- Introduction to Big Data & Big Data Challenges
- Limitations & Solutions of Big Data Architecture
- Hadoop & its Features
- Hadoop Ecosystem
- Hadoop 2.x Core Components
- Hadoop Storage: HDFS (Hadoop Distributed File System)
- Hadoop Processing: MapReduce Framework
- Different Hadoop Distributions
Big Data Hadoop Certification Training Course
To master the Big Data and Hadoop Ecosystem and the core associated concepts and tools such as Hive, Apache Pig, and ...Read more
Online
₹ 11999
Quick Facts
particular | details | ||||
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekends
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Course overview
Curated by Hadoop industry leaders, the Big Data Hadoop Certification Training course by Edureka will help you master the core tools of the Hadoop and Big Data Ecosystem. The course primarily focuses on different tools such as YARN, HDFS, Hive, Apache Pig, Apache Spark, SparkContext, Apache Oozie, HBase, Sqoop, and Flume.
The training programme will enable you to comprehend data ingestion capabilities in HDFS using Flume and Sqoop. You will also learn to analyse massive datasets that are stored in the Hadoop Distributed File System; learn to employ the best practices and industry standards for several real-life industry application projects. Besides, you will also have the opportunity to work on multiple Big Data projects during your training.
Moreover, the Big Data Hadoop Certification Training programme is crafted to help you become a certified Big Data professional by supplying you with valuable Hadoop Ecosystem hands-on training. You will become familiar with real-world use-cases in varying domains like social media, retail, travel and tourism, banking, telecommunication, and finance using Edureka’s Cloud Lab.
The highlights
- 60 days of access to Cloud Lab
- Live projects
- Live instructor-led training session
- Certificate of achievement from Edureka
- 24x7 technical support team
- Industry-based hands-on project
- Quiz assessments
- Community forum
- Lifetime LMS access
Program offerings
- Instructor-led live sessions
- Completion certificate from edureka
- Quiz assessment
- 24x7 online technical support
- Learners’ community forum
Course and certificate fees
Fees information
There are two components to the total fee of the Big Data Hadoop Certification Training programme by Edureka: the programme fee and GST. You can pay the programme fee in either lump sum or EMIs. A discount is also available on the course fee for a limited time.
Big Data Hadoop Certification Training Fee Structure
Head | Amount |
Original Price | Rs. 11,999 |
EMI starts at | Rs. 4,000 |
certificate availability
Yes
certificate providing authority
Edureka
Who it is for
The professionals who can benefit from the Big Data Hadoop Certification Training programme by Edureka include, but are not limited to:
- Software Developers
- Software Architects
- ETL Warehousing Professionals
- Data Warehousing Professionals
- Data Engineers
- Project Managers
- Business Intelligence Professionals
- Data Analysts
- Database Administrators
- Database professionals
- Experienced IT Professionals
- Testing professionals
- Professionals associated with Mainframe
- Graduates who want to pursue a career in Big Data or Data Science
Eligibility criteria
There are no prerequisites for the Big Data and Hadoop Certification Training course by Edureka. However, any previous experience of Core Java and SQL will be useful but not mandatory. Besides, once you register for the Big Data Hadoop Certification Training, Edureka also offers a free self-paced tutorial on "Java basics for Hadoop" to brush up your skills.
What you will learn
After the completion of the Edureka Big Data Hadoop Certification Training programme, you will become adept in the following skills:
- In-depth understanding of the Hadoop framework and all core concepts of the Hadoop Distributed File System (HDFS).
- Understand Yet Another Resource Negotiator (YARN) and master working with Hadoop resource management and storage.
- Learn to use and implement the MapReduce Framework to compounded business solutions.
- Learn to leverage Flume and Sqoop for data ingestion.
- Use Hive and Pig to perform data analysis and ETL operations.
- Be proficient in the implementation of indexing, bucketing, and partitioning in Hive.
- Master HBase integration with Hive, HBase mechanisms and architecture, and NoSQL DB in Hadoop.
- Learn to develop solutions for real-time Big Data challenges.
- Gain knowledge of the ecosystem of Apache Spark, Hadoop Cluster, and Oozie.
- Master implementation of best practises for Hadoop development.
The syllabus
Understanding Hadoop Certification
Hadoop Architecture and HDFS
- Hadoop 2.x Cluster Architecture
- Federation and High Availability Architecture
- Typical Production Hadoop Cluster
- Hadoop Cluster Modes
- Common Hadoop Shell Commands
- Hadoop 2.x Configuration Files
- Single Node Cluster & Multi-Node Cluster set up
- Basic Hadoop Administration
Hadoop MapReduce Framework
- Traditional way vs MapReduce way
- Why MapReduce
- YARN Components
- YARN Architecture
- YARN MapReduce Application Execution Flow
- YARN Workflow
- Anatomy of MapReduce Program
- Input Splits, Relation between Input Splits and HDFS Blocks
- MapReduce: Combiner & Partitioner
- Demo of Health Care Dataset
- Demo of Weather Dataset
Advanced Hadoop MapReduce
- Counters
- Distributed Cache
- MRunit
- Reduce Join
- Custom Input Format
- Sequence Input Format
- XML file Parsing using MapReduce
Apache Pig
- Introduction to Apache Pig
- MapReduce vs Pig
- Pig Components & Pig Execution
- Pig Data Types & Data Models in Pig
- Pig Latin Programs
- Shell and Utility Commands
- Pig UDF & Pig Streaming
- Testing Pig scripts with Punit
- Aviation use-case in PIG
- Pig Demo of Healthcare Dataset
Apache Hive
- Introduction to Apache Hive
- Hive vs Pig
- Hive Architecture and Components
- Hive Metastore
- Limitations of Hive
- Comparison with Traditional Database
- Hive Data Types and Data Models
- Hive Partition
- Hive Bucketing
- Hive Tables (Managed Tables and External Tables)
- Importing Data
- Querying Data & Managing Outputs
- Hive Script & Hive UDF
- Retail use case in Hive
- Hive Demo on Healthcare Dataset
Advanced Apache Hive and HBase
- Hive QL: Joining Tables, Dynamic Partitioning
- Custom MapReduce Scripts
- Hive Indexes and views
- Hive Query Optimizers
- Hive Thrift Server
- Hive UDF
- Apache HBase: Introduction to NoSQL Databases and HBase
- HBase v/s RDBMS
- HBase Components
- HBase Architecture
- HBase Run Modes
- HBase Configuration
- HBase Cluster Deployment
Advanced Apache HBase
- HBase Data Model
- HBase Shell
- HBase Client API
- Hive Data Loading Techniques
- Apache Zookeeper Introduction
- ZooKeeper Data Model
- Zookeeper Service
- HBase Bulk Loading
- Getting and Inserting Data
- HBase Filters
Processing Distributed Data with Apache Spark
- What is Spark
- Spark Ecosystem
- Spark Components
- What is Scala
- Why Scala
- SparkContext
- Spark RDD
Oozie and Hadoop Project
- Oozie
- Oozie Components
- Oozie Workflow
- Scheduling Jobs with Oozie Scheduler
- Demo of Oozie Workflow
- Oozie Coordinator
- Oozie Commands
- Oozie Web Console
- Oozie for MapReduce
- Combining flow of MapReduce Jobs
- Hive in Oozie
- Hadoop Project Demo
- Hadoop Talend Integration
Certification Project
Analyses of a Online Book Store
- Find out the frequency of books published each year. (Hint: Sample dataset will be provided)
- Find out in which year the maximum number of books were published
- Find out how many books were published based on ranking in the year 2002.
Sample Dataset Description
- The Book-Crossing dataset consists of 3 tables that will be provided to you.
Airlines Analysis
- Find list of Airports operating in Country India
- Find the list of Airlines having zero stops
- List of Airlines operating with codeshare
- Which country (or) territory having highest Airports
- Find the list of Active Airlines in United state
Sample Dataset Description
- In this use case, there are 3 data sets. Final_airlines, routes.dat, airports_mod.dat
Admission details
To enrol in the Big Data Hadoop Certification Training course by Edureka, follow these steps:
Step 1 - Visit the website of Edureka- https://www.edureka.co/
Step 2 – Search the "Big Data Hadoop Certification Training" course in the search bar on the website.
Step 3 – Locate the “Enrol now” tab on the top of the webpage.
Step 4 – You will be redirected to a new page to fill out the registration form, once you click on the "Enrol Now" button.
Step 5 - Next, you need to fill out the registration form. To apply for the course, you need to enter your contact details: phone number and email address
Step 6 – Finally, you need to choose the method of payment. Pay the applicable fee and save the receipt for future reference.
Filling the form
You will have to fill out an application form on the website to enrol in the Big Data Hadoop Certification Training course. As requested in the application form, you need to provide your contact information. You need to choose a payment mode and make the payment to confirm the application once you have filled out the details in the form.
Evaluation process
Applicants need to complete a certification project to implement the concepts taught in the training course. Candidates can mail the project to the support team of Edureka, within two weeks after the course completion. A group of experts will evaluate the project based on performance to provide a grade and award the certificate for the course.
How it helps
In the Big Data Hadoop Certification Training course, you will receive structured mentoring with an updated curriculum, based on the current industry demands and best practices. You will also have the guidance of a Hadoop professional who is currently working on real-world Big Data projects in the industry.
Besides, you will receive a certificate of accomplishment upon satisfactory completion of the Big Data Hadoop Certification Training programme. You will gain not only strong theoretical understanding but also get hands-on practical knowledge of real-world Big Data ventures using diverse Hadoop and Big Data tools.
Hadoop draws an array of possibilities to support your career to an unprecedented level. Businesses are increasingly looking for specialists who can interpret and use data to switch to Big Data. According to Forbes, the Hadoop market will reach $99.31 billion at a CAGR of around 42% by 2022. Hence, plenty of career prospects open for you after this Edureka training.
FAQs
Why should I learn Hadoop?
Certified Hadoop practitioners are one of the most highly paid professionals in the IT industry. And the market demand for Hadoop professionals has only increased furthermore. Thus, by taking the Big Data Hadoop Certification Training course by Edureka, you can improve your career prospects significantly.
How long does it take to master Hadoop?
Edureka Big Data Hadoop Certification Training course will help you learn the principles and practical implementations of the technology within 1 month. With committed resources and consistent efforts, you will master the technology in a month's time.
Who provides the course completion certificate?
Upon successful completion of the final course project, Edureka awards you a Big Data Expert Certificate.
How to access my course after enrolment?
When you sign up for the programme, you will receive the LMS login information instantly. You can log in to the system with these credentials to view all your lessons.
Who are the instructors for the Big Data Hadoop Certification Training?
Instructors at Edureka are experts with more than 10 years of experience, chosen after a rigorous selection process. In addition to technical expertise, we look for instructors who have passion and joy for teaching. Once shortlisted, the instructors also undertake a 3-month training programme.
Does Edureka Big Data Hadoop Certification Training offer a self-paced learning model?
No, the Big Data Hadoop Certification Training is a live instructor-led programme. You can opt for either a weekday batch or a weekend batch as per your convenience.