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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 IBM’S 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
10. 10. Simple models do better than experts LET US GET STARTED
11. 11. AN INSURANCE PROBLEM Product Revenues in last quarter in million Car Insurance 110 Life Insurance 180 Health Insurance 220 2-wheeler Insurance 90 Heavy Vehicle Insurance 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. Lets get started with two different techniques (Supervised) - Classification and Regression (Un-Supervised) - Clustering Analytics Machine Learning : Supervised & Un-supervised Learning
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 . . . . .