Master the key concepts of Hadoop and Big data. Join and learn from a Big Data/Hadoop expert.
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Corporate Served- Big Data Hadoop as the name implies, is an open-source utility software that helps to handle a large amount of data and possesses immense processing power. The USP of Big Data Hadoop is its ability to manage unlimited data simultaneously. Data analytics rely on the Big Data Hadoop platform because they are quite simple, fast, and flexible.
- Our Big Data Hadoop online training at Croma Campus is crafted by our team of experts to cater to the individual needs of the learners. It infuses detailed knowledge of Big Data Hadoop features like HDFS, YARN, Hive, Map Reduce, Pig, Spark, HBase, Sqoop, Flume, Oozie, and Hive, etc, to its learners. Get the benefit to work on real-life industry cases through our extensive Big Data Hadoop Online Training.
- Big Data Hadoop has witnessed a surge in its demand across the IT domain. Having a requisite skillset in handling Big Data using Hadoop gives you an upper hand over others seeking to enter the IT domain. Some of the popular Big Data job titles are Big Data Hadoop – Developer, Administrator, Data Analyst, Tester, and Solution Architect.
Big Data Hadoop Online Training
- The main objective of our Big Data Hadoop training and certification program online is to make you an expert in Big Data Hadoop learning skills. Here are a few of the skills you will be learning in our training course:
You will get to master all the basics of Big Data Hadoop, YARN, Map Reduce, and become an expert in writing apps using the mentioned tools.
Our Big Data Hadoop online training institute in India inculcates deep knowledge of HDFS, Sqoop, Pig, Hive, Oozie, shell scripting, Spark, Flume, Zookeeper online.
With the leading Big data Hadoop online training in India, you will acquire a clear understanding of the Big Data Hadoop cluster and learn Big Data Hadoop analytics as well.
Learn to create various ETL tools and know about set the pseudo nodes too.
With the Big data Hadoop placement training online, get hands-on experience through our real-life projects and assignments.
- According to a recent study by Indeed, the salary of a Big Data Hadoop Developer is expected to range between $119,250 to $168,250 per annum and approx. $110,000 per year for a Big Data Hadoop Admin.
- The average salary of Big Data Hadoop professionals across the world is:
- Here are some facts about Big Data Hadoop that might provide you reliable insights about the domain:
- According to Mckinsey, there will be a shortfall of skilled analysts and managers in near future and hence it will be a really great opportunity for you in the desired field. Hence enroll in our Big Data Hadoop certification course and pave your way towards an enormous career opportunity.
Big Data Hadoop Analyst - $110K
Big Data Hadoop Administrator - $125K
Big Data Hadoop Developers - $135K
Big Data Hadoop Architect - $170K
Big Data Hadoop Analytics is the most desirable data analytic tool.
It enhances the efficiency of an organization.
Big Data Hadoop Analytic tools are utilized to get better insights into their sales and marketing facilities.
Big data Hadoop is boosting business processes by marketing it on the social media platform.
The requirement of certified Big data Hadoop professionals is high as there are very few skilled analytical professionals available in the market.
- There is without a doubt enormous career opportunity in the Big Data Hadoop domain:
Backed by our experts and real-time sessions, the Big Data Hadoop training course offers a comprehensive knowledge of Big Data Hadoop, Big Data Hadoop certifications, and the current market trends in the relevant field.
Our course curriculum is the perfect blend of theoretical as well as practical components.
Big Data Hadoop online training session delivers Big Data framework, Storage & Processing, Sqoop, Pig, Hive, Oozie, Shell scripting, Spark detailed sessions in a practical way so that the learners can easily grasp the subject. It also offers live sessions, provides study material, PPT, projects, etc.
Upon completing the Big Data Hadoop certification training program, you will directly qualify for the next level certification and thereafter establish as a Big Data Hadoop expert.
- Big Data Hadoop online training has become more and more popular over the years as most of the companies are shifting to the Big Data Hadoop system. Due to the flexible nature of Big Data Hadoop, it is able to control the overall system and store data in HDFS and supports data compression. Big Data can be installed using tools such as Map Reduce, Pig, and Hive.
- According to a survey, it is predicted that the Big Data Hadoop market will rise up to $99.31 by 2022. There will be a shortage of certified Big Data Hadoop skilled experts around 1.6 million in the US alone. Almost every premium company has adopted the Big Data Hadoop system.
- If you are trained in the niche technology at one of the leading Big Data Hadoop online training institute in India, you will get to learn at your own pace and comfort Zone, leverage the benefits of interactive training sessions. With Instructor-led Big Data Hadoop classes get cost-effective personalized training.
- Needless to say that Big Data Hadoop platform seems promising and it will keep on progressing in the years to come by.
- Big Data Hadoop online training professionals are responsible for the following job roles and responsibilities that are covered as a part of our Big Data Hadoop online training program:
Get proficient in conducting database modeling and development, data mining, and warehousing.
Should be able to develop, implement and maintain Big Data solutions.
Should be an expert in designing and deploying data platforms across multiple domains ensuring operability.
Must have hands-on expertise in transforming data for meaningful analyses, improving data efficiency, reliability & quality, creating data enrichment, building high performance, and ensuring data integrity.
Must have sufficient experience working with the Big Data Hadoop ecosystem (HDFS, MapReduce, Oozie, Hive, Impala, Spark, Kerberos, KAFKA, etc.).
Must know all about Spark core, HBase or Cassandra, Pig, Yarn, SQL, MongoDB, RDBMS, DW/DM, etc.
Need to play a crucial role in the development and deployment of innovative big data platforms for advanced analytics and data processing.
- After completing Big Data Hadoop online training in India developer is one of the most preferred choices. Almost all companies have started accepting the Big Data ecosystem making Big Data Hadoop professionals even more alluring. Some of the top industries using and thus hiring Big Data experts are Infosys, Accenture, IBM, Wipro, TCS, Cognizant, HCL, Dell, etc.
- Indeed, Big Data Hadoop analytics would be the best career option for you. Furthermore, the high demand for Data Analytics skills is boosting the salary for qualified professionals.
- Since organizations have acknowledged the benefits of Big Data Hadoop online training. Hence, the demand for jobs in Big Data Hadoop is also increasing rapidly. To seize this opportunity individuals need to take proper training from our Big Data Hadoop online training institute in India and clear the certification exam expeditiously.
- Once you complete the training program at Big Data Hadoop online training in India, you will become an authorized Developer, Administrator, Data Analyst, Tester, or Solution Architect. Thus, if you are interested to pursue your career in this field, then this is the apt time to enroll in our Big Data Hadoop placement course online and savor a remarkable career ahead.
Why you should learn Big Data Hadoop?
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Big Data Hadoop Training
- Croma Campus offers the best Hadoop development Training in Noida with most experienced professionals. Our Instructors are working in Big Data Space and related technologies for years in MNC's.
- We aware of industry needs and we are offering Hadoop development Training in more practical way. Our team of Hadoop trainers offers the in-classroom training with best industry practices.
- We framed our syllabus to match with the real-world requirements for beginner level to advanced level. Our training will be handled in either weekday or weekends programme depends on participants requirements.
- In this program you will learn:
Introduction to Big Data & Hadoop
HDFS
YARN
Managing and Scheduling Jobs
Apache Sqoop
Apache Flume
Getting Data into HDFS
Apache Kafka
Hadoop Clients
Cluster Maintenance
Cloudera Manager
Cluster Monitoring and Troubleshooting
Planning Your Hadoop Cluster
Advanced Cluster Configuration
MapReduce Framework
Apache PIG
Apache HIVE
No SQL Databases HBase
Functional Programming using Scala
Apache Spark
Hadoop Datawarehouse
Writing MapReduce Program
Introduction to Combiner
Problem-solving with MapReduce
- Introduction to Big Data
Overview of Course
What is Big Data
Big Data Analytics
Challenges of Traditional System
Distributed Systems
- Introduction to Hadoop
Components of Hadoop Ecosystem
Commercial Hadoop Distributions
Why Hadoop
Fundamental Concepts in Hadoop
- Security in Hadoop
Why Hadoop Security Is Important
Hadoop’s Security System Concepts
What Kerberos Is and How it Works
Securing a Hadoop Cluster with Kerberos
- Initial Setup and Configuration
Deployment Types
Installing Hadoop
Specifying the Hadoop Configuration
Performing Initial HDFS Configuration
Performing Initial YARN and MapReduce Configuration
Hadoop Logging
- HDFS
What is HDFS
Need for HDFS
Regular File System vs HDFS
Characteristics of HDFS
HDFS Architecture and Components
High Availability Cluster Implementations
HDFS Component File System Namespace
Data Block Split
Data Replication Topology
HDFS Command Line
- YARN
Yarn Introduction
Yarn Use Case
Yarn and its Architecture
Resource Manager
How Resource Manager Operates
Application Master
How Yarn Runs an Application
Tools for Yarn Developers
- Managing and Scheduling Jobs
Managing Running Jobs
Scheduling Hadoop Jobs
Configuring the Fair Scheduler
Impala Query Scheduling
- Apache Sqoop
Apache Sqoop
Sqoop and Its Uses
Sqoop Processing
Sqoop Import Process
Sqoop Connectors
Importing and Exporting Data from MySQL to HDFS
- Apache Sqoop
Apache Flume
Flume Model
Scalability in Flume
Components in Flume’s Architecture
Configuring Flume Components
Ingest Twitter Data
- Getting Data into HDFS
Data Ingestion Overview
Ingesting Data from External Sources with Flume
Ingesting Data from Relational Databases with Sqoop
REST Interfaces
Best Practices for Importing Data
- Apache Kafka
Apache Kafka
Aggregating User Activity Using Kafka
Kafka Data Model
Partitions
Apache Kafka Architecture
Setup Kafka Cluster
Producer Side API Example
Consumer Side API
Consumer Side API Example
Kafka Connect
- Hadoop Clients
What is a Hadoop Client
Installing and Configuring Hadoop Clients
Installing and Configuring Hue
Hue Authentication and Authorization
- Cluster Maintenance
Checking HDFS Status
Copying Data between Clusters
Adding and Removing Cluster Nodes
Rebalancing the Cluster
Cluster Upgrading
- Cloudera Manager
The Motivation for Cloudera Manager
Cloudera Manager Features
Express and Enterprise Versions
Cloudera Manager Topology
Installing Cloudera Manager
Installing Hadoop Using Cloudera Manager
Performing Basic Administration Tasks using Cloudera Manager
- Cluster Monitoring and Troubleshooting
General System Monitoring
Monitoring Hadoop Clusters
Common Troubleshooting Hadoop Clusters
Common Misconfigurations
- Planning Your Hadoop Cluster
General Planning Considerations
Choosing the Right Hardware
Network Considerations
Configuring Nodes
Planning for Cluster Management
- Advanced Cluster Configuration
Advanced Configuration Parameters
Configuring Hadoop Ports
Explicitly Including and Excluding Hosts
Configuring HDFS for Rack Awareness
Configuring HDFS High Availability
- MapReduce Framework
What is MapReduce
Basic MapReduce Concepts
Distributed Processing in MapReduce
Word Count Example
Map Execution Phases
Map Execution Distributed Two Node Environment
MapReduce Jobs
Hadoop MapReduce Job Work Interaction
Setting Up the Environment for MapReduce Development
Set of Classes
Creating a New Project
Advanced MapReduce
Data Types in Hadoop
Output formats in MapReduce
Using Distributed Cache
Joins in MapReduce
Replicated Join
- Apache PIG
Introduction to Pig
Components of Pig
Pig Data Model
Pig Interactive Modes
Pig Operations
Various Relations Performed by Developers
- Apache HIVE
Introduction to Apache Hive
Hive SQL over Hadoop MapReduce
Hive Architecture
Interfaces to Run Hive Queries
Running Beeline from Command Line
Hive Meta Store
Hive DDL and DML
Creating New Table
Data Types
Validation of Data
File Format Types
Data Serialization
Hive Table and Avro Schema
Hive Optimization Partitioning Bucketing and Sampling
Non-Partitioned Table
Data Insertion
Dynamic Partitioning in Hive
Bucketing
What Do Buckets Do
Hive Analytics UDF and UDAF
Other Functions of Hive
- No SQL Databases HBase
NoSQL Databases HBase
NoSQL Introduction
HBase Overview
HBase Architecture
Data Model
Connecting to HBase
HBase Shell
- Functional Programming using Scala
Basics of Functional Programming and Scala
Introduction to Scala
Scala Installation
Functional Programming
Programming with Scala
Basic Literals and Arithmetic Programming
Logical Operators
Type Inference Classes Objects and Functions in Scala
Type Inference Functions Anonymous Function and Class
Collections
Types of Collections
Operations on List
Scala REPL
Features of Scala REPL
- Apache Spark
Apache Spark Next-Generation Big Data Framework
History of Spark
Limitations of MapReduce in Hadoop
Introduction to Apache Spark
Components of Spark
Application of In-memory Processing
Hadoop Ecosystem vs Spark
Advantages of Spark
Spark Architecture
Spark Cluster in Real World
- Data warehouse in Hadoop
Hadoop and the Data Warehouse
Hadoop Differentiators
Data Warehouse Differentiators
When and Where to Use Which
- Augmenting Enterprise Data Warehouse
Introduction
RDBMS Strengths
RDBMS Weaknesses
Typical RDBMS Scenario
OLAP Database Limitations
Using Hadoop to Augment Existing Databases
Benefits of Hadoop
Hadoop Trade-offs
- Advance Programming in Hadoop
Advance Programming in Hadoop
- Writing MapReduce Program
A Sample MapReduce Program: Introduction
Map Reduce: List Processing
MapReduce Data Flow
The MapReduce Flow: Introduction
Basic MapReduce API Concepts
Putting Mapper & Reducer together in MapReduce
Our MapReduce Program: Word Count
Getting Data to the Mapper
Keys and Values are Objects
What is Writable Comparable
Writing MapReduce application in Java
The Driver
The Driver: Complete Code
The Driver: Import Statements
The Driver: Main Code
The Driver Class: Main Method
Sanity Checking the Job’s Invocation
Configuring the Job with Job Conf
Creating a New Job Conf Object
Naming the Job
Specifying Input and Output Directories
Specifying the Input Format
Determining Which Files to Read
Specifying Final Output with Output Format
Specify the Classes for Mapper and Reducer
Specify the Intermediate Data Types
Specify the Final Output Data Types
Running the Job
Reprise: Driver Code
The Mapper
The Mapper: Complete Code
The Mapper: import Statements
The Mapper: Main Code
The Map Method
The map Method: Processing the Line
Reprise: The Map Method
The Reducer
The Reducer: Complete Code
The Reducer: Import Statements
The Reducer: Main Code
The reduce Method
Processing the Values
Writing the Final Output
Reprise: The Reduce Method
Speeding up Hadoop development by using Eclipse
Integrated Development Environments
Using Eclipse
Writing a MapReduce program
- Introduction to Combiner
The Combiner
MapReduce Example: Word Count
Word Count with Combiner
Specifying a Combiner
Demonstration: Writing and Implementing a Combiner
- Sorting & Searching large data sets
Introduction
Sorting
Sorting as a Speed Test of Hadoop
Shuffle and Sort in MapReduce
Searching
- Performing a secondary sort
Secondary Sort: Motivation
Implementing the Secondary Sort
Secondary Sort: Example
- Indexing data and inverted Index
Indexing
Inverted Index Algorithm
Inverted Index: Data Flow
Aside: Word Count
- Term Frequency - Inverse Document Frequency (TF- IDF)
Term Frequency Inverse Document Frequency (TF-IDF)
TF-IDF: Motivation
TF-IDF: Data Mining Example
TF-IDF Formally Defined
Computing TF-IDF
- Calculating Word co- occurrences
Word Co-Occurrence: Motivation
Word Co-Occurrence: Algorithm
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FAQ's
Croma Campus is one of the excellent Big Data Hadoop Online Training Institute in India that offers hands-on practical knowledge, practical implementation on live projects and will ensure the job with the help of Big Data Hadoop Online course, Croma Campus provides Big Data Hadoop Online Training by industrial experts, they have 8+ years working experience in top organization.
Croma Campus associated with top organizations like HCL, Wipro, Dell, BirlaSoft, Tech Mahindra, TCS, IBM, etc. make us capable to place our students in top MNCs across the globe. Our training curriculum is approved by our placement partners.
Croma Campus in India mentored more than 3000+ candidates with Big Data Hadoop Online Certification Training in India at a very reasonable fee. The course curriculum is customized as per the requirement of candidates/corporates. You will get study material in the form of E-Books, Online Videos, Certification Handbooks, Certification and 500 Interview Questions along with Project Source material.
For details information & FREE demo class, call us at 120-4155255, +91-9711526942 or write to us info@cromacampus.com
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WHAT OUR ALUMNI SAYS ABOUT US
Sachin Tyagi
Big Data Hadoop
Thanks for making this wonderful platform available. I would love to encourage more people to join Croma Learning Campus to fill the gap for their career needs. I took Big Data Hadoop Training from Croma and I must say that course content is just the great and well-structured as per the certificatio Read more...
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