The Fifth Elephant

The Fifth Elephant 2013

An Event on Big Data and Cloud Computing

(Skip ahead to session proposals)

In 2013, commodity hardware and computing capacity for storing and processing large and small volumes of data are easily available on demand. The bigger issues pertain to questions of how to scale data processing, handle data diversity, manage infrastructure costs, decide which technologies work best for different contexts and problems, and build products from the insights and intelligence that the data is presenting to you.

The Fifth Elephant 2013 is a three-day workshop and conference on big data, storage and analytics, with product demos and hacker corners.

http://fifthelephant.in/

Event format, themes and submission guidelines

The Fifth Elephant 2013 invites proposals on use cases and real-life examples. Tell us what specific problem you faced, which technology/tools worked for your use case and why, how you have developed business intelligence on the data you are collecting, and analytics tools and techniques you employ. Our preference is for showcasing original work with clear take-aways for the audience. Please emphasize these in your proposal.

The conference will have two parallel tracks on 12th and 13th July:

  1. Storage: OLTP, messaging and notifications, databases and big data, NoSQL
  2. Analytics: Metrics and tools, cloud computing, mathematical modelling and statistical analysis, visualization

Workshops

This year we are adding a preliminary day of workshops, on 11th July, to provide attendees more in-depth, hands-on training on open source frameworks and tools (Pig, Hadoop, Hive, etc), commercial solutions (sponsored), programming languages such as R, and visualization techniques and tricks, among others.

Product demos and sponsored sessions

We have a demo track for startups and companies who want to showcase their product to customers at The Fifth Elephant 2013 and get feedback. Slots are also open for 4-6 sponsored sessions for companies who want to talk about their technologies and reach out to developers, CTOs, CIOs and product managers at The Fifth Elephant. For more information on demo and sponsored session proposals, write to info@hasgeek.com.

Commitment to open source

HasGeek believes in open source as the foundation of the internet. Our aim is to strengthen these foundations for future generations. If your talk describes a codebase for developers to work with, we require that it is available under a license that does not impose itself on subsequent work. This is typically a permissive open source license (almost anything that is listed at opensource.org/licenses and is not GPL or AGPL), but restrictive and commercial licenses are also considered depending on how they affect the developer’s relationship with the user.

If you’d like to showcase commercial work that makes money for you, please consider supporting the event with a sponsorship.

Proposal selection process

Voting is open to attendees who have purchased event tickets. If there is a proposal you find notable, please vote for it and leave a comment to initiate discussions. Your vote will be reflected immediately, but will be counted towards selections only if you purchase a ticket. Proposals will also be evaluated by a program committee consisting of:

Emphasis will be placed on original work and talks which present new insights to the audience.

The programme committee will interview proposers who have received maximum votes from attendees and the committee. Proposers must submit presentation drafts as part of the selection process to ensure the talk is in line with the original proposal and to help the program committee build a coherent line-up for the event.

There is only one speaker per session. Attendance is free for selected speakers. HasGeek will cover your travel to and accommodation in Bangalore from anywhere in the world. As our budget is limited, we will prefer speakers from locations closer home, but will do our best to cover for anyone exceptional. If you are able to raise support for your trip, we will count that towards an event sponsorship.

If your proposal is not accepted, you can buy a ticket at the same rate as was available on the day you proposed. We’ll send you a code.

Discounted tickets are available from http://fifthelephant.doattend.com/

Dates

The program committee will announce the first round of selected proposals by end of April, a second round by end-May, and will finalize the schedule by 20th June. The funnel will close on 5th June. The event is on 11th-13th July 2013.

Hosted by

The Fifth Elephant
The Fifth Elephant
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
All submissions

Deepak Shenoy

@deepakshenoy

Money Talks: Analyzing Financial Market Data

Submitted Mar 26, 2013

Section: Analytics and Visualization Technical level: Intermediate

Financial markets produce a ton of data, but how can we look at them in useful ways, as compared to “looks-great-what-do-I-do-now”. By useful I mean to traders, to fraud-detectors, to investors and even to company management. Learn about the techniques of market data analysis from someone who’s done all the wrong things, sometimes in spectacular fashion.

Outline

Financial markets are action packed, fast paced dens of excitement constantly creating new stories and burying past ones, but what they produce is, essentially, big data. Every trade is out there somewhere, data is provided - free or at a cost - on how prices have moved, how companies have fared, how insiders have traded and how governments have reacted.

What I’m going to speak about:

  1. What kind of “raw” information exists: Prices, volumes, futures, options, bonds, currencies, commodities - the list is endless. Much of this is available around the clock, some of these can be traded from anywhere, and a significant percentage is traded purely through algorithms today.

  2. Analyzing the base information: From creating indexes, to “trading pairs” to “option strategies”, the idea of a big data strategy for markets is to create derivative data that is tradeable or provides outlier information that is required for action.

  3. The sucker theory: It’s easy to get all mathematical and assume that if we take any of these variables and find “correlations” we can automatically find patterns that will provide great profits in the future. Much about correlation is accidental, like the writing of shakespeare by enough monkeys with typewriters; in financial markets, correlation is even sometimes created to encourage suckers. I’ll speak of the pitfalls of such analysis.

  4. It’s often evident that fraud or manipulation is evident in market data; even in the Enron case or in the housing downturn in the US, the data actually revealed problems way before everyone else realized what was happening. A quick take on understanding what can be done with big data to weed out market fraud.

I’ll have a lot of time for Q&A, but if you want to speak on something specific, please post a comment.

Requirements

You should know something about financial markets like buying or selling of shares. It would be useful to have a basic idea of time-series analysis, like moving averages or statistical outliers, but it’s not mandatory as the talk will be in very simple language.

Speaker bio

I write about money, markets and trading at Capital Mind (capitalmind.in) and actively trade and educate people about financial markets. I am part of a new startup that will revolutionize analytics in macro-economics and bond markets in India. As a former geek, I have some experience in programming and plan to demonstrate how much of a fossil I now am. In my spare time, I like to climb stationary walls.

All submissions

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Hosted by

The Fifth Elephant
The Fifth Elephant
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