The Fifth Elephant 2012

Finding the elephant in the data.

What are your users doing on your website or in your store? How do you turn the piles of data your organization generates into actionable information? Where do you get complementary data to make yours more comprehensive? What tech, and what techniques?

The Fifth Elephant is a two day conference on big data.

Early Geek tickets are available from fifthelephant.doattend.com.

The proposal funnel below will enable you to submit a session and vote on proposed sessions. It is a good practice introduce yourself and share details about your work as well as the subject of your talk while proposing a session.

Each community member can vote for or against a talk. A vote from each member of the Editorial Panel is equivalent to two community votes. Both types of votes will be considered for final speaker selection.

It’s useful to keep a few guidelines in mind while submitting proposals:

  1. Describe how to use something that is available under a liberal open source license. Participants can use this without having to pay you anything.

  2. Tell a story of how you did something. If it involves commercial tools, please explain why they made sense.

  3. Buy a slot to pitch whatever commercial tool you are backing.

Speakers will get a free ticket to both days of the event. Proposers whose talks are not on the final schedule will be able to purchase tickets at the Early Geek price of Rs. 1800.

Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Joseph Ziegler

@jiyosub

Big Data and the Cloud a Best Friend Story

Submitted Jul 6, 2012

Communicate the challenges of big data processing that the cloud addresses, such as public data sets, sharing, collection, storage and analytic.

Outline

I will show how cloud infrastructure coupled with open source software is enabling the collection, sharing and processing of big data. I will have specific case studies on organisation that are now enabled to collect and use this information, how they are using it and what problems they are solving. As an evangelist for Amazon Web Services, I am able to work across many organisation using the cloud within big data and am on the front lines of this massive disruption.

Requirements

Proposing this as a plenary address.

Speaker bio

Joseph Ziegler

Technology Evangelist for Australia & New Zealand

Joe started his life in Texas but began his career in Silicon Valley. Previously, Joe worked at Accenture in San Francisco with Netscape amongst his clients. He developed some of the first e-commerce applications during the early days of the Internet and ran several start-up companies, including his first classic IPO on the NASDAQ. His most recent thriving venture is Iris Data Services, which landed on the “Forbes 500 Fastest Growing Companies in the US” list.

Joe started using cloud services in 2006 to create the infrastructure for Iris Data Services as the Director of Technical Services. Additionally, he worked with several enterprises developed on the cloud, including building his own company, IndexMedia, on Amazon Web Services. Now he has enthusiastically become an evangelist for Amazon, speaking about the services and features available to customers.

Joe has lived on five continents and enjoys meeting people in different parts of the globe. He likes long-distance running and spending time with his family, including his retired greyhound Flash, at his home in Melbourne, Australia. He has studied Mandarin Chinese, Japanese and Korean.

Joe earned his degree in Computer Science from Texas A&M University and an MBA from The University of Texas at Dallas.

He can be followed at his twitter handle @jiyosub.

Links

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Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more