Hadoop Certification Training Online
40 Hours
24/7 Digital Library Access
2765 Total Learners
30% Off
Instructor-led Online Training
Interactive Live training
Real Time, Certified, Expert Trainers
Job oriented & Industry ready curriculum
Free Course Access for 365 Days
Fast-track / Regular / Weekend
Recorded Video Online Training
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Certified & Industry Experts Trainers
Email & Forum support for 365 days
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Multi Instructor sessions
Learn Hadoop Online training
What is Hadoop Online Training
By attending our Big Data Hadoop training course, you gain expertise in the four modules of the basic framework from the Apache Foundation: MapReduce concepts, Hadoop Distributed File System (HDFS), along with other software components like Yet Another Resource Negotiator (YARN), Hadoop Common, Ambari, Cassandra, Flume, HBase, HCatalog, Hive, Oozie, Pig, Solr, Spark, Sqoop, Zookeeper, which run alongside Hadoop. All these concepts would be explained in our Hadoop tutorials with real-time scenarios that can be applied in different business domains such as Finance, Social media, Healthcare, Retail, Telecom, Manufacturing, IoT and the like.
What is Big Data?
Big Data is a term used to refer to data sets with voluminous amount of structured, semi-structured, and unstructured data. This data can be from multiple sources and of different varieties. Since this data is to be collected from different sources and is in huge volumes, it becomes difficult to collect store, analyze, transfer, and update it.This is where new technologies like Hadoop come in handy to make our lives easier.
What is Hadoop?
Hadoop is an open source framework, distributed by Apache, with set of projects and programs that helps in analyzing and processing Big Data.Hadoop has a lot of impressing features some of which are:
- Huge storage for a variety of data
- High efficiency in data processing
- Data need not be pre-processed
- Since it open source, it is free for practically anyone
Advantages of Big Data
Companies capture data from different sources, filter it for information relevant for their business and then perform Big Data analytics on the filtered data to gain insights that help them grow their customer reach. AS they say, it is not what you know, it is what you do with what you know.Analysis of Big Data collected from social media and web searches helps in optimizing business processes, enhances decision making, developing new strategies thereby creating more opportunities to gain new customers and serve existing customers in a better way.
New surveys show that 62.5% of the Fortune 1000 companies reported using Big Data analyticsacross their business. The number of firms that project investments in Big Data of greater than $50 million leaps to 26.8% by 2017(survey source: dezyre.com).
Why Big Data and Hadoop?
Since it is open source, Hadoop, as a data management platform, is accessible to anyone and everyone in who wish to use it. Using the core concepts of Hadoop (MapReduce, HDFS, YARN, and Hadoop Common, many young organizations alongside the tech giants are offering Hadoop services.
Industries are always in search of methods to improve their business using the data available. This calls for a constant requirement for professionals with a technical hands-on expertise with Big Data analysis. This is where Big Data Hadoop training becomes an essential step to reach industry standards.
The Hadoop market is forecast to grow at a compound annual growth rate (CAGR) 58% surpassing $16 billion by 2020 (source: marketanalysis.com).
Who Can Learn
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
- Software Developers and Architects
- Analytics Professionals
- Senior IT professionals
- Testing and Mainframe professionals
- Data Management Professionals
- Business Intelligence Professionals
- Graduates looking to build a career in Big Data Analytics
Prerequisite
- As the knowledge of Java is necessary for this course, we are providing a complimentary access to “Java Essentials for Hadoop”
course - Knowledge of an operating system like Linux is useful for the course
Hadoop Course Curriculum
Duration: 40 Hours
- Understand Big Data
- Limits of traditional systems
- Big Data vs. EDW
- Big Data vs. Cloud
- Big Data vs. HPC
- Why Hadoop (Introduction)
- Brief history
- Concepts of distributed file system
- Hadoop eco system
- Hadoop alternatives
- Scenarios
- Hadoop distributed file system (HDFS)
- Hadoop core daemons
- Hadoop Map Reduce Framework
- Hand shake of core components
- Job scheduling logic
- In-depth into Mappers, Reducers, sorting and shuffling
- File read and write semantics
- Bulk operations
- Hands-on & Assignments
- Apache Hive
- Hive Hands-on
- Apache Pig
- Pig Hands-on
- Apache HBase
- HBase hands-on
- Apache Scoop
- Scoop hands-on
- Apache Flume
- Apache Hue
- Apache Mahout
- Apache Oozie
- Apache Ambari
- Hands-on & Assignments
- Hive with Pig
- Hive with HBase
- Pig with HBase
- Scoop with Hive
- Scoop with HBase
- Python integration
- Hands-on & Assignments
- Challenges in Hadoop 1.x
- Name node high availability
- HDFS Federation
- Resource Manager – YARN
- Node Manager
- App Master
- Hands-on & Assignments
- Refresh on Unix/Linux commands
- Planning for Hadoop cluster
- Hardware and Software considerations
- Setting up a standalone system
- Setting up a pseudo distributed system
- Hadoop daemon addresses and ports
- Managing Jobs
- Types of Schedulers in Hadoop
- Configuring scheduler and run a job
- Cluster monitoring and trouble shooting
Frequently asked questions
period of 365 days from the day of enrolment.
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