Edureka’s Big Data Hadoop online training is designed to help you become a top Hadoop developer.
During this course, our expert instructors will help you:
- Master the concepts of HDFS and MapReduce framework
- Understand Hadoop 2.x Architecture
- Setup Hadoop Cluster and write Complex MapReduce programs
- Learn data loading techniques using Sqoop and Flume
- Perform data analytics using Pig, Hive, and YARN
- Implement HBase and MapReduce integration
- Implement Advanced Usage and Indexing
- Schedule jobs using Oozie
- Implement best practices for Hadoop development
- Work on a real-life Project on Big Data Analytics
- Understand Spark and its Ecosystem
- Learn how to work in RDD in Spark
Who should go for this Hadoop Course?
The market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals.
Here are the few Professional IT groups, who are continuously enjoying the benefits moving into Big data domain:
- Developers and Architects
- BI /ETL/DW professionals
- Senior IT Professionals
- Testing professionals
- Mainframe professionals
Why learn Big Data and Hadoop?
- Big Data & Hadoop Market is expected to reach $99.31B by 2022 growing at a CAGR of 42.1% from 2015 Forbes
- McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts Mckinsey Report
- Avg salary of Big Data Hadoop Developers is $135k Indeed.com Salary Data
What are the pre-requisites for the Hadoop Course?
As such, there are no pre-requisites for learning Hadoop. Knowledge of Core Java and SQL will be beneficial, but certainly not a mandate. If you wish to brush-up Core-Java skills, Edureka offers you a complimentary self-paced course, i.e. "Java essentials for Hadoop" when you enroll in Big Data Hadoop Certification course.
How will I do practicals in Online Training?
For practicals, we will help you to setup Edureka's Virtual Machine in your System with local access. The detailed installation guide will be present in LMS for setting up the environment. In case, your system doesn't meet the pre-requisites e.g. 4GB RAM, you will be provided remote access to the Edureka cluster for doing practical. For any doubt, the 24*7 support team will promptly assist you. Edureka Virtual Machine can be installed on Mac or Windows machine and the VM access will continue even after the course is over so that you can practice.
Towards the end of the course, you will work on a live project where you will be using PIG, HIVE, HBase, and MapReduce to perform Big Data analytics. Following are a few industry-specific Big Data case studies that are included in our Big Data and Hadoop Certification e.g. Finance, Retail, Media, Aviation etc. which you can consider for your project work:
Project #1: Analyze social bookmarking sites to find insights
Industry: Social Media
Data: It comprises of the information gathered from sites like reddit.com, stumbleupon.com which are bookmarking sites and allow you to bookmark, review, rate, search various links on any topic.reddit.com, stumbleupon.com, etc. A bookmarking site allows you to bookmark, review, rate, search various links on any topic. The data is in XML format and contains various links/posts URL, categories defining it and the ratings linked with it.
Problem Statement: Analyze the data in the Hadoop ecosystem to:
- Fetch the data into a Hadoop Distributed File System and analyze it with the help of MapReduce, Pig, and Hive to find the top rated links based on the user comments, likes etc.
- Using MapReduce, convert the semi-structured format (XML data) into a structured format and categorize the user rating as positive and negative for each of the thousand links.
- Push the output HDFS and then feed it into PIG, which splits the data into two parts: Category data and Rating data.
- Write a fancy Hive Query to analyze the data further and push the output is into a relational database (RDBMS) using Sqoop.
- Use a web server running on grails/java/ruby/python that renders the result in real time processing on a website.
Project #2: Customer Complaints Analysis
Data: Publicly available dataset, containing a few lakh observations with attributes like; CustomerId, Payment Mode, Product Details, Complaint, Location, Status of the complaint, etc.
Problem Statement: Analyze the data in the Hadoop ecosystem to:
- Get the number of complaints filed under each product
- Get the total number of complaints filed from a particular location
- Get the list of complaints grouped by location which has no timely response
Project #3: Tourism Data Analysis
Data: The dataset comprises attributes like City pair (combination of from and to), adults traveling, seniors traveling, children traveling, air booking price, car booking price, etc.
Problem Statement: Find the following insights from the data:
- Top 20 destinations people frequently travel to Based on given data we can find the most popular destinations where people travel frequently, based on the specific initial number of trips booked for a particular destination
- Top 20 locations from where most of the trips start based on booked trip count
- Top 20 high air-revenue destinations, i.e the 20 cities that generate high airline revenues for travel, so that the discount offers can be given to attract more bookings for these destinations.
Project #4: Airline Data Analysis
Data: Publicly available dataset which contains the flight details of various airlines such as Airport id, Name of the airport, Main city served by airport, Country or territory where the airport is located, Code of Airport, Decimal degrees, Hours offset from UTC, Timezone, etc.
Problem Statement: Analyze the airlines’ data to:
- Find list of airports operating in the country
- Find the list of airlines having zero stops
- List of airlines operating with codeshare
- Which country (or) territory has the highest number of airports
- Find the list of active airlines in the United States
Project #5: Analyze Loan Dataset
Industry: Banking and Finance
Data: Publicly available dataset which contains complete details of all the loans issued, including the current loan status (Current, Late, Fully Paid, etc.) and latest payment information.
Problem Statement: Find the number of cases per location and categorize the count with respect to the reason for taking a loan and display the average risk score.
Project #6: Analyze Movie Ratings
Data: Publicly available data from sites like rotten tomatoes, IMDB, etc.
Problem Statement: Analyze the movie ratings by different users to:
- Get the user who has rated the most number of movies
- Get the user who has rated the least number of movies
- Get the count of total number of movies rated by user belonging to a specific occupation
- Get the number of underage users
Project #7: Analyze YouTube data
Industry: Social Media
Data: It is about the YouTube videos and contains attributes such as VideoID, Uploader, Age, Category, Length, views, ratings, comments, etc.
Problem Statement: Identify the top 5 categories in which the most number of videos are uploaded, the top 10 rated videos, and the top 10 most viewed videos.
Apart from these, there are some twenty more use-cases to choose:
- Market Data Analysis
- Twitter Data Analysis
Where do our learners come from?
Professionals from around the globe have benefited from Edureka's Big Data Hadoop Certification course. Some of the top places that our learners come from including San Francisco, Bay Area, New York, New Jersey, Houston, Seattle, Toronto, London, Berlin, UAE, Singapore, Australia, New Zealand, Bangalore, New Delhi, Mumbai, Pune, Kolkata, Hyderabad and Gurgaon among many.
Edureka’s Big Data Hadoop online training is one of the most sought-after in the industry and has helped thousands of Big Data professionals around the globe bag top jobs in the industry. This online training includes lifetime access, 24X7 support for your questions, class recordings and mobile access. Our Big Data Hadoop certification also includes an overview of Apache Spark for distributed data processing.
Online Classes: 30 Hrs
There will be 30hrs of Online Live Instructor-led Classes. Depending on the batch you select, it can be:
- 10 live classes of 3 hrs each over Weekend or,
- 15 live classes of 2 hrs each on Weekdays.
Assignments: 40 Hrs
There are hands-on exercises associated with every module in the course. We anticipate that you will spend minimum 40 hours working on assignments to ensure better assimilation of concepts. Edureka will provide the required setup for doing practicals.
Project: 20 Hrs
At the end, you'll work on a Real-life Project on any of the selected use cases, involving Big Data Analytics using MapReduce, Pig, Hive, Flume and Sqoop
You get lifetime access to the Learning Management System (LMS). You will be able to access class recordings on LMS and lifetime feature shall also benefit you to get the future upgraded versions without paying any extra fee.
24 x 7 Support
We have round the clock support available to help you with any technical queries. All the queries are tracked as tickets and you get a guaranteed response from a support engineer. If required, the support team can also provide you Live support by accessing your machine remotely. Please be assured!
Towards the end of the course, you will work on a project. Edureka certifies you in Big Data and Hadoop course based on the project reviewed by our expert panel. Anyone certified by edureka will be able to demonstrate practical expertise in Big Data and Hadoop.
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Last updated February 13, 2018