Hadoop Online Training

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Credo Systemz provides the best Hadoop certification online training with real-time Big Data Certified experts. It is a comprehensive Hadoop online training course designed by Big Data experts by current industry standards to help you learn Big Data Hadoop with real-time scenarios.

Credo Systemz’s Hadoop online classes have been created with a full focus on the real-time projects of Big Data Hadoop.

Big data Hadoop is a trending and highly valuable skill. This Hadoop online training will help you master in Big Data such as HDFS, Map Reduce, HBase, Hive, Pig, Sqoop, etc.,

About Hadoop Online Course

Hadoop is the most widely used open-source software apache framework that allows storing and running a big data applications with its components. It allows multiple tasks to run with a single server without any time delay. Important Hadoop framework components are,
  • HDFS
  • MapReduce
  • YARN
  • HBase
  • Oozie
  • Hive
  • Pig
  • Spark
Hadoop is used to store and process a large amount of data easily and most of the big IT companies uses Hadoop for storage purpose. So Hadoop job opportunities increasingly for many Hadoop positions. Also, Hadoop used big companies are Google, Yahoo, IBM, and eBay, etc.. If you learn Hadoop Training surely you get Job in one of the best MNC's.
Hadoop is an open-source, Java-based framework used for storing and processing big data. The data is stored on inexpensive product servers that run as clusters. Cafarella, Hadoop uses the MapReduce programming model for quicker storage and recovery of data from its nodes.
When to Use Hadoop
  • For Processing Really BIG Data.
  • For Storing a Diverse Set of Data.
  • For Parallel Data Processing.
  • For Real-Time Data Analysis.
  • For a Relational Database System.
  • For a General Network File System.
  • For Non-Parallel Data Processing.
  • Hadoop Distributed File System (HDFS).
Hadoop is not a mere framework in the Big Data world. It has a wide ecosystem with an umbrella of related technologies. For the same reason, a career in Hadoop is promising. If you have a good understanding of Hadoop fundamentals it will be a substance for great Career in Hadoop.

Key Features

Training from
Industrial Experts

24 x 7
Expert Support

Hands on
Practicals/ Projects

Certification
of Completion

100% Placement
Assistance

Free
Live Demo

HADOOP TRAINING COURSE CONTENT

Learning outcomes of our Hadoop Online Course:

  • You can gain knowledge in Hadoop functions and its components in the current trending technologies.
  • You can learn about imperative search concepts such as informed and uninformed search.
  • Well known about the logical proof, planning, and constraints satisfaction in Hadoop.
  • Finally, you will have the ability to apply Big Data Techniques for problem-solving and also to become a well-trained expert in Hadoop.
  • Further, Best practices in building, optimizing and debugging the Hadoop solutions.
  • We will conduct Hadoop Assessments and Mock Interview, so that we can evaluate candidate’s performance individually.
  • In conclusion, an Overall understanding of Big Data Hadoop and be equipped to clear Big Data Hadoop Certification.

Highlights of Our Hadoop Online Training:

  • Credo Systemz is one of the most prominent Hadoop training institutes that presents First Class Training in Chennai.
  • Conducted Hadoop Online Training with well Advanced Learning Program.
  • Well Experienced Trainers who are working in leading Top MNCs.
  • Shape your learning path with customized skills in Big Data Hadoop.
  • In addition, Guidance for Hadoop Developer Certification.
  • Get Practical Knowledge with Real-time Hands-on Projects.
  • Earn a Completion Certificate in Hadoop from Credo Systemz at the end of your training completion.

Course Features

  • Duration60 hours
  • Skill levelAll level
  • Batch Strength15
  • AssessmentsYes
  • Mock InterviewsYes
  • Resume BuildingYes
  • PlacementsYes
  • Flexible TimingYes
  • Fee InstallmentsYes
  • LanguageTamil/English
Section 1: INTRODUCTION TO BIG DATA-HADOOP
  • Overview of Hadoop Ecosystem
  • Role of Hadoop in Big data– Overview of other Big Data Systems
  • Who is using Hadoop
  • Hadoop integrations into Exiting Software Products
  • Current Scenario in Hadoop Ecosystem
  • Installation
  • Configuration
  • Use Cases ofHadoop (HealthCare, Retail, Telecom)
Section 2: HDFS
  • Concepts
  • Architecture
  • Data Flow (File Read , File Write)
  • Fault Tolerance
  • Shell Commands
  • Data Flow Archives
  • Coherency -Data Integrity
  • Role of Secondary NameNode
Section 3: MAPREDUCE
  • Theory
  • Data Flow (Map – Shuffle - Reduce)
  • MapRed vs MapReduce APIs
  • Programming [Mapper, Reducer, Combiner, Partitioner]
  • Writables
  • InputFormat
  • Outputformat
  • Streaming API using python
  • Inherent Failure Handling using Speculative Execution
  • Magic of Shuffle Phase
  • FileFormats
  • Sequence Files
Section 4: HBASE
  • Introduction to NoSQL
  • CAP Theorem
  • Classification of NoSQL
  • Hbase and RDBMS
  • HBASE and HDFS
  • Architecture (Read Path, Write Path, Compactions, Splits)
  • Installation
  • Configuration
  • Role of Zookeeper
  • HBase Shell  Introduction to Filters
  • RowKeyDesign -What's New in HBase  Hands On
Section 5: HIVE
  • Architecture
  • Installation
  • Configuration
  • Hive vs RDBMS
  • Tables
  • DDL
  • DML
  • UDF
  • Partitioning
  • Bucketing
  • Hive functions
  • Date functions
  • String functions
  • Cast function Meta Store
  • Joins
  • Real-time HQL will be shared along with database migration project
Section 6: PIG
  • Architecture
  • Installation
  • Hive vs Pig
  • Pig Latin Syntax
  • Data Types
  • Functions (Eval, Load/Store, String, DateTime)
  • Joins
  • UDFs- Performance
  • Troubleshooting
  • Commonly Used Functions
Section 7: SQOOP
  • Architecture , Installation, Commands(Import , Hive-Import, EVal, Hbase Import, Import All tables, Export)
  • Connectors to Existing DBs and DW
Real-time Practicals
  • SQOOP to import Real Time Weblogs from application to DB and try to export the same to MySQL
Section 8: KAFKA
  • Kafka introduction
  • Data streaming Introduction
  • Producer-consumer-topics
  • Brokers
  • Partitions
  • Unix Streaming via kafka
Real-time Practicals
    Kafka
  • Producer and Subscribers setup and publish a topic from Producer to subscriber
Section 9: OOZIE
  • Architecture
  • Installation
  • Workflow
  • Coordinator
  • Action (Mapreduce, Hive, Pig, Sqoop)
  • Introduction to Bundle
  • Mail Notifications
Section 10: HADOOP 2.0 and Spark
  • Limitations in Hadoop
  • 1.0 - HDFS Federation
  • High Availability in HDFS
  • HDFS Snapshots
  • Other Improvements in HDFS2
  • Introduction to YARN aka MR2
  • Limitations in MR1
  • Architecture of YARN
  • MapReduce Job Flow in YARN
  • Introduction to Stinger Initiative and Tez
  • BackWard Compatibility for Hadoop 1.X
  • Spark Fundamentals
  • RDD- Sample Scala Program- Spark Streaming
Real-time Practicals
  • Difference between SPARK1.x and SPARK2.x
  • PySpark program to create word count program in pyspark
Section 11: Big Data Use cases
  • Hadoop
  • HDFS architecture and usage
  • MapReduce Architecture and real time exercises
  • Hadoop Eco systems
  • Sqoop - mysql Db Migration
  • Hive. -- Deep drive
  • Pig - weblog parsing and ETL
  • Oozie - Workflow scheduling
  • Flume - weblogs ingestion
  • No SQL
  • HBase
  • Apache Kafka
  • Pentaho ETL tool integration & working with Hadoop eco system
  • Apache SPARK
  • Introduction and working with RDD.
  • Multinode Setup Guidance
  • Hadoop latest version Pros & cons discussion
  • Ends with Introduction of Data science.
Section 12: Real Time Project
  • Getting applications web logs
  • Getting user information from my sql via sqoop
  • Getting extracted data from Pig script
  • Creating Hive SQL Table for querying
  • Creating Reports from Hive QL

Click Stream Data Analytics Report Project

ClickStream Data

ClickStream data could be generated from any activity performed by the user over a web application. What could be the user activity over any website? For example, I am logging into Amazon, what are the activities I could perform? In a pattern, I may navigate through some pages; spend some time over certain pages and click on certain things. All these activities, including reaching that particular page or application, clicking, navigating from one page to another and spending time make a set of data. All these will be logged by a web application. This data is known as ClickStream Data. It has a high business value, specific to e-commerce applications and for those who want to understand their users’ behavior.

More formally, ClickStream can be defined as data about the links that a user clicked, including the point of time when each one of them were clicked. E-commerce businesses mine and analyse ClickStream data on their own websites. Most of the E-commerce applications have their built-in system, which mines all this information.


ClickStream Analytics

Using the ClickStream data adds a lot of value to businesses, through which they can bring many customers or visitors. It helps them understand whether the application is right, and the application experience of users is good or bad, based on the navigation patterns that people take. They can also predict which page you are most likely to visit next and can-do Ad Targeting as well. With this, they can understand the needs of users and come up with better recommendations. Several other things are possible using the ClickStream Data.


Project Scope

In this project candidates are given with sample click stream data which is taken from a web application in a text file along with problem statements.

  • Users information in MySQL database.
  • Click stream data in text file generated from Web application.

Each candidate has to come up with high level system architecture design based upon the Hadoop eco systems covered during the course. Each candidate has to table the High-level system architecture along with designed eco systems and pros and cons will be discussed with all the other candidates. Finally, will choose the best possible optimal system design approach for implementation.

Candidates are given instructions to create an oozie work flow with the respective Hadoop Eco systems finalized based on the discussion. Candidates has to submit the project for the given problem statement and this will be validated by the trainer individually before course completion.


ECO System involved in click stream analytics Project
HDFS, Sqoop, Pig, Hive, Oozie

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Our Best Hadoop online Training Program Schedule

Hadoop online Training program schedule - Credo Systemz

Top MNC Hadoop Interview Questions

  1. What is Fact Table and Dimension Table (When I said that I am aware of Dataware house concept)
  2. What type of data we should store in Fact table and dimension table?
  3. There is a string in a Hive column, how you will find the count of a character. For example, the string is “hdfstutorial”, then how to count number of ‘t’.
  4. There is a table in Hive, and the columns are student id, score and year. Find the top 3 students based on the score in each year.
  5. There is a table having 500 Million records. Now you want to copy the data of that table in some other table, what best approach you will choose.
  6. You have 10 tables, and there are certain join conditions you have to put and then the result needs to be updated in another table. How you will do it and what best practice you will follow
  7. Which all analytical functions you have used in Hive
  8. Why we use bucketing
  9. what is actually happening in bucketing and when we apply
  10. How bucketing is different from Partition and why we use it
  11. If you have a bucketed table then can you take those records to Sqoop directly
  1. What are the differences between Hadoop and Spark?
  2. What are the daemons required to run a Hadoop cluster?
  3. How will you restart a NameNode?
  4. Explain about the different schedulers available in Hadoop.
  5. List few Hadoop shell commands that are used to perform a copy operation.
  6. What is jps command used for?
  7. What are the important hardware considerations when deploying Hadoop in production environment?
  8. How many NameNodes can you run on a single Hadoop cluster?
  9. What happens when the NameNode on the Hadoop cluster goes down?
  10. What is the conf/hadoop-env.sh file and which variable in the file should be set for Hadoop to work?
  11. Apart from using the jps command is there any other way that you can check whether the NameNode is working or not.
  12. Which command is used to verify if the HDFS is corrupt or not?
  13. List some use cases of the Hadoop Ecosystem
  14. Which is the best operating system to run Hadoop?
  15. What are the network requirements to run Hadoop?
  16. What is the best practice to deploy a secondary NameNode?
  17. How often should the NameNode be reformatted?
  18. How can you add and remove nodes from the Hadoop cluster?
  19. Explain about the different configuration files and where are they located.
  20. What is the role of the namenode?
  1. What is serialization?
  2. How to remove the duplicate records from a hive table?
  3. How to find the number of delimiter from a file?
  4. Replace a certain word from a file using Unix?
  5. How to import a table without a primary key?
  6. What is cogroup in pig?
  7. How to write a UDF in Hive?
  8. How you can join two big tables in Hive?
  9. The difference between order by and sort by?
  1. What is rack awareness? And why is it necessary?
  2. What is the default block size and how is it defined?
  3. How do you get the report of hdfs file system? About disk availability and no.of active nodes?
  4. What is Hadoop balancer and why is it necessary?
  5. Difference between Cloudera and Ambari?
  6. What are the main actions performed by the Hadoop admin?
  7. What is Kerberos?
  8. What is the important list of hdfs commands?
  9. How to check the logs of a Hadoop job submitted in the cluster and how to terminate already running process?
  1. What Hadoop components will you use to design a Craiglist based architecture?
  2. Why cannot you use Java primitive data types in Hadoop MapReduce?
  3. Can HDFS blocks be broken?
  4. Does Hadoop replace data warehousing systems?
  5. How will you protect the data at rest?
  6. Propose a design to develop a system that can handle ingestion of both periodic data and real-time data.
  7. A folder contains 10000 files with each file having size greater than 3GB.The files contain users, their names and date. How will you get the count of all the unique users from 10000 files using Hadoop?
  8. File could be replicated to 0 Nodes, instead of 1. Have you ever come across this message? What does it mean?
  9. How do reducers communicate with each other?
  10. How can you backup file system metadata in Hadoop?
  11. What do you understand by a straggler in the context of MapReduce
  1. Why Hadoop? (Compare to RDBMS)
  2. What would happen if NameNode failed? How do you bring it up?
  3. What details are in the “fsimage” file?
  4. What is SecondaryNameNode?
  5. Explain the MapReduce processing framework? (start to end)
  6. What is Combiner? Where does it fit and give an example? Preferably from your project.
  7. What is Partitioner? Why do you need it and give an example? Preferably from your project.
  8. Oozie – What are the nodes?
  9. What are the actions in Action Node?
  10. Explain your Pig project?
  11. What log file loaders did you use in Pig?
  12. Hive Joining? What did you join?
  13. Explain Partitioning & Bucketing (based on your project)?
  14. Why do we need bucketing?
  15. Did you write any Hive UDFs?
  16. Filter – What did you filter out?
  17. HBase?
  18. Flume?
  19. Sqoop?
  20. Zookeeper?
  1. What is Hive variable
  2. What is Object inspector
  3. Please explain Consolidation in hive
  4. What are the differences between MapReduce and YARN
  5. Can you differentiate between Spark and MapReduce
  6. Explain RDD and data frames in spark
  7. Can you write the syntax for Sqoop import
  8. WHat do you know about Hive views
  9. Difference between Hive external table and Hive managed Table
  10. What are the differences between HBase and Hive
  11. What are Orderby, sortby, and clustered by
  12. What is Speculative execution
  13. Which all Alter column command in hive you have worked
  14. What is lazy evaluation in pig?
  15. What is dynamic partition and static partition in hive?
  16. What is the use of partitions and bucketing in hive?
  17. Explain the flow of MapReduce program?
  18. What is default partition in MapReduce and how can we override it?
  19. What is difference between key class and value class in MapReduce?
  20. What is the level of sub queries in hive?
  21. What is transformation and action in spark?
  1. What is heap error and how can you fix it?
  2. How many joins does MapReduce have and when will you use each type of join?
  3. What are sinks and sources in Apache Flume when working with Twitter data?
  4. How many JVMs run on a DataNode and what is their use?
  5. If you have configured Java version 8 for Hadoop and Java version 7 for Apache Spark, how will you set the environment variables in the basic configuration file?
  6. Differentiate between bash and basic profile.
  1. Garbage Collection in Java – How it works?
  2. Different Types of Comprassions in Hive?
  3. Job Properties in Oozie
  4. How do you ensure 3rparty Jar files are available in Data Nodes.
  5. How do you define and use UDF’s in Hive
  6. If we have 10GB and 10MB file, How do you load and process the 10 MB file in map-reduce
  7. What are Joins in Hive in Map-Reduce Paradigm
  8. Apart from Map-side and reduce side joins any other joins in map-reduce?
  9. What is Sort-merge-Bucketing?
  10. How do we test Hive in production?
  11. What is the difference between Hashmap and HashTable
  12. What is bucketing
  1. What are the differences between Hadoop and Spark?
  2.  What are the real-time industry applications of Hadoop?
  3. How is Hadoop different from other parallel computing systems?
  4. In what all modes Hadoop can be run?
  5. Explain the major difference between HDFS block and InputSplit.
  6. What is distributed cache? What are its benefits?
  7. Explain the difference between NameNode, Checkpoint NameNode, and Backup Node.
  8. What are the most common input formats in Hadoop?
  9. Define DataNode. How does NameNode tackle DataNode failures?
  10. What are the core methods of a Reducer?
  11. What is a SequenceFile in Hadoop?
  12. What is the role of a JobTracker in Hadoop?
  13. What is the use of RecordReader in Hadoop?
  14. What is Speculative Execution in Hadoop?
  15. How can you debug Hadoop code?
  1. How will you decide whether you need to use the Capacity Scheduler or the Fair Scheduler?
  2. What are the daemons required to run a Hadoop cluster?
  3. How will you restart a NameNode?
  4. Explain about the different schedulers available in Hadoop.
  5. List few Hadoop shell commands that are used to perform a copy operation.
  6. What is jps command used for?
  7. What are the important hardware considerations when deploying Hadoop in production environment?
  8. How many NameNodes can you run on a single Hadoop cluster?
  9. What happens when the NameNode on the Hadoop cluster goes down?
  10. What is the conf/hadoop-env.sh file and which variable in the file should be set for Hadoop to work
  11. Apart from using the jps command is there any other way that you can check whether the NameNode is working or not.
  12. Which command is used to verify if the HDFS is corrupt or not?
  13. List some use cases of the Hadoop Ecosystem
  14. I want to see all the jobs running in a Hadoop cluster. How can you do this?
  15. Is it possible to copy files across multiple clusters? If yes, how can you accomplish this?
  16. Which is the best operating system to run Hadoop?
  1. Explain Hadoop streaming?
  2. What is HDFS- Hadoop Distributed File System?
  3. What does hadoop-metrics.properties file do?
  4. How Hadoop’s CLASSPATH plays a vital role in starting or stopping in Hadoop daemons?
  5. What are the different commands used to startup and shutdown Hadoop daemons?
  6. What is configured in /etc/hosts and what is its role in setting Hadoop cluster?
  7. How is the splitting of file invoked in Hadoop framework?
  8. Is it possible to provide multiple input to Hadoop? If yes then how?
  9. Is it possible to have hadoop job output in multiple directories? If yes, how?
  10. Explain NameNode and DataNode in HDFS?
  11. Why is block size set to 128 MB in Hadoop HDFS?
  12. How data or file is written into HDFS?
  13. How data or file is read in HDFS?
  14. How is indexing done in HDFS?
  15. What is a Heartbeat in HDFS?
  16. Explain Hadoop Archives?
  1. Configure slots in Hadoop 2.0 and Hadoop 1.0.
  2. In case of high availability, if the connectivity between Standby and Active NameNode is lost. How will this impact the Hadoop cluster?
  3. What is the minimum number of ZooKeeper services required in Hadoop 2.0 and Hadoop 1.0?
  4. If the hardware quality of few machines in a Hadoop Cluster is very low. How will it affect the performance of the job and the overall performance of the cluster?
  5. How does a NameNode confirm that a particular node is dead?
  6. Explain the difference between blacklist node and dead node.
  7. How can you increase the NameNode heap memory?
  8. Configure capacity scheduler in Hadoop.
  9. After restarting the cluster, if the MapReduce jobs that were working earlier are failing now, what could have gone wrong while restarting?
  10. Explain the steps to add and remove a DataNode from the Hadoop cluster.
  11. In a large busy Hadoop cluster-how can you identify a long running job?
  12. When NameNode is down, what does the JobTracker do?
  13. When configuring Hadoop manually, which property file should be modified to configure slots?
  14. How will you add a new user to the cluster?
  15. What is the advantage of speculative execution? Under what situations, Speculative Execution might not be beneficial?
  1. What is Apache Hadoop?
  2. Why do we need Hadoop?
  3. What are the core components of Hadoop?
  4. What are the Features of Hadoop?
  5. Compare Hadoop and RDBMS?
  6. What are the modes in which Hadoop run?
  7. What are the features of Standalone (local) mode?
  8. What are the features of Pseudo mode?
  9. What are the features of Fully-Distributed mode?
  10. What are configuration files in Hadoop?
  11. What are the limitations of Hadoop?
  12. Compare Hadoop 2 and Hadoop 3?
  13. Explain Data Locality in Hadoop?
  14. What is Safemode in Hadoop?
  15. What is Safemode in Hadoop?
  16. What is a “Distributed Cache” in Apache Hadoop?
  17. How is security achieved in Hadoop?
  18. Why does one remove or add nodes in a Hadoop cluster frequently?
  19. What is throughput in Hadoop?
  20. How to restart NameNode or all the daemons in Hadoop?
  1. How will you initiate the installation process if you have to setup a Hadoop Cluster for the first time?
  2. How will you install a new component or add a service to an existing Hadoop cluster?
  3. If Hive Metastore service is down, then what will be its impact on the Hadoop cluster?
  4. How will you decide the cluster size when setting up a Hadoop cluster?
  5. How can you run Hadoop and real-time processes on the same cluster?
  6. If you get a connection refused exception - when logging onto a machine of the cluster, what could be the reason? How will you solve this issue?
  7. How can you identify and troubleshoot a long running job?
  8. How can you decide the heap memory limit for a NameNode and Hadoop Service?
  9. If the Hadoop services are running slow in a Hadoop cluster, what would be the root cause for it and how will you identify it?
  10. How many DataNodes can be run on a single Hadoop cluster?
Get Answer for all the above questions and place in your dream company

Hadoop Interview Questions and Answers

FAQs

Online session schedules will be flexible according to both trainees and trainers available timing. We have both weekend and weekday sessions available to learn according to your convenient timing.
Sure you can discuss with him at any when ever you have doubts. You will be having a separate Whatsapp group with your batch mates and trainers to reach them at any time.
In order to meet the need of every individual, we used to offer different batch schedules like the classroom, online, corporate training, and fast track sessions. You can book your batch according to your needs.
You can contact us via +91 9884412301 / 9600112302 reach us via the contact form to book your seat in the upcoming batch for your Hadoop Big data training.
Yes, You can. Credo Systemz offers to you for installment payment via Cash, Cheque, Card, and UPI services.
Yes, Our Big Data training program is designed with real-time projects, case studies, and practicals. So you will surely work on live projects during your training period. Also, it is suitable for both beginners and experienced professionals which enhances yourself to give the confidence to become a Big data expert.
Our Hadoop instructor having 15+ years of experience in the IT industry. They are currently working as Hadoop in top MNCs.
Graphical representation of our course journey given below,

Our Hadoop Trainer Profile

Our Hadoop instructor having 15+ years of experience in the IT industry. They are currently working as Hadoop in top MNCs.
  • More than 10 Years of experience in Big Data Hadoop Knowledge.
  • Has functioned on multiple real-time Hadoop projects.
  • Employed in a top MNC company in India.
  • Trained 1000+ Students so far.
  • Strong Theoretical & Practical Knowledge.
  • Certified Professionals with High Grade.
  • We have trainers that are specialists and they are certified.

Hadoop Certification Details

Credo Systemz Hadoop certification course helps you learn the Hadoop certification syllabus with the help of experts from top IT firms. Likewise, this course will guide you into the professional way to work on each and every component with practical and real-time scenarios based sessions. Similarly, Our expert level certified trainers will help you to gain the required skillset to clear the examination easily.
The Hadoop Developer certification details is given below,
Exam CodeExam Name
CCA175 CCA Spark and Hadoop Developer
CCA159 CCA Data Analyst
CCA131 CCA Administrator
DE575 CCP Data Engineer

Cloudera Certification Exam Information

Here you go with details about the Hadoop Certification Cost and other details.
Exam Details
No of Questions8 to 12 Hands-on tasks to be carried out on a Cloudera Enterprise Cluster
Duration120 minutes for candidates answering in English language.
Pass mark70%

Benefits of Our Hadoop Online Training

  • First of all, Hadoop Online classes will help you to learn all concepts of the Hadoop Framework which is basic to advanced concepts.
  • On begin, You can learn here from basic java concepts to Hadoop Frameworks.
  • In other words, You can attend the Free Online Demo class with our Big Data Experts
  • We are ranked as the Top 10 Big Data online certification training institute all over the world.
  • On the other hand, trainees those who attending our Hadoop online training will get the recorded video for complete course.
  • Providing Best Big Data Hadoop online training with Certification.

Big Data Hadoop is the top trending tools in Big Data industry. According to the Big Data survey, hadoop is the most used Big Data tool in the industry, its, growth increased more than expected ratio in the year of 2020.

 Hadoop Online course from Credo Systemz offers the job oriented and real time project oriented Big data certification course with maximum number of real time datas. More than 90% organization takes Big Data expert in a top priority.

Select a time that suits you and Get your Big Data Certification online training

Highlights of Hadoop online training

  • In short, Credo Systemz is ranked as the best Hadoop online course in India and referred by our alumni in Quora, Google, Facebook and other social mediums.
  • Big Data online course are handled by experts and experienced professionals via live online medium with practical and projects.
  • To begin with Apache Hadoop course content plays a major role and covers the essential and various features of Big Data Hadoop.
  • Initially our Hadoop training and placement online course covers the complete basics to assist the trainees the root concepts and includes the updated Apache Spark, Scala concepts as well.
  • Hadoop online training with projects is one important factor which hikes up the skill set of the every trainee to clear Big Data Certification easily.
  • In addition our Hadoop online training program includes the 100% placement assistance from our separate HR team.
  • As a matter of fact trainees completed our Big Data Hadoop online certification program has ranked us as the best online training institute in India.

Top Factors which makes us the Best Hadoop Online Training

  • Credo Systemz is ranked as the hadoop online training institute in Chennai with placement for both Velachery and OMR, according to the more number of positive reviews across the internet.
  • Most Importantly hadoop training online course in Chennai velachery and OMR is handled by hadoop Professional Level Certified Trainers.
  • In addition, we are providing the Online and Corporate Hadoop Training on tailor-made fees structure.
  • For the most part, Our Hadoop Course Syllabus suits for both Beginners and Experienced Professional to enhance their skills.
  • Our Hadoop Instructor has more than 12+ years of Industry experience. As a result, you can get updated and learn latest hadoop Topics.
  • During the hadoop online course you will get fully hands-on experience in real-time projects which boost the confidence level in aspirants to face the real-time challenges successfully.
  • We will conduct hadoop Assessments and Mock Interview, so that we can evaluate candidate’s performance individually.
  • Also, we will guide you to complete hadoop online training in chennai which will help you to stand out in the market.
  • In addition, our best hadoop online training you can also attend our free hadoop workshops and discuss with our consultant to know about the topics, case studies and real-time Hadoop projects that is included in this training program.
  • Consequently you will receive Job alerts to your registered email and whatsapp from our placement team and also we are doing hadoop online course chennai in various ways.

Related Trainings

Big Data Hadoop Developer career opportunities

Big Data Hadoop market report shares there will be significant growth in the year of 2020. The global market share of Hadoop has been increased all over the world including Asia, America, Europe, the Middle East, this results in more number of company growth and increase in the need for Hadoop Developers.
Big data Hadoop career opportunities
As an individual having Hadoop knowledge is very much required, Hadoop has also been listed as one of the important skillsets to have in 2020 according to Forbes 2020. Graphical representation of Hadoop Job opportunities given below,

Hadoop Developer Job Roles

There are various job roles are available in Big Data domain, these are
  • Business Analyst
  • Big Data Engineer
  • Data Analyst
  • Hadoop Developer
  • Hadoop Admin
  • Database developer
  • Hadoop Tester
  • Machine Learning Engineer
  • Data Scientist
Nearby Access Areas
Our Velachery and OMR branches are very nearby access to the below locations.
Medavakkam, Adyar, Tambaram, Adambakkam, OMR, Anna Salai, Velachery, Ambattur, Ekkattuthangal, Ashok Nagar, Poonamallee, Aminjikarai, Perambur, Anna Nagar, Kodambakkam, Besant Nagar, Purasaiwakkam, Chromepet, Teynampet, Choolaimedu, Madipakkam, Guindy, Navalur, Egmore, Triplicane, K.K. Nagar, Nandanam, Koyambedu, Valasaravakkam, Kilpauk, T.Nagar, Meenambakkam, Thiruvanmiyur, Nungambakkam, Thoraipakkam, Nanganallur, St.Thomas Mount, Mylapore, Pallikaranai, Pallavaram, Porur, Saidapet, Virugambakkam, Siruseri, Perungudi, Vadapalani, Villivakkam, West Mambalam, Sholinganallur.
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