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Best Hadoop Training Institute in Chennai

Big data is making its presence now, and Hadoop is a big data technology that lets distributed storage and computing of data. The businesses nowadays are keener on customers. Customer care relates to personalized service while dealing with various modes of consumer interaction. Hadoop fixes difficult challenges faced by companies. It also lessens the drawbacks of conventional data approaches and is gaining momentum in big data technology. Enroll in the Hadoop training in Chennai and get to know the importance of this solution for big data. Aimore Technologies concentrates on career-oriented training so that you have the confidence to attend the interviews.

Big data is making its presence now, and Hadoop is a big data technology that lets distributed storage and computing of data. The businesses nowadays are keener on customers.

Customer care relates to personalized service while dealing with various modes of consumer interaction. Hadoop fixes difficult challenges faced by companies. It also lessens the drawbacks of conventional data approaches and is gaining momentum in big data technology. Enroll in the Hadoop training in Chennai and get to know the importance of this solution for big data. Aimore Technologies concentrates on career-oriented training so that you have the confidence to attend the interviews.

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Overview of Hadoop

Hadoop offers a powerful and affordable data storage system. Hadoop with its entire ecosystem is a solution for significant data concerns, Several components of Hadoop ecosystem including MapReduce, TEZ, etc. offer support for big data analytics, Companies utilize Hadoop for big data crunching, Learn about this powerful concept from the best Hadoop training institute in Chennai.

Career scope of Hadoop

When you have skills including Hadoop, etc. you can get into promising big data jobs. The best means to kickstart your career in big data is taking up Hadoop developer or administrator training. As per the job profile you require for yourself, you can opt for the right training for you.

Big data applications and demand for skilled, trained personnel demonstrates momentous growth. Besides, the job scope of Hadoop is ever-growing since data continues to increase tremendously and is utilized by most devices today. Hadoop also serves as the most popular suite for managing big data sets. Moreover, Hadoop is excellent at handling petabytes of big data.

It is suggested to join Big Data Hadoop training in Chennai and gain practical hands-on experience. Theoretical knowledge is not sufficient to dive into Big Data. The companies may pay a handsome pay for the right candidate. So you can quickly get into the Hadoop job with an excellent salary if you could prove your worth. Big Data Hadoop job needs more concentration, and you should take care of the enormous sum of data. So enroll in the best Hadoop training institute in Chennai and get trained by proficient trainers.

Job profiles for Hadoop professionals after Big data Hadoop training in Chennai

Hadoop Architect
Hadoop Developer
Hadoop Administrator
Hadoop Analysts
Hadoop Scientist
Hadoop Engineer

Prerequisites for Hadoop classes in Chennai

Fair knowledge of Java, Linux, and big data

Who can attend Big Data Hadoop training in Chennai?

If you are enthusiastic towards Big Data Hadoop, then this course will take your career to the next level. However, if you belong to a Science background and possess excellent mathematical skills, then big data could be a great career option.

Software Developers,
Project Managers
Software Architects
ETL and Data Warehousing Professionals
Testing professionals
Analytics & Business Intelligence Professionals
DBAs
Senior IT Professionals
Mainframe professionals
Graduates inclined to build a career in the big data field

Hadoop certifications

Cloudera Hadoop Certification
Cloudera Certified Professional – Data Scientist (CCP DS)
Cloudera Certified Administrator for Hadoop (CCAH)
Cloudera Certified Hadoop Developer (CCDH)

MapR Hadoop Certification

MapR Certified Hadoop Developer (MCHD)
MapR Certified Hadoop Administrator (MCHA)
MapR Certified HBase Developer (MCHBD)

Hortonworks Hadoop Certification

Hortonworks Certified Apache Hadoop Developer (HCAHD)
Hortonwoks Certified Apache Hadoop Administrator (HCAHA)

Hadoop training in Chennai Syllabus

Topics:

Apache Hadoop

Introduction to Big Data & Hadoop Fundamentals
Dimensions of Big data
Type of Data generation
Apache ecosystem & its projects
Hadoop distributors
HDFS core concepts
Modes of Hadoop employment
HDFS Flow architecture
HDFS MrV1 vs. MrV2 architecture
Types of Data compression techniques
Rack topology
HDFS utility commands
Min h/w requirements for a cluster & property files changes

Module 2 (Duration :03:00:00)

MapReduce Framework

Goal : In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will understand concepts like Input Splits in MapReduce, Combiner &Partitioner and Demos on MapReduce using different data sets.

Objectives – Upon completing this Module, you should be able to understand MapReduce involves processing jobs using the batch processing technique.

MapReduce can be done using Java programming.
Hadoop provides with Hadoop-examples jar file which is normally used by administrators and programmers to perform testing of the MapReduce applications.
MapReduce contains steps like splitting, mapping, combining, reducing, and output.

Topics:

Introduction to MapReduce

MapReduce Design flow
MapReduce Program (Job) execution
Types of Input formats & Output Formats
MapReduce Datatypes
Performance tuning of MapReduce jobs
Counters techniques

Module 3 (Duration :03:00:00)

Apache Hive

Goal : This module will help you in understanding Hive concepts, Hive Data types, Loading and Querying Data in Hive, running hive scripts and Hive UDF.

Objectives – Upon completing this Module, you should be able to understand Hive is a system for managing and querying unstructured data into a structured format.

The various components of Hive architecture are metastore, driver, execution engine, and so on.
Metastore is a component that stores the system catalog and metadata about tables, columns, partitions, and so on.
Hive installation starts with locating the latest version of tar file and downloading it in Ubuntu system using the wget command.
While programming in Hive, use the show tables command to display the total number of tables.

Topics:

Introduction to Hive & features

Hive architecture flow
Types of hive tables flow
DML/DDL commands explanation
Partitioning logic
Bucketing logic
Hive script execution in shell & HUE

Module 4 (Duration :03:00:00)

Apache Pig

Goal : In this module, you will learn Pig, types of use case we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, PIG running modes, PIG UDF, Pig Streaming, Testing PIG Scripts. Demo on healthcare dataset.

Objectives – Upon completing this Module, you should be able to understand Pig is a high-level data flow scripting language and has two major components: Runtime engine and Pig Latin language.

Pig runs in two execution modes: Local mode and MapReduce mode. Pig script can be written in two modes: Interactive mode and Batch mode.
Pig engine can be installed by downloading the mirror web link from the website: pig.apache.org.

Topics:

Introduction to Pig concepts
Pig modes of execution/storage concepts
Pig program logics explanation
Pig basic commands
Pig script execution in shell/HUE

Module 5 (Duration :03:00:00)

Goal : This module will cover Advanced HBase concepts. We will see demos on Bulk Loading, Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.

Objectives – Upon completing this Module, you should be able to understand HBasehas two types of Nodes—Master and RegionServer. Only one Master node runs at a time. But there can be multiple RegionServersat a time.

The data model of Hbasecomprises tables that are sorted by rows. The column families should be defined at the time of table creation.
There are eight steps that should be followed for installation of HBase.
Some of the commands related to HBaseshell are create, drop, list, count, get, and scan.

Topics:

Apache Hbase

Introduction to Hbase concepts
Introdcution to NoSQL/CAP theorem concepts
Hbase design/architecture flow
Hbase table commands
Hive + Hbase integration module/jars deployment
Hbase execution in shell/HUE

Module 6 (Duration :02:00:00)

Goal : Sqoop is an Apache Hadoop Eco-system project whose responsibility is to import or export operations across relational databases. Some reasons to use Sqoop are as follows:

SQL servers are deployed worldwide
Nightly processing is done on SQL servers
Allows to move certain part of data from traditional SQL DB to Hadoop
Transferring data using script is inefficient and time-consuming
To handle large data through Ecosystem
To bring processed data from Hadoop to the applications

Objectives – Upon completing this Module, you should be able to understand Sqoop is a tool designed to transfer data between Hadoop and RDBs including MySQL, MS SQL, Postgre SQL, MongoDB, etc.

Sqoop allows the import data from an RDB, such as SQL, MySQL or Oracle into HDFS.

Topics:

Apache Sqoop

Introduction to Sqoop concepts
Sqoop internal design/architecture
Sqoop Import statements concepts
Sqoop Export Statements concepts
Quest Data connectors flow
Incremental updating concepts
Creating a database in MySQL for importing to HDFS
Sqoop commands execution in shell/HUE

Module 7 (Duration :02:00:00)

Goal : Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates them to where they need to be processed.

Objectives – Upon completing this Module, you should be able to understand Apache Flume is a distributed data collection service that gets the flow of data from their source and aggregates the data to sink.

Flume provides a reliable and scalable agent mode to ingest data into HDFS.

Topics:

Apache Flume

Introduction to Flume & features
Flume topology & core concepts
Property file parameters logic

Module 8 (Duration :02:00:00)

Goal : Hue is a web front end offered by the ClouderaVM to Apache Hadoop.

Objectives – Upon completing this Module, you should be able to understand how to use hue for hive,pig,oozie.

Topics:

Apache HUE

Introduction to Hue design
Hue architecture flow/UI interface

Module 9 (Duration :02:00:00)

Goal : Following are the goals of ZooKeeper:

Serialization ensures avoidance of delay in reading or write operations.
Reliability persists when an update is applied by a user in the cluster.
Atomicity does not allow partial results. Any user update can either succeed or fail.
Simple Application Programming Interface or API provides an interface for development and implementation.

Objectives – Upon completing this Module, you should be able to understand ZooKeeper provides a simple and high-performance kernel for building more complex clients.

ZooKeeper has three basic entities—Leader, Follower, and Observer.
Watch is used to get the notification of all followers and observers to the leaders.

Topics:

Apache Zookeeper

Introduction to zookeeper concepts
Zookeeper principles & usage in Hadoop framework
Basics of Zookeeper

Module 10 (Duration :05:00:00)

Goal:

Explain different configurations of the Hadoop cluster

Identify different parameters for performance monitoring and performance tuning
Explain configuration of security parameters in Hadoop.

Objectives – Upon completing this Module, you should be able to understand Hadoop can be optimized based on the infrastructure and available resources.

Hadoop is an open-source application and the support provided for complicated optimization is less.
Optimization is performed through xml files.
Logs are the best medium through which an administrator can understand a problem and troubleshoot it accordingly.
Hadoop relies on the Kerberos based security mechanism.

Topics:

Administration concepts

Principles of Hadoop administration & its importance
Hadoop admin commands explanation
Balancer concepts
Rolling upgrade mechanism explanation

Advantages of Hadoop

Hadoop is a storage platform and is thoroughly scalable. It can conveniently store and distribute massive databases at a specific instance on servers that could be functioned in parallel.
Hadoop is very affordable compared to conventional database management systems.
Hadoop controls data via clusters, thus offering a unique storage method according to distributed file systems. Hadoop’s striking feature of mapping data on the clusters facilitates quick data processing.
Hadoop lets companies access and process data in a very simple way to produce the values needed by the company. It offers companies with the tools to gain valuable insights from several types of data sources that are functioning in parallel.
Fault tolerance is one of the significant highlights of Hadoop. This attribute is offered by replicating the data to another node in the cluster. So when there is a failure, the data from the replicated node can be utilized, thereby adhering to data consistency.

Parts of Hadoop

Hadoop Distributed File System: Generally called as HDFS, it is a distributed file system that is compatible with massive scale bandwidth.
MapReduce: A software framework that is used for processing big data
YARN: It is a technology applied for controlling and scheduling Hadoop’s resources in Hadoop infrastructure.
Libraries: Assists other models to function with Hadoop

Windows Application Developer
Technology Architect
IOS Developer
C# Developer
Python Developer
VB Developer
Android App Developer
Web Developer
UI Developer

Hadoop certifications

Cloudera Hadoop Certification
Cloudera Certified Professional – Data Scientist (CCP DS)
Cloudera Certified Administrator for Hadoop (CCAH)
Cloudera Certified Hadoop Developer (CCDH)

MapR Hadoop Certification

MapR Certified Hadoop Developer (MCHD)
MapR Certified Hadoop Administrator (MCHA)
MapR Certified HBase Developer (MCHBD)

Hortonworks Hadoop Certification

Hortonworks Certified Apache Hadoop Developer (HCAHD)
Hortonwoks Certified Apache Hadoop Administrator (HCAHA)

Trainer Profile

Aimore Trainers give total opportunity to the understudies,
to investigate the subject and learn dependent on constant models. Our coaches help the up-and-comers
in finishing their undertakings and even set them up for inquiries questions and replies.

Competitors are allowed to pose any inquiries whenever.

More than 10+ Years of Experience.

Prepared more than 2000+ understudies in a year.

Solid Theoretical and Practical Knowledge.

Confirmed Professionals with High Grade.

Very much associated with Hiring HRs in worldwide organizations.

Master level Subject Knowledge and completely state-of-the-art on certifiable industry applications.

Coaches have Experienced on various ongoing undertakings in their Industries.

Our Trainers are working in global organizations, for example,ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies and so on

Overview

Overview of Hadoop

Syllabus

Oracle Training Syllabus

The syllabus for Oracle training in Chennai is crafted so that the aspiring candidate gets to know all the concepts of the subject in a thorough manner. Oracle is a broad concept and we are careful to comprise all the technicalities in our well-formed syllabus. We want to make the candidate industry-ready and hence ensure that the syllabus is both the latest and best. You can view the detailed syllabus here.

Database Architecture

Describe course objectives
Explore the Oracle 10g database architecture

Installing the Oracle Database Software

Explain core DBA tasks and tools
Plan an Oracle installation
Use optimal flexible architecture
Install software with the Oracle Universal Installer (OUI)

Creating an Oracle Database

Create a database with the Database Configuration Assistant (DBCA)
Create a database design template with the DBCA
Generate database creation scripts with the DBCA

Managing the Oracle Instance

Start and stop the Oracle database and components
Use Enterprise Manager (EM)
Access a database with SQL*Plus and iSQL*Plus
Modify database initialization parameters
Understand the stages of database startup
View the Alert log
Use the Data Dictionary

Managing Database Storage Structures

Describe table data storage (in blocks)
Define the purpose of tablespaces and data files
Understand and utilize Oracle Managed Files (OMF)
Create and manage tablespaces
Obtain tablespace information
Describe the main concepts and functionality of Automatic Storage Management (ASM)

Administering User Security

Create and manage database user accounts
Authenticate users
Assign default storage areas (tablespaces)
Grant and revoke privileges
Create and manage roles
Create and manage profiles
Implement standard password security features
Control resource usage by users

Managing Schema Objects

Define schema objects and data types
Create and modify tables
Define constraints
View the columns and contents of a table
Create indexes, views and sequences
Explain the use of temporary tables
Use the Data Dictionary
Manage data through SQL
Monitor and resolve locking conflicts

Managing Undo Data

Explain DML and undo data generation
Monitor and administer undo
Describe the difference between undo and redo data
Configure undo retention
Guarantee undo retention
Use the undo advisorv

Implementing Oracle Database Security

Describe DBA responsibilities for security
Apply the principal of least privilege
Enable standard database auditing
Specify audit options
Review audit information
Maintain the audit trail
Oracle DBA Training Syllabus – Part 2

Configuring the Oracle Network Environment

Create additional listeners
Create Net Service aliases
Configure connect-time failover
Control the Oracle Net Listener
Test Oracle Net connectivity
Identify when to use shared versus dedicated servers

Backup and Recovery Concepts

Identify the types of failure that may occur in an Oracle Database
Describe ways to tune instance recovery
Identify the importance of checkpoints, redo log files, and archived log files
Configure ARCHIVELOG mode

Performing Database Backups

Create consistent database backups
Back your database up without shutting it down
Create incremental backups
Automate database backups
Monitor the flash recovery area

Performing Database Recovery

Recover from loss of a control file
Recover from loss of a redo log file
Perform complete recovery following the loss of a data file

Performing Flashback

Describe Flashback database
Restore the table content to a specific point in the past with Flashback Table
Recover from a dropped table
View the contents of the database as of any single point in time with Flashback Query
See versions of a row over time with Flashback Versions Query
View the transaction history of a row with Flashback Transaction Query

Moving Data

Describe available ways for moving data
Create and use directory objects
Use SQL*Loader to load data from a non-Oracle database (or user files)
Explain the general architecture of Data Pump
Use Data Pump Export and Import to move data between Oracle databases
Use external tables to move data via platform-independent files

Configuring Recovery Manager

Recovery Manager Features and Components
Using a Flash Recovery Area with RMAN
Configuring RMAN
Control File Autobackups
Retention Policies and Channel Allocation
Using Recovery Manager to connect to a target database in default NOCATALOG mode
Displaying the current RMAN configuration settings
Altering the backup retention policy for a database

Using Recovery Manager

RMAN Command Overview
Parallelization of Backup Sets
Compressed Backups
Image Copy
Whole Database and Incremental Backups
LIST and REPORT commands
Enable ARCHIVELOG mode for the database
Use Recovery Manager

Recovering from Non-critical Losses

Recovery of Non-Critical Files
Creating New Temporary Tablespace
Recreating Redo Log Files, Index Tablespaces, and Indexes
Read-Only Tablespace Recovery
Authentication Methods for Database Administrators
Loss of Password Authentication File
Creating a new temporary tablespace
Altering the default temporary tablespace for a database

Incomplete Recovery

Recovery Steps
Server and User Managed Recovery commands
Recovering a Control File Autobackup
Creating a New Control File
Incomplete Recovery Overview
Incomplete Recovery Best Practices
Simplified Recovery Through RESETLOGS
Point-in-time recovery using RMAN

Flashback

Flashback Database Architecture
Configuring and Monitoring Flashback Database
Backing Up the Flash Recovery Area
Using V$FLASH_RECOVERY_AREA_USAGE
Flashback Database Considerations
Using the Flashback Database RMAN interface
Using Flashback Database EM Interface
Managing and monitoring Flashback Database operations

Dealing with Database Corruption

Block Corruption Symptoms: ORA-1578
DBVERIFY Utility and the ANALYZE command
Initialization parameter DB_BLOCK_CHECKING
Segment Metadata Dump and Verification
Using Flashback for Logical Corruption and using DBMS_REPAIR
Block Media Recovery
RMAN BMR Interface
Dumping and Verifying Segment Metadata

Monitoring and Managing Storage I

Database Storage Structures
Space Management Overview
Oracle-Managed Files (OMF)
Row Chaining and Migrating
Proactive Tablespace Monitoring
Managing Resumable Space Allocation
SYSAUX Tablespace
Monitoring table and index space usage

Monitoring and Managing Storage II

Automatic Undo Management
Redo Log Files
Table Types
Partitioned Tables
Index-Organized Tables (IOT)
Managing index space with SQL
Configure optimal redo log file size
View “Automatic Tuning of Undo Retention”

VLDB Support

Creating Bigfile Tablespaces
Packages and data dictionary changes to support VLDB
Creating and maintaining temporary tablespace groups (TTG)
Partitioning and Partitioned Indexes
Skipping unusable indexes
DML Error Logging
Interpreting Bigfile ROWIDs

Why Hadoop Bigdata

Advantages of Hadoop

Hadoop is a storage platform and is thoroughly scalable. It can conveniently store and distribute massive databases at a specific instance on servers that could be functioned in parallel.
Hadoop is very affordable compared to conventional database management systems.

Hadoop controls data via clusters, thus offering a unique storage method according to distributed file systems. Hadoop’s striking feature of mapping data on the clusters facilitates quick data processing.
Hadoop lets companies access and process data in a very simple way to produce the values needed by the company. It offers companies with the tools to gain valuable insights from several types of data sources that are functioning in parallel.
Fault tolerance is one of the significant highlights of Hadoop. This attribute is offered by replicating the data to another node in the cluster. So when there is a failure, the data from the replicated node can be utilized, thereby adhering to data consistency.

Parts of Hadoop

Hadoop Distributed File System: Generally called as HDFS, it is a distributed file system that is compatible with massive scale bandwidth.
MapReduce: A software framework that is used for processing big data
YARN: It is a technology applied for controlling and scheduling Hadoop’s resources in Hadoop infrastructure.
Libraries: Assists other models to function with Hadoop

To Whom

Windows Application Developer
Technology Architect
IOS Developer
C# Developer
Python Developer
VB Developer
Android App Developer
Web Developer
UI Developer

Certification

Hadoop certifications

Cloudera Hadoop Certification
Cloudera Certified Professional – Data Scientist (CCP DS)
Cloudera Certified Administrator for Hadoop (CCAH)
Cloudera Certified Hadoop Developer (CCDH)

MapR Hadoop Certification

MapR Certified Hadoop Developer (MCHD)
MapR Certified Hadoop Administrator (MCHA)
MapR Certified HBase Developer (MCHBD)

Hortonworks Hadoop Certification

Hortonworks Certified Apache Hadoop Developer (HCAHD)
Hortonwoks Certified Apache Hadoop Administrator (HCAHA)

Trainer Profile

Competitors are allowed to pose any inquiries whenever.

More than 10+ Years of Experience.

Prepared more than 2000+ understudies in a year.

Solid Theoretical and Practical Knowledge.

Confirmed Professionals with High Grade.

Very much associated with Hiring HRs in worldwide organizations.

Master level Subject Knowledge and completely state-of-the-art on certifiable industry applications.

Coaches have Experienced on various ongoing undertakings in their Industries.

Our Trainers are working in global organizations, for example,ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies and so on

Key Features

Our Testimonials

The faculties are highly experienced and friendly. The quality of teaching is excellent and the approach is very practical. They have designed the syllabus for easy learning and every aspect of the subject is covered with real time knowledge and problems. They train everyone irrespective of their technical or non technical knowledge at their best. build us from the basic. Aimore is the best choice for any course learning and it is more than worth of our time and money.

I joined Aimore Technologies after my graduation. I did Database Develpment course and once i finished the course. I joint Mentis Inc through Aimore Technologies as Production Support Engineer. I got lot of knowdlege and confidence from Aimore. They helped me to start my carrer in right path and still i am closely associated with Aimore to enhance my Skills in Software.

Excellent Training Institute for Fresher. I did Oracle course and got placed in Mentis Inc as Oracle Developer. Trainers are so friendly and they helped me in improving Interview Skills. Totally trustable and who ever is ready to chose SOFTWARE as career they can come and join in Aimore with full confidence.

Datascience at Aimore Very amazing course. Great teacher Great explanation. From zero, I know a very lot about data science and its process from this course. The way he taught, his slide and his explanation are very easy to understand. All of these make me want to jump into the data scientist world. Again, very very amazing course, I highly recommend this. Very statisfied.

Best institute to learn AWS. Prakash teaches each and every service required here in great details and provides all the key pointers for you to understand them well. AWS training in Aimore teaches you AWS and not just prepares you for exam.Again, very very amazing course, I highly recommend this. Very statisfied.