Big Data & Its Bigger Possibilities In The Cloud
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1 Big Data & Its Bigger Possibilities In The Cloud Chhavi Gupta Software Engineer, EMC Corporation Sai Pattem Professional MBA Candidate 2013 August 15 th, 9:30 10:30 AM Session Room 200 (Hynes Convention Center) 1
2 Agenda Big Data Definition Relativity Challenges Cloud Computing Definition Private, Public, and Hybrid Cloud SaaS PaaS IaaS Technology Tools Handling Big Data in the Cloud Conclusion 2
3 Big Data Definition of Big Data consists of 3Vs+C High Volume (Facebook,youTube) High Velocity (Facebook,Twitter) High Variety (text files, multimedia, pdfs) Complexity (Amazon) Mobile Sensors Social Media Video Surveillance Video Rendering Smart Grids Geophysical Exploration Medical Imaging Gene Sequencing 3
4 Big Data Relativity Big Data is a relative concept What is BIG today May not be so big tomorrow. 4
5 Big Data Relativity 5
6 Big Data Challenges Challenges related to big data Organization needs to grow but can t spend much to buy new servers, storage Reliable backup and need to access anywhere/anytime Want to test a software before investment in it May need an application for only a brief period of time Critical customer data, but lacks secured storage infrastructure 6
7 Cloud Introduction What is Cloud Computing? Massively scalable Convenient on-demand network access Enables an organization to extend virtualization beyond enterprise data center Aggregates resources scattered across the globe Location independent virtual image of aggregated resources Fully- automated request fulfillment process in the background 7
8 Cloud Pros & Cons Private Public Hybrid Private Cloud 1) Higher Security 2) Higher Control 3) Better Service Quality 4) Higher Availability 1) More Maintenance 2) Big or Mid-size Companies Public Cloud 1) Cost Efficient 2) Competitive Advantage 3) Readily Available 1) Less Secured & Compliant 2) Higher Data Vulnerabilities Hybrid Cloud 1) Combine Multiple Services to Increase Overall Capability or Capacity 2) Improved Resiliency and Disaster Recovery 3) Better Service Quality 4) Complex Architectural and Design Needs 8
9 Cloud SaaS SaaS Software-as-a-Service You pay for the application Apps accessible from various client devices Through a web browser For example: Salesforce.com EMC Mozy (Backup as the service) Google Apps [Source: NIST] 9
10 Cloud PaaS PaaS Platform-as-a-Service You pay for the platform software components Your applications are built on top For example: Google App Engine Microsoft Azure Force.com Platform [Source: NIST] 10
11 Cloud IaaS IaaS Infrastructure-as-a-Service You pay for the infrastructure components Your OS image and applications on top For example: Amazon EC2 EMC Atmos [Source: NIST] 11
12 Technology Big Data & Cloud Forrester Research 12
13 Technology Big Data & Cloud 13
14 Technology Big Data & Cloud 14
15 Big Data & Cloud 15
16 Technology Big Data & Cloud 16
17 Tools Big Data & Cloud Analytics Structured Data Unstructured Data 17
18 Conclusion Big Data challenges 1) Need for highly-scalable systems 2) Need for highly-available systems 3) Demand huge hardware investment Cloud benefits 1) Provide highly flexible and scalable systems 2) Provide higher availability for applications 3) Reduce costs Big Data + Cloud + Technology = Affordable Cost + Better Analytics + Competitive Advantage Explore Bigger Possibilities 18
19 Conclusion 19
20 References Forrester Reports on Big Data and Cloud Computing Gartner Reports on Big data and Cloud Computing EMC Internal Big Data and Cloud Computing Initiatives and Education IDC Reports and analysis on big data and cloud National Institute of Standards and Technology (NIST), Information Technology Laboratory ] Patricia Florissi, CTO, EMC Sales 20
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