Course Outline:
Day 1: Private Cloud Focus (OpenStack)
Description:
Day 1 focus will provide overview state of the art topics in how companies are building hyperscale data centers using the new open source technologies OpenStack. OpenStack dramatically reduces the cost and speed of deploying a private cloud that is build using inexpensive, off the shelf infrastructure. The sessions will also provide insights into what big data is and how companies can learn and assess the opportunities provided by big data. There is an entire ecosystem and framework that makes OpenStack and Hadoop the key disruptive technologies that will transform how data centers are deployed and how companies use their data for strategic advantages.
The content will address key questions such as:
OpenStack
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What is OpenStack and how can I use it in my organization?
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Are there fully integrated and tested end to end solution that I know works?
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What are the different options of deploying OpenStack?
Module 1:
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OpenStack history and background
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Differences between the existing virtualization technology in the market that enables public and private cloud?
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What is the trend in US and Silicon Valley nowadays in terms of Cloud direction?
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Top reasons why company choose OpenStack over other virtualization technology?
Module 2:
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A case analysis on the cost saving using the right Virtualization and the right Hardware infrastructure to gain the best TCO.
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What application in the Silicon Valley are mostly seem integrated with OpenStack?
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What is the industry future of OpenStack?
Module 3: Lab Session (2pm-3:20 on Friday afternoon)
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Demonstration of Provisioning super scale VM (2014 Edison Award - RESEARCH & BUSINESS OPTIMIZATION models)
Module 4: Hands on Lab Session and VIP Q&A session (3:30-5:00pm on Friday afternoon)
Day 2: Big Data Focus:
Description:
Day 2 executive level seminar will review state of the art topics in big data to understand what it is and how companies can learn and assess the opportunities provided by big data. Hadoop has become the standard for analyzing big data, but it is not just a single application. There is an entire ecosystem and framework that makes Hadoop a massive big data analytics platform with many options.
The content will address key questions such as:
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What is Hadoop and why has it gained so much adoption to analyze big data?
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What are practical, real-life problems that can be solved using Hadoop?
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What are some of the challenges faced by the largest Hadoop deployments at companies such as Facebook?
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How do I create a data center architecture that can scale for optimal performance?
Module 1:
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Hadoop history and background
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Differences between Hadoop and traditional data analytics or business intelligence applications
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How does Hadoop scale to process so much data
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Top problems Hadoop can help companies analyze and understand better
Module 2:
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Hadoop ecosystem
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Key components of Hadoop
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How does Hadoop work?
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Hadoop reference architecture
Module 3:
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Data center architecture considerations for Hadoop
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State of the art technologies for building scalable data center infrastructure
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Building data centers that can scale out vs. scale up
Module 4:
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Developing a big data strategy that is right for your company
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Examples of real world problems that can be solved with Hadoop
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Financial services
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Telecommunications
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E-commerce
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Retail
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Network management
Module 5:
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Keys to developing an effective big data strategy?
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When is Hadoop not a good choice?
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Where do I start?
Module 6:
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Building a data strategy
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Building a capability roadmap to iterate to value to the most valuable business issues
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Technology considerations
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Recap and conclusion
For More Information, Please Contact:
Phone: +852 63885595 / 64982323
Email: info@cloudoceantech.com
www.cloudoceantech.com
www.itu.edu/bigdata
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