Single Course Details

About the Training

This Hadoop preparing is intended to make you an affirmed Big Data professional by giving you rich hands-on preparing on Hadoop biological system and best practices about HDFS, MapReduce, HBase, Hive, Pig, Oozie, Sqoop. This course is venturing stone to your Big Data voyage and you will get the chance to take a shot at a Big information Analytics extend subsequent to selecting an informational collection of your decision.

What you will learn in this training?

1.Master fundamentals of Hadoop 2.7 and YARN and write applications using them

2.Setting up Pseudo node and Multi node cluster on Amazon EC2

3.Master HDFS, MapReduce, Hive, Pig, Oozie, Sqoop, Flume, Oozie, Pig, Zookeeper, HBase

4.Learn Spark, Spark RDD, Graphx, MLlib writing Spark applications

5.Master Hadoop administration activities like cluster managing, monitoring, administration and troubleshooting

6.Configuring ETL tools like Pentaho/Talend to work with MapReduce, Hive, Pig, etc

7.Detailed understanding of Big Data analytics

8.Hadoop testing applications using MR Unit and other automation tools.

9.Work with Avro data formats

10.Practice real-life projects using Hadoop and Apache Spark

11.Be equipped to clear Big Data Hadoop Certification.

Who should take this training?

1.Programming Developers and System Administrators

2.Experienced working professionals, Project managers

3.Big DataHadoop Developers eager to learn other verticals like Testing, Analytics, Administration

4.Mainframe Professionals, Architects & Testing Professionals

5.Business Intelligence, Data warehousing and Analytics Professionals

6.Graduates, undergraduates eager to learn the latest Big Data technology can take this Big Data Hadoop Certification online training

What are the prerequisites for this training?

There is no pre-requisite to take this Big data training and to master Hadoop. But basics of UNIX, SQL and java would be good. We provide complimentary unix and Java course with our Big Data certification training to brush-up the required skills so that you are good on you Hadoop learning path

Why you should go for training?

1. Worldwide Hadoop Market to Reach $84.6 Billion by 2021 - Allied Market Research

2. Shortage of 1.4 - 1.9 million Hadoop Data Analysts in only us by 2018 - Mckinsey

3. Hadoop Administrator in the US can get a pay of $123,000 - indeed.com

4. Enormous Data is quickest developing and most encouraging innovation for taking care of expansive volumes of information for doing information investigation. This Big Data Hadoop preparing will help you to be up and running in the most requesting proficient abilities. All the top MNC are attempting to get into Big Data Hadoop consequently there is an enormous interest for Certified Big Data experts. Our Big Data internet preparing will help you to overhaul your vocation in huge information space.

What Hadoop Projects you will be working on?

Towards the finish of the course, you will chip away at a live venture where you will utilize PIG, HIVE, HBase and MapReduce to perform Big Data examination.

A couple of industry case studies -particular Big Data contextual analyses that are incorporated into our Big Data and Hadoop Certification e.g. Back, Retail, Media, Aviation and so on which you can consider for your extend 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 Ratings data.
• Write a fancy Hive Query to analyze the data further and push the output is into 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

Industry:Retail

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

Industry:Tourism

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

Industry:Aviation

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 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 code share
• 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 reason for taking loan and display the average risk score.

Project #6: Analyze Movie Ratings

Industry:Media

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