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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CURRICULUM & PROJECTS
Big Data Hadoop Training
- 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
- Overview of Course
- What is Big Data
- Big Data Analytics
- Challenges of Traditional System
- Distributed Systems
- Components of Hadoop Ecosystem
- Commercial Hadoop Distributions
- Why Hadoop
- Fundamental Concepts 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
- Deployment Types
- Installing Hadoop
- Specifying the Hadoop Configuration
- Performing Initial HDFS Configuration
- Performing Initial YARN and MapReduce Configuration
- Hadoop Logging
- 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 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 Running Jobs
- Scheduling Hadoop Jobs
- Configuring the Fair Scheduler
- Impala Query Scheduling
- Apache Sqoop
- Sqoop and Its Uses
- Sqoop Processing
- Sqoop Import Process
- Sqoop Connectors
- Importing and Exporting Data from MySQL to HDFS
- Apache Flume
- Flume Model
- Scalability in Flume
- Components in Flume’s Architecture
- Configuring Flume Components
- Ingest Twitter Data
- 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
- 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
- What is a Hadoop Client
- Installing and Configuring Hadoop Clients
- Installing and Configuring Hue
- Hue Authentication and Authorization
- Checking HDFS Status
- Copying Data between Clusters
- Adding and Removing Cluster Nodes
- Rebalancing the Cluster
- Cluster Upgrading
- 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
- General System Monitoring
- Monitoring Hadoop Clusters
- Common Troubleshooting Hadoop Clusters
- Common Misconfigurations
- General Planning Considerations
- Choosing the Right Hardware
- Network Considerations
- Configuring Nodes
- Planning for Cluster Management
- Advanced Configuration Parameters
- Configuring Hadoop Ports
- Explicitly Including and Excluding Hosts
- Configuring HDFS for Rack Awareness
- Configuring HDFS High Availability
- 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
- Introduction to Pig
- Components of Pig
- Pig Data Model
- Pig Interactive Modes
- Pig Operations
- Various Relations Performed by Developers
- 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
- NoSQL Databases HBase
- NoSQL Introduction
- HBase Overview
- HBase Architecture
- Data Model
- Connecting to HBase
- HBase Shell
- 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 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
- Hadoop and the Data Warehouse
- Hadoop Differentiators
- Data Warehouse Differentiators
- When and Where to Use Which
- 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
- 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
- The Combiner
- MapReduce Example: Word Count
- Word Count with Combiner
- Specifying a Combiner
- Demonstration: Writing and Implementing a Combiner
- Introduction
- Sorting
- Sorting as a Speed Test of Hadoop
- Shuffle and Sort in MapReduce
- Searching
- Secondary Sort: Motivation
- Implementing the Secondary Sort
- Secondary Sort: Example
- Indexing
- Inverted Index Algorithm
- Inverted Index: Data Flow
- Aside: Word Count
- Term Frequency Inverse Document Frequency (TF-IDF)
- TF-IDF: Motivation
- TF-IDF: Data Mining Example
- TF-IDF Formally Defined
- Computing TF-IDF
- 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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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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