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Big Data, Analytics and Beyond Sri Krishnamurthy, CFA, CAP Founder and CEO www.QuantUniversity.com Lecturer, Babson College [email protected]

Big data, Analytics and Beyond

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Page 1: Big data, Analytics and Beyond

Big Data, Analytics and Beyond Sri Krishnamurthy, CFA, CAP

Founder and CEO www.QuantUniversity.com

Lecturer, Babson College [email protected]

Page 2: Big data, Analytics and Beyond

BABSON COLLEGE — ALL RIGHTS RESERVED

Agenda

• Big Data and Analytics : A brief introduction

• Leveraging technology to gain competitive advantage

• The Five technological trends of the last decade

• Technology tips to implement a successful analytics strategy

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BIG DATA: A BRIEF INTRODUCTION

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http://tinyurl.com/bzbxf44

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BABSON COLLEGE — ALL RIGHTS RESERVED

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BABSON COLLEGE — ALL RIGHTS RESERVED

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Traditional Analytics versus Big-Data Analytics– The paradigm shift

• Exploration versus canned reports

• Information from multiple sources

• Trading off accuracy for speed

• What versus Why?

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LEVERAGING TECHNOLOGY TO GAIN COMPETITIVE ADVANTAGE

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Netflix

• Close to 30 million customers

• Beat brick-and-mortar giant Blockbuster.

• Uses Amazon’s cloud services

• Recommendation engines, A/B Testing infrastructure, data stores etc.

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Zynga - Farmville

• Expected 200,000 daily users in first 2 months

• Got 1 million users every month

• Scaled seamlessly since the application was built on the cloud

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New York Times

• Used Amazon EC2

• Process 4TB of images to 11 million PDF files in 24 hrs

• Cost: $240

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5 TECHNOLOGICAL TRENDS IN THE LAST DECADE

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Trend 1: Machine learning comes to age

• Parallel and distributed algorithms have made mining massive data sets simpler

– Example: Map-Reduce (Hadoop)

• Large-scale recommendation systems possible with newer algorithms

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Trend 2: Memory is cheap

• Cost to store all the music in the world - $600!

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Trend 3: Good bye datacenters. Hello Cloud!

• Rent versus Buy

• Super computing: Cycle computing set up a 30,000 core cluster at the cost of $1,279/hr for 8 hrs on Amazon

• 1000 CPUs for 1 hr = 1 CPU for 1000 hrs

Microsoft’s datacenter in Ireland to support the Azure cloud

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Trend 4: Open source drives innovation

• Hadoop: Software framework that supports data-intensive distributed applications

• Mahout : Java-based machine learning algorithms

• Mongo-DB: A No SQL document database

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Trend 5: Rich Visualization

• From reporting to data exploration

• Visualizing live data streams

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TECHNOLOGY TIPS TO IMPLEMENT A SUCCESSFUL ANALYTICS STRATEGY

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Source: http://tdwi.org/research/2011/09/best-practices-report-q4-big-data-analytics.aspx

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Tips

1. Assess: How analytical is your organization now?

2. Ask: Do you really have a big-data problem?

3. Need: Is there a compelling case to address the problem now? Can you articulate the business value of solving this problem ?

4. Change: Does your organization have the right kind of skills , aptitude and culture to implement a solution?

5. Foresee: Does the technology roadmap you plan to adopt meet the demands you see in the future?

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Summary

• Data has significantly increased in the last decade • Huge opportunities for businesses; tech has been a key-enabler. • Technology trends made Big Data and Analytics possible:

Trend 1: Machine learning comes to age Trend 2: Memory is cheap Trend 3: Good bye datacenters. Hello Cloud! Trend 4: Open source drives innovation Trend 5: Rich Visualization

• Before embarking on implementing a big-data solution, companies must analyze whether the solution would help them achieve the business value they aim for.

Page 25: Big data, Analytics and Beyond

Big Data, Analytics and Beyond Sri Krishnamurthy, CFA, CAP

Founder and CEO www.QuantUniversity.com

Lecturer, Babson College [email protected]