The document discusses the importance of learning Hadoop due to the explosive growth of big data, predicting that by 2020, global information will reach 40 zettabytes. It highlights Hadoop's advantages, such as speed, flexibility, scalability, and cost-effectiveness, and emphasizes the increasing enterprise adoption of Hadoop, which will lead to better job opportunities in the future. The conclusion urges individuals to learn Hadoop now to capitalize on these trends and prepare for a career in data science.

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Is It the right time for me to Learn Hadoop ?
Find Out!

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At the end of the session, you will be able to:
 Understand Why Learn Hadoop?
 Know Advantages of Hadoop & its Predictions for 2015
 Discover Hadoop Career Path
 Understand how Companies are using Hadoop?
Agenda

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Why Hadoop?

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Rise of Big Data
 By 2020, IDC (International Data Corporation) predicts the number will have reached 40,000 EB, or 40 Zettabytes
(ZB)
The world’s information is doubling every two years. By 2020, there will be 5,200 GB of data for every person on
Earth.
0
1000
2000
3000
4000
5000
6000
7000
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Unstructured Data
Structured Data Un-structured Data

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Application of Big Data
Source: Twitter

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Application of Big Data
Amazon handles 15 million
customer click stream user
data per day to
recommend products.
Stock market generates about one
terabyte of new trade data per day
to perform stock trading analytics to
determine trends for optimal trades.
294 billion emails sent every
day. Services analyse this data
to find the spams.
Systems / Enterprises generate huge amount of data from Terabytes to Petabytes of information

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Can’t use Big Data without Hadoop
Current Scenario:
 Unstructured Data is Exploding
 Organizations take fact based decisions
 The Bigger the data, accurate is the decision!
Conclusion:
The use of Big Data is essential
 To Enable the use of Big Data one needs “Hadoop”

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Advantages of Hadoop & its Predictions

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Advantages of Hadoop
F  Fast
F  Flexible
S  Scalable
CE  Cost Effective
FT  Fault Tolerant
F
CE
FT
S
F

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Feature Comparision
Structured Data Types Multi and Unstructured
Limited, No Data Processing Processing Processing coupled with Data
Standards & Structured Governance Loosely Structured
Required On Write Schema Required On Read
Reads are Fast Speed Writes are Fast
Software License Cost Support Only
Known Entity Resources Growing, Complexities, Wide
OLTP
Complex ACID Transactions
Operational Data Store
Best Fit Use Data Discovery
Processing Unstructured Data
Massive Storage/Processing
RDBMS HADOOP

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2015 Predictions for Hadoop!
Hadoop has been found not
guilty of being an over-
hyped open source platform!
Source: Forrester
Hadooponomics makes enterprise adoption mandatory
Enterprise
Adoption
The Hadoop skills shortage will disappear
Enterprise
Developers
Hadoop will become SQL enabled
SQL Featured
Hadoop
Integration with enterprise softwares – SAS, Teradata,
Talent etc.
Large Enterprise
Adoption
Hadoop Clusters in the cloud
Scalable Hadoop
Cluster
Beyond Analytics, it will become Application Platform
Expanding Horizon
More Hadoop Distributions will emerge by large
enterprise vendors like SAS, Oracle, IBM etc.
Increasing
Competition

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Hadoop Career Path

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Hadoop Career Path
• Java / Python / Ruby
• Hadoop Eco-system
• NoSQL DB
• Spark
• Linux Administration
• Cluster Management
• Cluster Performance
• Virtualization
• Statistics Skills
• Machine Learning
• Hadoop Essentials
• Expertise in R
Developers/Testers
Administrators
Data Analyst
Hadoop Developer
Hadoop Administrator
Data Scientist

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Job Trends

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Major Companies Using Hadoop

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How Companies are using Hadoop?

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Common Big Data Customer Scenarios
 Web and e-tailing
» Recommendation Engines
» Ad Targeting
» Search Quality
» Abuse and Click Fraud Detection
 Telecommunications
» Customer Churn Prevention
» Network Performance Optimization
» Calling Data Record (CDR) Analysis
» Analysing Network to Predict Failure
http://wiki.apache.org/hadoop/PoweredBy

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Common Big Data Customer Scenarios
 Government
» Fraud Detection and Cyber Security
» Welfare Schemes
» Justice
 Healthcare and Life Sciences
» Health Information Exchange
» Gene Sequencing
» Serialization
» Healthcare Service Quality Improvements
» Drug Safety
http://wiki.apache.org/hadoop/PoweredBy

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Demo

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The Big Question!
Is it the right time for me to learn Hadoop?

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The Big Question!
Is it the right time for me to learn Hadoop?
Answer – Yes, it’s Now or Never!
Reasons:
1. Hadoop has proved its worth
2. Large Enterprises are adopting Hadoop
3. Hadoop skill Shortage will disappear. Learn Before its too late
4. Handsome paid opportunities

22. Questions
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