Batch Starts in
Big Data Using HADOOP
Hadoop is an Apache project (i.e. an open source software) to store & process Big Data. Hadoop stores Big Data in a distributed & fault tolerant manner over commodity hardware. Afterwards, Hadoop tools are used to perform parallel data processing over HDFS (Hadoop Distributed File System).
As organisations have realized the benefits of Big Data Analytics, so there is a huge demand for Big Data & Hadoop professionals. Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop Ecosystem and best practices about HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume.
This course is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop Ecosystem. This Hadoop developer certification training is stepping stone to your Big Data journey and you will get the opportunity to work on various Big data projects.
- In-depth knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) & MapReduce
- Comprehensive knowledge of various tools that fall in Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
- The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
- The exposure to many real world industry-based projects which will be executed in Edureka’s CloudLab
- Projects which are diverse in nature covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce
- Rigorous involvement of a Hadoop expert throughout the Big Data Hadoop Training to learn industry standards and best practices
Big Data is one of the accelerating and most promising fields, considering all the technologies available in the IT market today. In order to take benefit of these opportunities, you need a structured training with the latest curriculum as per current industry requirements and best practices.
Besides strong theoretical understanding, you need to work on various real world big data projects using different Big Data and Hadoop tools as a part of solution strategy.
Additionally, you need the guidance of a Hadoop expert who is currently working in the industry on real world Big Data projects and troubleshooting day to day challenges while implementing them.
- Master the concepts of HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator), & understand how to work with Hadoop storage & resource management.
- Understand MapReduce Framework
- Implement complex business solution using MapReduce
- Learn data ingestion techniques using Sqoop and Flume
- Perform ETL operations & data analytics using Pig and Hive
- Implementing Partitioning, Bucketing and Indexing in Hive
- Understand HBase, i.e a NoSQL Database in Hadoop, HBase Architecture & Mechanisms
- Integrate HBase with Hive
- Schedule jobs using Oozie
- Implement best practices for Hadoop development
- Understand Apache Spark and its Ecosystem
- Learn how to work with RDD in Apache Spark
- Work on real world Big Data Analytics Project
- Work on a real-time Hadoop cluster
- Software Developers, Project Managers
- Software Architects
- ETL and Data Warehousing Professionals
- Data Engineers
- Data Analysts & Business Intelligence Professionals
- DBAs and DB professionals
- Senior IT Professionals
- Testing professionals
- Mainframe professionals
- Graduates looking to build a career in Big Data Field
- Hadoop Market is expected to reach $99.31B by 2022 at a CAGR of 42.1% -Forbes
- McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts
- Average Salary of Big Data Hadoop Developers is $97k
There are no such prerequisites for Big Data Using Hadoop Course. However, prior knowledge of Core Java and SQL will be helpful but is not mandatory. Further, to brush up your skills, EduCare offers a complimentary self-paced course on "Java essentials for Hadoop" when you enroll for the Big Data and Hadoop Course.
For more information and details about the course
Learning Objectives: In this module, you will understand what Big Data is, the limitations of the traditional solutions for Big Data problems, how Hadoop solves those Big Data problems, Hadoop Ecosystem, Hadoop Architecture, HDFS, Anatomy of File Read and Write & how MapReduce works.
- 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
Learning Objectives: In this module, you will learn Hadoop Cluster Architecture, important configuration files of Hadoop Cluster, Data Loading Techniques using Sqoop & Flume, and how to setup Single Node and Multi-Node Hadoop Cluster.
- 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
Productivity Hacks to Get More Done in 2018
— 28 February 2017
- Facebook News Feed Eradicator (free chrome extension) Stay focused by removing your Facebook newsfeed and replacing it with an inspirational quote. Disable the tool anytime you want to see what friends are up to!
- Hide My Inbox (free chrome extension for Gmail) Stay focused by hiding your inbox. Click "show your inbox" at a scheduled time and batch processs everything one go.
- Habitica (free mobile + web app) Gamify your to do list. Treat your life like a game and earn gold goins for getting stuff done!