and figure out what is wrong, and Java especially helps in doing that. Scala language can be used because Hadoop is built on the same ecosystem. 

If Big Data is the problem, Hadoop can be said to be the solution. The Hadoop framework can be used for storing and processing big data that is present in large clusters in an organized manner. Hadoop segregates the big data into small parts and stores them separately on different servers present in a particular network. It is highly efficient and can handle large volumes of data. So, with knowledge of Hadoop, you can work on Big Data quickly and efficiently. 

Hadoop plays a tremendous role in the Big Data industry. It is easy to use, scalable and cost-effective. Hadoop provides massive storage solutions for any kind of data and can handle virtually limitless concurrent tasks or jobs. 

Hadoop is not a database; it is a software ecosystem that allows parallel computing on a vast scale. Hadoop enables specific types of NoSQL distributed databases (e.g. HBase) to spread the data across thousands of servers without affecting the quality.  

Yes, Hadoop is an Open-Source software framework that allows storing and processing the massive amount of data.  

Use of Big Data Hadoop

Hadoop is the most favoured and in-demand Big Data tool worldwide. It is popular due to the following attributes: 

  • Power of Computing-  

The distributed computing model in Hadoop processes big data very fast. The power of computing will be more if the number of nodes you use is more. 

  • Massive data storing and processing- 

This tool lets organizations store and process massive amounts of any type of data quickly. 

  • Zero Fault tolerance rate- 

HDFS is highly fault tolerant and handles faults by the process of replica creation. In case a node goes down, the tasks are redirected to other nodes to ensure that the distributed computing doesn’t fail, and fault tolerance rate will be zero. 

  • Cheapest Price- 

It is an open-source framework that uses commodity hardware to store and process large amounts of data.  

  • More Flexibility- 

Hadoop allows data processing before storing it, unlike in a traditional relational database.   

  • Scalability-  

You can extend your system easily if you are required to handle more data by adding nodes with the help of the administration.    

Following are the benefits of Hadoop technology: 

  • Hadoop is a storage platform which can store and distribute very large sets of data across hundreds of servers 
  • Hadoop is a cost-effective tool as it can store huge data sets for businesses 
  • Hadoop allows businesses to access new data sources easily  
  • Hadoop can process terabytes of data in just minutes and petabytes of data in hours 
  • The major benefit of using Hadoop is that it is resilient to failure due to its zero-fault tolerance rate    

The following are the top five organizations that are using Hadoop: 

  • Marks and Spencer 
  • Royal Bank of Scotland 
  • Expedia 
  • British Airways 
  • Royal Mail 

Hadoop is a crucial tool in Data Science, and Data Scientists who have knowledge of Hadoop are highly sought after. Given below are the reasons why Data Scientists use Hadoop: 

  • Transparent Parallelism 

With Hadoop, Data Scientists can write Java-based MapReduce code and use other big data tools in parallel. 

  • Data transport is easy 

Hadoop helps Data Scientists in transporting the data to different nodes on a system at a faster rate. 

  • Load data into Hadoop first 

The very first thing data scientists can do is to load data into Hadoop. For this, they need not do any transformations to get the data into the cluster. 

  • Easy data exploration 

With Hadoop, Data Scientists can easily explore and figure out the complexities in the data. 

  • Data Filtering 

Hadoop helps data scientists to filter a subset of data based on requirementsand address a specific business problem. 

  • Sampling for data modelling 

Sampling in Hadoop gives a hint to Data Scientists on what approach might work best for data modelling. 

Learn Hadoop Administration

As Hadoop is in great demand, those professionals who are seeking a career in Big Data would do well to add it to their resume. Learning Hadoop needs hard work and full dedication to the study. There are various sources available that you can refer to learn Hadoop. The sources include videos, blogs, tutorials, and books. If you want to learn Hadoop through hands-on learning, you can go for the Hadoop training that will help you to clear your every doubt while learning and working on the projects.        

There are several free or paid resources available in the market to learn the Hadoop Administration course. The following is a list of resources that you can refer to: 

No, knowledge of a programming language is not required to learn the Hadoop administration course. However, a strong knowledge of Linux is mandatory to undertake a Hadoop administration role in an organization.  

The simple answer to this is if you have a zeal to work in the Big Data industry as a Hadoop administrator, it is easy to learn. However, undergoing Hadoop administration training will help you gain practical knowledge on Hadoop including Hadoop modules such as HDFS, Map Reduce, Hive, HBase, Sqoop, Flume, Oozie, Yarn. Learning from experts with years of experience will help you to understand concepts with ease, and working on a project will aid you in building a solid foundation in Hadoop.      

You are required to be aware of the following skills or techniques to become a Hadoop Administrator: 

  • You should be able to deploy a Hadoop cluster, keep track of tasks, add or remove nodes, monitor clusters, etc. 
  • General operational skills that include good troubleshooting skills, understanding of system’s capacity, bottlenecks, basics of memory, CPU, OS, storage, and networks 
  • A strong understanding of Linux 
  • Basic knowledge of open-source configuration management and deployment tools such as Puppet or Chef and Linux scripting 
  • Should know core Java 
  • Highly proficient in Unix commands and Unix based File system 
  • Networking knowledge 

Training

The best training institutes to learn Hadoop Administration course are as follows. 

  • Edureka 
  • Udemy 
  • KnowledgeHut 
  • Cloudera 
  • Mindmajix 

KnowledgeHut is among the preferred coaching platforms for Hadoop Administration. The institute offers a clear and structured training on Hadoop Administration. Some of the benefits of choosing KnowledgeHut as your training provider are -  

  • It is an Instructor-led training course  
  • Industry renowned trainers 
  • Practical approach to learning  
  • Comprehensive training from basics to advanced concepts  
  • Case Study based learning  
  • Post-training mentoring 

Hadoop Admin professional course is not just limited to the IT industry. Any individual with a sound knowledge of Linux can be a part of the Hadoop Admin training. Here are the few steps to follow to become a Hadoop admin professional: 

  • Enrol for the Hadoop admin course from KnowledgeHut 
  • Take 30-hrs of live training from the Hadoop experts 
  • Take 60-hrs of MCQs assignments 
  • Work on 2 real-time projects to gain hands-on experience 
  • Earn course completion certificate from KnowledgeHut 

Upon successful completion of the Hadoop Administration certification training along with live sessions, practical case studies you will be awarded an industry-recognized course completion certificate from KnowledgeHut. 

The course completion Hadoop Administration Certificate from KnowledgeHut has lifetime validity. 

Career scope and Salary

Most of the companies are looking for candidates who can handle their requirements. Hadoop Administration training is the best way to demonstrate to your employer that you belong to the category of niche professionals who can make a difference. 

The demand for Hadoop in leading organizations has increased a lot, and today it is considered one of the most powerful versatile framework sources to opt for. There are multiple career opportunities in which you can make your mark across industries. You will be benefited with the following: 

  • Get an edge over other professionals 
  • Knowledge of Hadoop will enhance your salary prospects 
  • Get hired by leading corporates 
  • Plentiful job opportunities in a wide range of roles 

Today organizations need Hadoop administrators to take care of large Hadoop clusters. Top companies like Facebook, eBay, Twitter, etc are using Hadoop. The professionals with Hadoop skills are in huge demand. According to Payscale, the average salary for Hadoop Administrators is $121k.  

The Hadoop Administrator course is the right choice if you want to upgrade your data analytics skills. It is one of the best courses that provides you the practical as well as real-time industry experience. This course comes with lifetime validity. You can advance your big data skills which results in better job opportunities. By the end of the course, you will be able to get a clear understanding of the plan and deployment of a Hadoop Cluster, obtain an in-depth understanding of Apache Hadoop, HDFS, and Hadoop administration. 

The average Hadoop Admin salary in the USA is $110,000 per year or $56.41 per hour. Entry-level positions start at $78,000 per year, and the most experienced professionals can earn up to $175,939 per year. 

Big Data is everywhere! It has found uses across industries ranging from retail to politics to environmental issues. Most significantly it has been used to understand and target customers. Retailers are also using it with success to optimize their business processes. Big Data has also revolutionized the way healthcare operates and has helped huge advances to be made in the field of science and technology.With the increased adoption of Hadoop in the Big Data space, there is an ever-increasing demand for Hadoop Administrators in the market.  

The following are different types of companies that hire Hadoop Administrator Professionals: 

  • IBM 
  • Amazon 
  • Infosys 
  • Vodafone 
  • Data Labs 
  • Capgemini 
  • UnitedHealth Group 
  • Cognizant Softvision 

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