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BIG DATA ANALYTICS

By

Rahul Kulkarni
 Big Data
Big Data Players in the Market
Hadoop Ecosystems

 Analytics


Machine Learning Algorithms

 SMAC
WHAT IS BIG DATA?
“Big Data” is high-volume, high velocity,
high variety information assets that demand cost effective,
in...
By 2020, 1.7 MB of new information will be created for each and every human being on the planet – every second every day.
DATA CONTRIBUTIONS
Personalized for each visitor
HADOOP WAS A KEY PART OF IBMS WATSON
Hadoop analytics and data
discovery abilities were a
big reason that IBM's
Watson com...
BIG DATA PLAYERS
EVOLUTION OF HADOOP
Simple models do
better than experts

LET US GET STARTED
AN INSURANCE PROBLEM
Product
Car Insurance
Life Insurance
Health Insurance
2-wheeler Insurance
Heavy Vehicle Insurance

Re...
WHAT WE CANNOT EXPLAIN
FIRST MODEL . . .
 Categorize data as VEHICLE and NON-VEHICLE insurance.
 The average of vehicle insurance: 100
 The un...
Analytics

Machine Learning : Supervised & Un-supervised Learning

Lets get started with two different techniques
(Supervi...
Machine Learning
- Grew out of work in AI
- New capability for computers
Examples:
- Database mining
Large datasets from g...
SUPERVISED LEARNING
PREDICTION AND FORECASTING
UN-SUPERVISED LEARNING
"Consumer data will be the biggest
differentiator in the next two to three years.
Whoever unlocks the reams of data and us...
The Obama 2012 campaign used data analytics and the experimental method
to assemble a winning coalition vote by vote. The ...
SMAC will be the platform that will enable
organizations to drive consumerization of
technology, including IT. Early adopt...
cloud computing is a synonym for
distributed computing over a network,
and means the ability to run a program
or applicati...
THANK YOU . . . . .
Big data analytics
Big data analytics
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Big data analytics
Big data analytics
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Big data analytics

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Big data analytics

  1. 1. BIG DATA ANALYTICS By Rahul Kulkarni
  2. 2.  Big Data Big Data Players in the Market Hadoop Ecosystems  Analytics  Machine Learning Algorithms  SMAC
  3. 3. WHAT IS BIG DATA? “Big Data” is high-volume, high velocity, high variety information assets that demand cost effective, innovative forms of information processing for enhanced insight and decision making.
  4. 4. By 2020, 1.7 MB of new information will be created for each and every human being on the planet – every second every day.
  5. 5. DATA CONTRIBUTIONS
  6. 6. Personalized for each visitor
  7. 7. HADOOP WAS A KEY PART OF IBMS WATSON Hadoop analytics and data discovery abilities were a big reason that IBM's Watson computer was able to win a widely publicized "Jeopardy“ showdown last year against a couple of very successful human former champions.
  8. 8. BIG DATA PLAYERS
  9. 9. EVOLUTION OF HADOOP
  10. 10. Simple models do better than experts LET US GET STARTED
  11. 11. AN INSURANCE PROBLEM Product Car Insurance Life Insurance Health Insurance 2-wheeler Insurance Heavy Vehicle Insurance Revenues in last quarter in million 110 180 220 90 100
  12. 12. WHAT WE CANNOT EXPLAIN
  13. 13. FIRST MODEL . . .  Categorize data as VEHICLE and NON-VEHICLE insurance.  The average of vehicle insurance: 100  The unexplained = (90-100)2+(100-100)2+(110-100)2=200  The average non-vehicle insurance = 200  The unexplained = (180-200)2+(220-200)2= 800 R2
  14. 14. Analytics Machine Learning : Supervised & Un-supervised Learning Lets get started with two different techniques (Supervised) - Classification and Regression (Un-Supervised) - Clustering
  15. 15. Machine Learning - Grew out of work in AI - New capability for computers Examples: - Database mining Large datasets from growth of automation/web. E.g., Web click data, medical records, biology, engineering - Applications can’t program by hand. E.g., Autonomous helicopter, handwriting recognition, most of Natural Language Processing (NLP), Computer Vision. - Self-customizing programs E.g., Amazon, Netflix product recommendations - Understanding human learning (brain, real AI).
  16. 16. SUPERVISED LEARNING
  17. 17. PREDICTION AND FORECASTING
  18. 18. UN-SUPERVISED LEARNING
  19. 19. "Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win“ -Angela Ahrendts, CEO of Burberry Big Data is key to any Loyalty scheme
  20. 20. The Obama 2012 campaign used data analytics and the experimental method to assemble a winning coalition vote by vote. The interests of individual voters were known and addressed. Online Media and Web Analytics helped Obama beat McCain, changed the political scene in one of the most powerful nations in the world and how it has influenced the course of history - Obama had 2.5 M Facebook friends compared to a paltry 0.5 M Facebook friends for McCain (seems strange to think of politicians on Facebook though..) – Obama raised USD 500 M online versus the total amount of USD, 201 M by McCain Percentage of votes cast for Obama by early voters in Hamilton Model - 57.68%, Actual 57.16% Television commercials aired on TV land (National cable level) Obama campaign - 1,710, Romney campaign - 0 Money spent on online Ads through Mid-October Romney Campaign - $26 million, Obama Campaign - $52 millions
  21. 21. SMAC will be the platform that will enable organizations to drive consumerization of technology, including IT. Early adopters of SMAC stack would have a clear competitive edge in their line of business
  22. 22. cloud computing is a synonym for distributed computing over a network, and means the ability to run a program or application on many connected computers at the same time
  23. 23. THANK YOU . . . . .

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