Big Data Hadoop Course in Chandigarh Mohali Panchkula - ThinkNEXT
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Applications are invited for Free 6 Months/6 Weeks Industrial Training. Email your resume at information@thinknext.co.in (Limited Seats).    
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Big Data Hadoop Training Course in Chandigarh Mohali Panchkula

Best Hadoop (Big Data) Training in Chandigarh Mohali panchkula

Hadoop Training is gaining popularity in a great speed in the IT sectors. If you are looking for Hadoop Training in Chandigarh, then why not settle for the best. ThinkNEXT Technologies Pvt. Ltd. provides Hadoop Big Data Training in Chandigarh. We provide the best practical training sessions along with 100% practical and live based project training program. We have established the name in the field of Hadoop Training along with other IT Courses.


Hadoop (Big Data) Industrial Training - Contents

Hadoop (Big Data) Ecosystem
  Motivation for Hadoop
  Different types of projects by Apache
  Role of projects in the Hadoop Ecosystem
  Key technology foundations required for Big Data
  Limitations and Solutions of existing Data Analytics Architecture
  Comparison of traditional data management systems with Big Data management systems
  Evaluate key framework requirements for Big Data analytics
  Hadoop Ecosystem & Hadoop 2.x core components
  Explain the relevance of real-time data
  Explain how to use big and real-time data as a Business planning tool

Building Blocks
  Quick tour of Java
  Quick tour of Linux commands
  Introduction to Cloudera VM/Cloudera Manager(Apache Ambari)/Download & usage instructions

Hadoop Cluster -Architecutre - Configuration files
  Hadoop Master-Slave Architecture
  The Hadoop Distributed File System - data storage
  Explain different types of cluster setups(Fully distributed/Pseudo etc)
  Hadoop Cluster set up - Installation
  Hadoop 2.x Cluster Architecture
  A Typical enterprise cluster – Hadoop Cluster Modes

Hadoop Core Components - HDFS & Map Reduce(YARN)
  HDFS Overview & Data storage in HDFS
  Get the data into Hadoop from local machine (Data Loading Techniques) - vice versa
  MapReduce Overview (Traditional way Vs. MapReduce way)
  Concept of Mapper & Reducer
  Understanding MapReduce program skeleton
  Running MapReduce job in Command line/Eclipse
  Develop MapReduce Program in JAVA
  Develop MapReduce Program with the streaming API
  Test and debug a MapReduce program in the design time
  How Partitioners and Reducers Work Together
  Writing Customer Partitioners Data Input and Output
  Creating Custom Writable and Writable Comparable Implementations

Data Integration using Sqoop, Flume & Talend
  Integrating Hadoop into an existing Enterprise
  Loading Data from an RDBMS into HDFS by Using Sqoop
  Managing Real-Time Data Using Flume
  Accessing HDFS from Legacy Systems with FuseDFS and HttpFS
  Introduction to Talend (commuity system)
  Data loading to HDFS using Talend

data Analysis using PIG
  Introduction to Hadoop Data Analysis Tools
  Introduction to PIG - MapReduce Vs Pig, Pig Use Cases
  Pig Latin Program & Exectution
  Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Pig UDF
  Use Pig to automate the design and implementation of MapReduce applications
  Data Analysis using PIG

Data Analysis using HIVE
  Introduction to Hive - Hive Vs. PIG - Hive Use Cases
  Discuss the Hive data storage principle
  Explain the File formats and Records formats supported by the Hive environment
  Perform operations with data in Hive
  Hive QL: Joining Tables, Dynamic Partitioning, Custom MapReduce Scripts
  Hive Script, Hive UDF

Data Analysis using Impala
  Introduction to Impala & Architecture
  How Impala executes Queries and its importance.
  Hive vs. PIG vs. Impala
  Extending impala with User Defined functions
  Improving impala Performance

NoSql Data base - HBASE
  Introduction to NoSQL Databases and Hbase
  HBase v/s RDBMS, HBase Components, HBase Architecture
  HBase Cluster Deployment

Hadoop - Other Analytics Tools
  Introduction to role of R in Hadoop Eco-system
  Introduction to Jasper Reports & creating reports by integrating with Hadoop
  Role of Kafka & Avro in real projects



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