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Most popular course on Big Data trusted by over 50,000 students! Built with years of experience by industry experts and gives you a complete package of video lectures, practice problems, quizzes. Start Today!

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Big Data Videos

Bigdata என்றால் என்ன? | Big Data Tutorial For Beginners | What Is Big Data Analytics in Tamil

Bigdata என்றால் என்ன? | Big Data Tutorial For Beginners | What Is Big Data Analytics in Tamil

Cloud computing in english | history of cloud computing | cloud server top 10 most online videos

Cloud computing in english | history of cloud computing | cloud server top 10 most online videos

Machine Learningஎன்றால் என்ன?| What Is Machine Learning in Tamil ?| Introduction to Machine Learning

Machine Learningஎன்றால் என்ன?| What Is Machine Learning in Tamil ?| Introduction to Machine Learning


Course Content
5 Days
Topic Text Material Image content Video content Quiz
Pig Introduction -
Story of Big Data -
Big Data Analytics - Data Life Cycle -
Big Data Analytics -
Big Data Analytics - Methodology -
HBase Commands -
HDFS Data Write Operation -
Big Data Analytics - Data Analyst -
Big Data Analytics - Data Scientist -
Avro -
Hadoop Ecosystem -
Hive Architecture -
Impala Installation -
Hadoop Architecture -
Impala Built in Function -
Big Data Analytics - Core Deliverables -
Ambari -
Flume Introduction -
Hadoop Introduction -
HBase -
HCatalog -
HDFS Introduction -
Hive introduction -
Impala -
Mapreduce introduction -
Sqoop Introduction -
Flume installation on Ubuntu -
HBase Architecture -
HDFS Architecture -
Hive Tutorial -
Impala Features -
MapReduce Data Flow Chart -
Pig Hadoop Tutorial -
Sqoop Features -
Types of Big Data -
Why Hadoop -
Application of Big Data -
Hadoop Features -
HBase Features -
HDFS Features -
Hive Features Limitations of Hive -
Impala Use Cases -
MapReduce Mapper -
Pig Installation -
Hadoop History -
HBase Pros and Cons -
Hive Installation on Ubuntu -
Impala Architecture -
10 Days
Topic Text Material Image content Video content Quiz
Big Data Analytics - Data Collection -
Big Data Analytics -
Big Data Analytics - Data Exploration -
Big Data Analytics - Data Visualization -
Hadoop Pors and Cons -
Hadoop Analytics Tools -
Hadoop Internal Works -
Hadoop Commands -
Hadoop getmerge Command -
Hadoop copy From Local Command -
HDFS Data Read and Write Operations -
HDFS Read operation -
MapReduce Reducer -
MapReduce Key-Value Pair in Hadoop -
MapReduce Input Format -
Hive Built-In Functions -
Hive UDFs -
Hive DDL Commands -
Hive DML Commands -
Hive View and Index -
Impala User Defined Functions -
Impala Data Types -
Impala Comments -
Impala SQL -
Impala Select a Database -
Impala CREATE DATABASE -
HBase Use Cases -
HBase Operations -
HBase Table Management -
Pig Hadoop Working -
Pig Latin -
Pig Latin Operators -
Flume Architecture -
Flume Features & Limitations -
Sqoop Architecture -
ZooKeeper Features -
HCatalog Features -
Ambari Features -
Avro Features -
Yarn -
15 Days
Topic Text Material Image content Video content Quiz
Big Data Analytics - Introduction to R -
Big Data Analytics - Introduction to SQL -
Big Data Analytics - Charts & Graphs -
Big Data Analytics - Data Analysis Tools -
Big Data Analytics - Statistical Methods -
Hadoop Cluster -
Hadoop High Availability -
Hadoop Schedulers -
Hadoop Distributed Cache -
Hadoop Failover -
Hadoop Security -
HDFS Commands Part-1 -
HDFS Commands Part-2 -
HDFS Commands Part-3 -
MapReduce Record Reader -
MapReduce Partitioner -
Hive Metastore -
Hive Data Model -
Hive Data Types -
Hive Operators -
Hive SerDe -
Impala DROP DATABASE -
Impala Describe Statement -
Impala Select Statement -
Impala CREATE TABLE -
Impala DROP TABLE Statement -
Impala INSERT Statement -
HBase Data Manipulation -
HBase Admin API -
HBase Client API -
Pig Architecture and Execution -
Pig Features -
Pig pros on cons -
Apache Application -
Flume Source -
Sqoop Installation -
Sqoop Eval -
Sqoop Import -
Zookeeper Architecture -
HCatalog Applications -
Ambari Architecture -
Avro Uses -
YARN Resource -
20 Days
Topic Text Material Image content Video content Quiz
Hadoop Streaming -
Hadoop Limitations -
Hadoop Installation Ubuntu -
Hadoop Installation Multi Node Cluster -
What is New in Hadoop 3 -
Hadoop HBase Compaction -
Hadoop 2 vs Hadoop 3 -
HDFS Data Blocks -
HDFS Rack Awareness -
HDFS High Availability -
HDFS Fault Tolerance -
Name Node High -
MapReduce Combiner -
MapReduce Shuffling and Sorting -
Mapreduce Output Format -
Hive Data Partition -
Hive Bucketing -
Hive Partitioning vs Bucketing -
Hive Join -
Hive Map Join -
Impala TRUNCATE TABLE -
Impala Alter Table -
Impala SHOW Statement -
Impala CREATE VIEW -
Impala DROP -
Impala ALTER -
HBase MemStore -
HBase MapReduce -
HBase Security -
HBase vs RDBMS -
HBase Performance -
Pig Career -
Pig Grunt Shell -
Pig Built in Functions -
Flume Sink -
Flume Sink Processors -
Sqoop Export -
Sqoop Import All Tables -
Zookeeper Workflow -
Zookeeper Terminologies -
HCatalog Command -
Ambari Advantages -
Avro Schema -
YARN Node Manager -
1 Month
Topic Text Material Image content Video content Quiz
Machine Learning for Data Analysis -
Big Data Analytics - Naive Bayes Classifier -
Big Data Analytics - K-Means Clustering -
Big Data Analytics - Association Rules -
Big Data Analytics - Decision Trees -
Big Data Analytics - Logistic Regression -
Big Data Analytics - Time Series Analysis -
Big Data Analytics - Text Analytics -
Big Data Analytics - Online Learning -
Hadoop Best Books -
Hadoop Career -
Hadoop Job Opportunities -
Hadoop Job Profiles -
Hadoop Developer Salary -
Hadoop Certifications -
HDFS Federation -
HDFS Disk Balancer -
MapReduce InputSplit vs HDFS Block -
MapReduce Map Only Job -
MapReduce Data locality in Hadoop -
MapReduce peculative Execution -
Hive Bucket Map Join -
Hive Skew Join -
Hive Sort Merge Bucket Join -
Hive Internal vs External -
Hive Configure MySQL -
Hive QL SELECT Statement -
Hive QL Select Group By Query -
Impala ORDER BY Clause -
Impala GROUP -
Impala LIMIT -
Impala HAVING -
Impala WITH -
Impala UNION -
HBase vs Impala -
HBase Troubleshooting -
Pig User Defined Function -
Pig Script Execution -
Pig Reading Data and Storing -
Flume Channel -
Flume Types of Channels -
Sqoop Validation -
Sqoop Codegen -
Zookeeper Applications -
Zookeeper Benefits -
HCatalog CLI -
Ambari Views -
AVRO Reference API -
Yarn Comparison -
2 Months / 6 Weeks
Topic Text Material Image content Video content Quiz
Big Data Analytics - MapReduce -
Apache Flume -
Apache Sqoop -
Bigdata Testing -
Challenge of Bigdata -
Bigdata - Hive -
Modes of Hive -
Bigdata - HBase -
Feature of HDFS -
Data Flow in MapReduce -
Hadoop for Data Science -
Hadoop vs Cassandra -
Hadoop vs MongoDB -
Hadoop vs Spark vs Flink -
Hadoop Ecosystem Infographic -
HDFS Erasure Coding -
MapReduce Counters -
MapReduce Job Optimization -
MapReduce Performance -
Hive QL Select Order By Query -
Hive Optimization Techniques -
Hive Best Apache Books -
Impala OFFSET -
Impala DISTINCT -
Impala Shell -
Impala Troubleshooting -
Impala Security -
Impala Pros and Cons -
Top 5 Impala books -
Impala vs Hive -
HBase Books -
HBase Career -
HBase Complete Guide -
Pig Execution Modes -
Pig Comprehensive Guide -
Sqoop Metastore -
Sqoop Merge -
ZooKeeper Introduction -
ZooKeeper Data Model -
HCatalog Loader -
Ambari Cluster -
Avro Serialization -
View more

Overview

The volume of data that one has to deal has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. Private companies and research institutions capture terabytes of data about their users’ interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data.This is where big data analytics comes into picture.

Big Data Analytics largely involves collecting data from different sources, munge it in a way that it becomes available to be consumed by analysts and finally deliver data products useful to the organization business.

The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics.

In this internship, we will discuss the most fundamental concepts and methods of Big Data Analytics.

This internship has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. Professionals who are into analytics in general may as well use this internship to good effect.

Before you start proceeding with this internship, we assume that you have prior exposure to handling huge volumes of unprocessed data at an organizational level.

Big Data Description

Big Data Certification

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Internship Certificate

Big Data Projects

Testimonial Reviews

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Surya Maharajan

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A Anand

I will join the FULL STAKE DEVELOPMENT AND DOTNET Class is Awesome ? ?
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Mirnalini Babu

Attended 5 days internship for IOT and he made us to understand the basics of the course . Venkat S

Video Reviews

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Preethi shares her KaaShiv learning experience helped her gain an edge in job interviews and land a job.

Ram Prithiv Raju

Ram Prithiv Raju shares her KaaShiv learning experience helped her gain an edge in job interviews and land a job.

Ajith

Ajith shares her KaaShiv learning experience helped her gain an edge in job interviews and land a job.


Big Data Online Features

24 x 7 Expert Support

We have a lifetime 24x7 online support team to resolve all your technical queries, through a ticket based tracking system.

Certification

Successfully complete your final course project and Kaashiv will certify you as a Big Data Expert.

Forum

We have a community forum for all our learners that further facilitates learning through peer interaction and knowledge

Big Data FAQs