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 the best #datascience and #machinelearning conference in Asia - is transitioning into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Rahul Deshmukh

@thedeshmukhs

Splunk> Driving Real-time Analytics from Small Data, Big Data and Huge Data

Submitted May 30, 2012

Hear how more than half of Fortune 100 companies drive value from their data and how Splunk is helping organizations.

Outline

Data is everywhere, but few organizations are deriving the full value from their data. Hidden inside the websites, application servers, networks and mobile devices that power the enterprise is critical information about website traffic, customer behavior, IT systems performance, cyber-security threats and more. How do you keep up with the velocity and variety of data streaming in and get actionable insights on it, all in real-time? What about correlating big data with data from social platforms and relational databases? In this talk, we’ll examine real-world examples from leading online, retail, telecoms and financial services organizations that offer a blueprint for integrating big data technologies, delivering new visibility and insights to IT and the business users and accelerating the adoption of big data in the enterprise.

Speaker bio

Rahul has a unique blend of Web Analytics strategy, Business Intelligence and marketing experience. Rahul is very passionate about the web and his areas of interest are web analytics, marketing strategies, optimization and KPI evaluation. He is currently Director - Web Intelligence Product Marketing at Splunk. Previously, he was Sr. Manger - Search Analytics at eBay. His team worked on analytics and optimization for Product Based Experience, Catalogs, Fitment, Classification, Verticals Search and Advertising. Prior to eBay, Rahul was an Independent Web Strategy consultant focused on Social Media. His past experience include Director of Analytics and Optimization for Ask.com. and Dell. At Dell, Rahul was responsible for the Web Analytics Tools Strategy for Dell.com (largest e-commerce site) which included identifying capabilities, KPI, functionality, vendor selection, and implementation of a Web Analytics tool. Rahul was also responsible for Competitive Intelligence (Hitwise, Compete.com, MSN Adlabs).
Rahul can be followed on twitter @thedeshmukhs

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Hosted by

The Fifth Elephant - known as one the best #datascience and #machinelearning conference in Asia - is transitioning into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more