About the Course
Big Data is upcoming technolgies where their is a around 40K to 4 Lakhs openings were generating in next 6 months to 3 years.
We provide a training on such emerging technology i.e Big Data by our Industry expert who is having around 10 years of experience in Data base and Big Data technology experience.
Topics CoveredCourse Objectives
The course outline (HADOOP Development)
Module-I Virtual Box/VM Ware
Basics, Installations, Backups, Snapshots
Basics, Installations, Commands
Why Hadoop?, Scaling, Distributed Framework, Hadoop v/s RDBMS, Brief history of hadoop, Problems with traditional large-scale systems, Requirements for a new approach, Anatomy of a Hadoop Cluster,Other Hadoop Ecosystem Components
Module-II HDFS- Hadoop distributed File System-
HDFS Design and Architecture, HDFS Concepts, Interacting HDFS using command line, Interacting HDFS using Java APIs, Dataflow, Blocks, Replica
Name node, Secondary name node, Job tracker, Task tracker, Data node
Module-III Map Reduce
Developing Map Reduce Application, Phases in Map Reduce Framework, Map Reduce Input and Output Formats, Advanced Concepts, Sample Applications, Combiner
Writing a MapReduce Program
The MapReduce Flow, Examining a Sample MapReduce Program, Basic MapReduce API Concepts, The Driver Code, The Mapper, The Reducer, Hadoop’s Streaming API, Using Eclipse for Rapid Development, Hands-on exercise, The New MapReduce API
Common MapReduce Algorithms
Sorting and Searching, Indexing, Machine Learning, Term Frequency – Inverse Document Frequency, Word Co-Occurrence, Hands-On Exercise
Module-IV Hadoop Programming Languages
HIVE:Introduction, Installation and Configuration, Interacting HDFS using HIVE, Map Reduce Programs through HIVE, HIVE Commands, Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in HIVE
PIG:Basics, Installation and Configurations, Commands
What is HBase?, HBase Architecture, HBase API, Managing large data sets with HBase, Using HBase in Hadoop applications, Working Hive With Hbase(Integration), Sqoop Exports and Imports, Hands-on exercise
After the completion of the Big Data and Hadoop Course, you should be able to:
• Master the concepts of Hadoop Distributed File System and MapReduce framework
• Setup a Hadoop Cluster
• Understand Data Loading Techniques using Sqoop and Flume
• Program in MapReduce
• Learn to write Advance MapReduce programs
• Perform Data Analytics using Pig and Hive
• Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing
• Implement best Practices for Hadoop Development and Debugging
• Implement a Hadoop Project
• Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience
Who should go for this course?
This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course.
Some of the prerequisites for learning Hadoop include hands-on experience in Core Java and good analytical skills to grasp and apply the concepts in Hadoop. We provide a complimentary Course "Java Essentials for Hadoop" to all the participants who enroll for the Hadoop Training. This course helps you brush up your Java Skills needed to write Map Reduce programs.
Towards the end of the 8 week schedule you will be working on a project which will be a large dataset and you will be using PIG, HIVE, HBase and MapReduce to perform Big Data analytics. The final project is a real life business case on some open data set. There is not one but a large number of datasets which are a part of the Big Data and Hadoop Program.
In addition, you can choose your own dataset and create a project around that as well.
Why Learn Big Data and Hadoop?
BiG Data! A Worldwide Problem?
According to Wikipedia, “Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.” In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, It is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success!
The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop, which is not less than a panacea for all those companies working with BIG DATA in a variety of applications has become an integral part for storing, handling, evaluating and retrieving hundreds or even petabytes of data.
Apache Hadoop! A Solution for Big Data!
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don’t overlook the charming yellow elephant you see, which is basically named after Doug’s son’s toy elephant!
Big Data is a set of unstructured and structured data that is complex in nature and is growing exponentially with each passing day. Organizations are facing a major challenge in storing and utilizing this enormous data. This problem spans across the world because of a serious dearth of skilled programmers.
"The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data."
Some of the top companies using Hadoop:
The importance of Hadoop is evident from the fact that there are many global MNCs that are using Hadoop and consider it as an integral part of their functioning, such as companies like Yahoo and Facebook! On February 19, 2008, Yahoo! Inc. established the world's largest Hadoop production application. The Yahoo! Search Webmap is a Hadoop application that runs on over 10,000 core Linux cluster and generates data that is now widely used in every Yahoo! Web search query.
Facebook, a $5.1 billion company has over 1 billion active users in 2012, according to Wikipedia. Storing and managing data of such magnitude could have been a problem, even for a company like Facebook. But thanks to Apache Hadoop! Facebook uses Hadoop to keep track of each and every profile it has on it, as well as all the data related to them like their images, posts, comments, videos, etc.
Opportunities for Hadoopers!
Opportunities for Hadoopers are infinite - from a Hadoop Developer, to a Hadoop Tester or a Hadoop Architect, and so on. If cracking and managing BIG Data is your passion in life, then think no more and Join course and carve a niche for yourself!
Who should attendB E \M Tech Graduates freshares as well as experienced students
BCA\MCA\BSc comp or E&C can attend.
SQL or Oracle data base knowledge
If the student doesnt have knowledge on Java or Data base we provide training in the same course.
What you need to bringPen
Key TakeawaysAfter successful completion of training student can able to Analyse the Structured and Un Structured data using Big Data concepts.
Able to write a Queries and generate analytics.