Big Data and Hadoop Introduction
Master Big Data and Hadoop to unlock great career opportunities as a Hadoop developer. Become a Hadoop expert by learning concepts like MapReduce, Yarn, Pig, Hive, Sqoop, Flume, HBase, Oozie. Get real time industry with some of the best Big Data projects and real-life use-cases.
Big Data and Hadoop Introduction
Objective: In this module, you will be able to get big data context, its definition and its integration with Hadoop in terms of storage and processing.
Topics: Big Data definition, Big Data context with case studies, structured vs unstructured, Hadoop basics, Hadoop characteristics, entire Hadoop ecosystem, Hadoop core components, Secondary name node.
HDFS Architecture, HADOOP Configurations & Data Loading
Objective: In this module, you will learn the concept of Blocks, Rack awareness, HDFS architecture and a few Hadoop commands. This module also covers HDFS High Availability, HDFS Federation and YARN.
Topics: Blocks, Data Replication and Rack Awareness, HDFS File Write Anatomy, HDFS File Read Anatomy, HDFS Architecture, Common Hadoop Shell Commands, High Availability, HDFS Federation, YARN, Firing our First Map Reduce Job, Checking the output of M/R Job and Understanding the dump of Map Reduce Job.
Introduction to Map Reduce
Objective: In this module, you will learn about different Hadoop modes, configuration files, Split vs Blocks, traditional and Hadoop based distributed computing techniques. You will also learn advanced concepts like Combiners & Partitioners and Shuffle & Sort.
Topics: Hadoop Cluster Modes, Configuration Files, Web URLs, Split vs Blocks, Map Reduce use-cases, solving a problem in Traditional way, Understanding Map Reduce way, Map Reduce Anatomy, Advantages of Map Reduce, and Map Reduce Flow.
Advanced Map Reduce Concepts
Objective: In this module, you will learn the advanced concepts like MR Unit, Counters, Distributed Cache and Joins.
Topics: MR Unit, Counters, Distributed Cache, Joins, Secondary Sort and Total Order Sort.
Introduction to Pig and Advance Pig
Objective: In this module, you will be get a complete understanding of PIG & its association with Map Reduce.
Topics: Pig Background, Need for Pig, Pig Vs M/R, Pig Definition, Pig Latin, Pig users, Pig usage at Yahoo, Pig Interaction Modes, Pig program execution, Pig data model, Pig data types, Pig operators and specialized Joins.
Introduction to Hive and Advance Hive
Objective: In this module you will learn about Hive Background, Hive comparison with RDBMS and Hive design and architecture.
Topics: Hive Background, Hive Definition, Pig vs Hive, RDBMS vs Hive, Hive components, Hive Architecture, Hive Meta Store, Hive Design, Hive Data Model, Partition and Buckets.
Introduction to Hbase and Advanced HBase
Objective: In this module you will learn about NoSQL Background, Hive comparison with RDBMS and Hive design and architecture.
Topics: NoSQL background and description, Real time scenarios, NoSQL landscapes, HBase definition, HBase characteristics, HBase history, HBase vs. RDBMS, HBase Data Model, HBase Data Model – Graphical representation, HBase Data Model – Logical Vs. Physical representation, Version concepts, Region and Region Servers and Zookeeper.
Sqoop and Flume
Objective: In this module, you will learn the concepts of Defining the Flume flow, configuring individual components, configuration with twitter, Flume agent, Source, Sync, configuration of entire Flume set-up.
Topics: Scoop Setup between Hadoop and RDBMS, Exporting Data from Hadoop into RDBMS, Importing Data from RDBMS into Hadoop,importing data from.
Basic Oozie and Oozie configuration
Objective: In this module, you will learn the concepts of Oozie as a Hadoop Workflow Framework and how it orchestrates the execution of Hadoop Components.
Topics: Oozie workflow, Oozie server , Oozie co-ordinator, Oozie Bundles, Configuration XML and Properties file, Creating Oozie application, Oozie web console, Oozie scheduling.
Project Discussions
Objective: In this session, you will get familiar with the project you would be working for your certification along with several other topics.
Topics: Project Discussions, Evaluating Individual Approaches, Finalizing Optimal Approach.
After completing this course, you will have absolute theoretical & practical mastery over the following:
- Data Loading via HDFS
- HDFS Read, Write & File Anatomy
- Configuring Name Node, Slave Node, Job Tracker & Task Tracker
- Applying the YARN Framework
- YARN Resource & Application Managers
- MapReduce 2.0 – YARN Interaction
- Running Jobs via MapReduce 2.0
- Distributed Cache, Combiner, Mapper & Reducer
- MR-Unit, Counters & Map+Reduce Side Joins
- PIG-Latin, Data Models & Interaction Modes
- Data Types, Operators & Specialized Joins
- PIG – Mapreduce Compliers & UDFs
- HiveQL, Hive vs RDBMS, Hive vs PIG
- Metastore, Data Models, Partition & Buckets
- Hive Compiler & UDFs
- Integrating Hive with MapReduce
- Sqoop Setup, Hadoop – RDBMS Data Loading
- Sequences & Configuration Management
- Flume Agent, Setup & Workflow
- Source-Sync-Configuration
- Hbase Real-time Scenarios
- Hbase vs RDBMS, NoSQL Landscapes
- Data Modelling: Logical, Physical & Graphical
- Region Servers
- Integrating Hbase with MapReduce
- Oozie Bundles, Workflow & Servers
- XML & Properties Files
- Applications, Web Consoles & Job Scheduling
- Use-Cases: 15 Industries
We are only happy, if you are happy. If you have any reason to doubt the content, delivery & expertise of our program, you are eligible for a 100% refund within 7 days of enrollment.
If we're able to provide you with a valid alternative or in case you choose to drop-out due to a personal emergency, a refund will not be valid. This is being done to protect our company from fraud.
This the the best BIG Data & Hadoop course in the market for the following reasons:
Completely Optimized for Hadoop 2.x - This ensures you learn the latest version of this technology.
5 Live Industry Grade Projects – These projects are developed in liaison with our corporate partners & esteemed faculty consisting of industry experts with 10+ years of experience. Each of the projects is very advanced; the average time to complete one project is 12 hours. You will be exposed to domains such as Finance, Retail, Aviation, Manufacturing, IT Networking, Healthcare & Social Media. In addition to you getting real-time project experience, you also get exposure to production level implementation challenges. This gives you the perfect platform to work on BIG Data & Hadoop at your work-place.
Production Level Cloud-Based Labs – We provide you exclusive access to our very own production-level BIG Data & Hadoop clusters wherein you can practice & implement all your assignments & projects. These clusters were initially created for our corporate clients such as HP & Wipro, thus, ensuring that you are getting the highest quality of production exposure. These labs have a 100% up-time.
Quality of Instructors – We don’t have young amateur professionals who’ve memorized slides to teach you. Instead, we’ve got the absolute experts to give you the best learning experience. This is our instructor hiring check-list:
- Minimum Industry Experience – 10 Years
- Minimum Industry Experience in Core Subject – 3 Years
- Required Certifications: Cloudera, Hortonworks & MapR
- Minimum Training Experience – 120 Hours
Optimized for Industry Certifications - Do you want to get certified by any of the industry bodies? Our BIG Data & Hadoop course is absolutely optimized for all leading certifications. In addition to the live classes & projects we will also provide you with question banks, installation manuals and practical guides which will aid your endeavor.
You will be provided with an LMS – Learning Management System. This is a 24/7 lifetime-access student dashboard featuring the following:
- Course Recordings
- PDFs, eBooks & Installation Guides
- Assignments, Data-sets & Quizzes
- Support Access
- Project Statements & Solution Guides
We have a 24/7 support team featuring expert professionals with at least 3 years of experience in the specific technology. In addition to this, they're also given soft-skills training to ensure the best possible experience for you.
The support team is accessible via phone, email, live chat & video-calls. Please note, this is a lifetime facility. Even after course completion you can access the support facilities.
You will be eligible for placement assistance only after you’ve completed the whole course and at least 2 out of 5 projects from our repository.
This program would involve the following to give you the best chance of getting placed:
- Preparation via Question Banks & HR FAQs
- CV Assistance
- Profile Showcase to 50+ Corporate Partners
- Interaction Management
The only reason we can offer this to you is because our corporate partners trust us with their employee training and validate our course, therefore, they also hire from our student pool.
If you stay in your current domain for the next 4 years, will you be happy with you career growth? Or, do you want more?
If you do, then BIG Data & Hadoop would be the perfect avenue for you. The reasons for this are as follows:
- The BIG Data industry is growing at an annual growth rate of 31.7%, the highest of any technology till date – IDC Report 2015
- Professionals can expect salary hikes up to 250% when they upgrade to BIG Data & Hadoop – Analytics Industry Report 2015
- Hadoop will be the most advanced analytics product in 2015-2016 – Gartner BIG Data Report
- Enterprise adoption of Hadoop will be compulsory in 2016; It will transform from a framework into an application platform; They will be an unprecedented demand for skilled Hadoop professionals – Forrester Analytics Update
Another testament to this is that leading IT companies such as Wipro, Cognizant, Dell, HP, Persistent, Unisys, Mphasis & more have an extremely high demand for Hadoop developers running in 10,000+ to whom they are willing to pay very premium salaries.
What does this mean for you? This means that you have the opportunity to learn the most lucrative technology in the market in terms on career progressions, work quality and remuneration.
This would be the first step for you into data sciences, the most lucrative profession of the 21st century.
We are only happy, if you are happy. If you have any reason to doubt the content, delivery & expertise of our program, you are eligible for a 100% refund within 7 days of enrollment.
If we're able to provide you with a valid alternative or in case you choose to drop-out due to a personal emergency, a refund will not be valid. This is being done to protect our company from fraud.
If anybody tells you that Core Java is not required to learn Hadoop, then they are lying to you. The only pre-requisite to learn Hadoop is a basic functional knowledge of Core Java. In case you don’t have that, then we give out a course to all students on enrollment titled ‘Java & Linux Essentials for Hadoop’, wherein we cover all the essential required concepts.
Individuals with the following backgrounds should immediately upgrade to Hadoop:
- Java Developers
- Database Administrators
- ETL Developers
- Business Intelligence Developers
- Mainframe Developers
- Data-warehousing Professionals
- Testing Professionals
- Technical Architects
This course can also be taken by young graduates as they have an opportunity to start their careers with the latest technology in the market.
The reason for this is superior capability of Hadoop as compare traditional RDBMS. These are the key factors:
- Completely Open Source
- Enables Parallel & Batch Processing
- Perfect for Unstructured Data
- Based on Distributed File System
- 100% Fault Tolerance & Backups
- 100% Flexibility & Scalability
Therefore, it is the most potent BIG Data technology in the market.
Each student is provided with a industry recognized certification after course completion. This certificate is recognizned by all our corporate partners and also features the grade awarded to each student based on their classroom, assignment & project performance.
In addition to this, we also provide assistance for all leading industry standard certifications.
