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

Avik Sarkar

@avik

Combining Social Media Insights with Statistical Insights for Improved Analytics

Submitted Jun 25, 2012

Various facts are discussed about organizations and brands on Social media. How can the organizations incorporate the findings from Social Media to improve Analytics process like identifying customer churn or finding users to target in a new marketing campaign? This can help in real time proactive action by organizations to retain customers or improve customer satisfaction. This 360 degrees view would help organizations increase profitability and have happy customers.

This touches upon areas of Big Data Analytics, Data Analytics & Industry solutions

Outline #

In this session we discuss few real customer use cases to first extract the insights from Social Media (comments in Facebook, Twitter, blogs) using text mining on Big Data platform. Then we discuss the probabilistic approach to combine the social media findings with the in-house customer records. The combination of social media insights along with the customer records are used for improved prediction. These predictions can then be used to target action in real time to customers.

Analytics Tools used for these scenarios are: IBM SPSS Modeler, IBM Big Insights, Cognos Consumer Insight, SPSS Decision Management, SPSS Data Collection

Requirements #

None

Speaker bio #

Avik currently holds the position of Senior Architect in Predictive Analytics and Data Mining at IBM working on developing algorithms for SPSS and Predictive Analytics based industry assets. Avik is also involved in collaborative academic research in Geographical Information Systems and Big Data Analytics. Avik has over 12 years of experience in the areas of Predictive Analytics, Data mining, text mining, statistical modeling and related areas across verticals like telecommunication, retail, manufacturing, hi-tech, environment, insurance, economic forecasting, etc.

Avik received his Bachelors in Statistics, Masters in Applied Statistics & Informatics from IIT Bombay and PhD in Computing & Data Mining from UK. Avik has authored several technical publications and technology patents.

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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