Bigdata & Hadoop Online Training

Course Overview

The Bigdata Hadoop Course Training is provided to everyone who successfully completes this course and passes the online test held at the end of every module. This course is designed to give an in-depth knowledge of Big Data framework with the help of Hadoop and Spark. Real-life and Industry based projects are also included in the course content to give hands-on practical training. Upgrade your skills with the help of Big Data and Hadoop as they are smart career decisions.

About Big Data Hadoop

Big Data and Hadoop are not similar to each other as many people are of a concept that these two are similar to each other. Big Data is an actual problem faced by many organisations and Hadoop is the solution to this problem. Hadoop is used to handle Big Data which is used by many large companies and social media networks. Big Data and Hadoop are very trending in today's IT industry and companies are looking for candidates who have acquired skill-set in these concepts.

What are the objectives of Bigdata Hadoop Online Training?

The comprehensive training provided by SV Soft Solutions on Big Data and Hadoop helps you learn various concepts. The main ones are listed below -

• Setting up a pseudo node and multi-node cluster on Amazon EC2
• Fundamental concepts of Hadoop and Yarn and how to write applications using them.
• Hadoop applications test using MRUnit and other similar automation tools.
• Data Frame, Spark, Spark SQL, Streaming, GraphX, MLlib writing Spark applications.
• Zookeeper, Flume, HBase, HDFS, MapReduce, etc.

Why learning Bigdata Hadoop is a good idea to grow your career?

Big Data and Hadoop are growing at a very fast pace and the technology is very promising as it helps to handle a large volume of data for data analysis. Almost all top MNCs are looking forward to getting into Big Data and Hadoop and therefore they are looking for certified candidates of this field. Other benefits include -

• The global market of Big Data and Hadoop will reach $84.6 billion in two years. Thus, taking up a big share of the market.
• The job opportunities for data professionals will increase to 2.7 million per year.
• A Hadoop Administrator earns an average salary of $123,000 per year.

Who should learn Bigdata Hadoop?

People who can obtain great benefits by taking up Best Bigdata Hadoop Training From India are -

• Experience working professionals of a similar field and Project Managers
• Business Intelligence, Data Warehousing and Analytics Professional
• Programming Developers and System Administrators
• Big Data Hadoop Developers who are eager to learn other different verticals like analytics, testing, etc.

What will you learn from Bigdata Hadoop Online Training?

The Bigdata Hadoop Training From Hyderabad course provided is a combination of Hadoop Development, Hadoop Administration, Hadoop Testing and Analytics with Apache Spark. Below mentioned concepts are learned in this course -

• Working with Avro Data Formats
• Administration activities by using Hadoop
• Writing applications using Hadoop, YARN, etc.
• ETL Tools configuration, learn how to use MapReduce, Hive, Pig, etc.
• Monitoring, administering, troubleshooting, etc. master such skills.

Certificates Provided

Variety of modules are taught in the entire course and certificates are provided after completing each separate module. Some major certifications provided by SV Soft Solutions are -

• Big Data Architect Masters Program
• Big Data and Hadoop Training Certificate
• Apache Kafka Certificate
• Python Spark using PySpark
• Comprehensive Hive Certification

What are the career paths after taking Bigdata Hadoop Online Training?

Big Data opportunities for career growth are on the rise and Hadoop is a well-known technology used by large companies who handle Big Data. Therefore, professionals with such skills get job opportunities in different job roles such as -

• Analytics Professionals
• Data Management Professionals
• Data Scientists or Aspiring Data Scientists
• Software Developers and Architects
• Business Intelligence Professionals

Which companies recruit Bigdata Hadoop professionals?

Below mentioned large companies are constantly looking for professionals who have acquired skills in Big Data Management using Hadoop.

• Microsoft
• Amazon Web Services
• Pivotal Software
• Cloudera
• Hortonworks
• IBM
• Mu Sigma

HDFS and MAPREDUCE

• Introduction to BIG DATA and Its characteristics
• 4 V's of BIG DATA(IBM Definition of BIG DATA)
• What is Hadoop?
• Why Hadoop?
• Core Components of Hadoop
• Intro to HDFS and its Architecture
• Difference b/w Code Locality and Data Locality
• HDFS commands
• Name Node’s Safe Mode
• Different Modes of Hadoop
• Intro to MAPREDUCE
• Versions of HADOOP
• What is Daemon?
• Hadoop Daemons?
• What is Name Node?
• What is Data Node?
• What is Secondary name Node?
• What is Job Tracker?
• What is Task Tracker?
• What is Edge computer in Hadoop Cluster and Its role
• Read/Write operations in HDFS
• Complete Overview of Hadoop1.x and Its architecture
• Rack awareness
• Introduction to Block size
• Introduction to Replication Factor(R.F)
• Introduction to HeartBeat Signal/Pulse
• Introduction to Block report
• MAPREDUCE Architecture
• What is Mapper phase?
• What is shuffle and sort phase?
• What is Reducer phase?
• What is split?
• Difference between Block and split
• Intro to first Word Count program using MAPREDUCE
• Different classes for running MAPREDUCE program using Java
• Mapper class
• Reducer Class and Its role
• Driver class
• Submitting the Word Count MAPREDUCE program
• Going through the Jobs system output
• Intro to Partitioner with example
• Intro to Combiner with example
• Intro to Counters and its types
• Different types of counters
• Different types of input/output formats in HADOOP
• Use cases for HDFS & MapReduce programs using Java
• Single Node cluster Installation
• Multi Node cluster Installation
• Introduction to Configuration files in Hadoop and Its
• Complete Overview of Hadoop2.x and Its architecture
• Introduction to YARN
• Resource Manager
• Node Manager
• Application Master(AM)
• Applications Manager(AsM)
• Journal Nodes
• Difference Between Hadoop1.x and Hadoop2.x
• High Availability(HA)
• Hadoop Federation

PIG

• Intro to PIG
• Why PIG?
• The difference between MAPREDUCE and PIG
• When to go with MAPREDUCE?
• When to go with PIG?
• PIG data types
• What is field in PIG?
• What is tuple in PIG?
• What is Bag in PIG?
• Intro to Grunt shell?
• Different modes in PIG
• Local Mode
• MAPREDUCE mode
• Running PIG programs
• PIG Script
• Intro to PIG UDFs
• Writing PIG UDF using Java
• Registering PIG UDF
• Running PIG UDF
• Different types of UDFs in PIG
• Word Count program using PIG script
• Use cases for PIG scripts

HIVE

• Intro to HIVE
• Why HIVE?
• History of HIVE
• Difference between PIG and HIVE
• HIVE data types
• Complex data types
• What is Metastore and its importance?
• Different types of tables in HIVE
• Managed tables
• External tables
• Running HIVE queries
• Intro to HIVE partitions
• Intro to HIVE Buckets
• How to perform the JOINS using HIVE queries
• Intro to HIVE UDFs
• Different types of UDFs in HIVE
• Running HIVE queries for Word Count example
• Use cases for HIVE

HBASE

• Intro to HBASE
• Intro to NoSQL database
• Sparse and dense Concept in RDBMS
• Intro to columnar/column oriented database
• Core architecture of HBase
• Why Hbase?
• HDFS vs HBase
• Intro to Regions, Region server and Hmaster
• Limitations of Hbase
• Integration with Hive and Hbase
• Hbase commands
• Use cases for HBASE

FLUME

• Intro to Flume
• Intro to Sink, Source, Flume Master and Flume agents
• Importance of Flume agents
• Live Demo on copying LOG DATA into HDFS

SQOOP

• Intro to Sqoop
• Importing and exporting the RDBMS into HDFS
• Intro to incremental imports and its types
• Use cases to import the Mysql data into HDFS

ZOOKEEPER

• Intro to Zookeeper
• Zookeeper operations

OOZIE

• Intro to Oozie
• What is properties
• What is xml
• Scheduling the jobs in Oozie
• Scheduling MapReduce, HIVE,PIG jobs/Programs using
• Setting up the VMware for Hadoop
• Installing all Hadoop Components
• Intro to Hadoop Distributions
• Intro to Cloudera and its major components

SCALA

• Getting started With
• Scala Background, Scala Vs Java
• Introduction to Scala – REPL
• Scala data types, variables, simple
• Intro to Scala compiler
• Installing Scala on Linux
• Intro to Functional Programming Language
• Differences between OOPS and FPP
• Word count pgm, file handling
• Running Scala script
• Intro to Maps, Sets, groupBy, Options, flatten, flatMap and more

SPARK

• What is Spark Ecosystem
• Batch vs real time data processing
• Intro to Spark Architecture
• Installing Scala on Linux

• Scala utility in Spark
• Spark Cluster Managers
• Spark -Standalone mode Installation
• Spark on YARN
• Spark on MESOS
• What is SparkContext
• Intro to RDDs
• Intro to DAG
• RDD’s lineage
• How to work on RDD in Spark
• What is transformations and Actions
• Intro to Spark Streaming(SS)
• Intro to Discretized Streams RDD
• Applying Transformations and Actions on Streaming data
• Intro to Spark Streaming Architecture
• Applying transformations and Actions on SS data
• How to run a Spark Cluster
• Comparison of MapReduce vs Spark
• Integration of Hadoop and Spark

TABLEAU

• Tableau Fundamentals
• Tableau Analytics
• Visual Analytics
• Creating different types of WorkSheets,Dashboards and
• Connecting with different data sources
• Hadoop Integration with Tableau