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Radhika Subramanian
  • Atlanta, GA
  • United States
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Profile Information

Emcien Corporation
Job Function:
Business Analytics, Data Mining, Web Analytics, Vizualization
Computer Software
Short Bio:
Radhika is CEO at Emcien Corporation, a software company that offers a suite of solutions built to automate the data analysis process.
LinkedIn Profile:
Networking, Recruiting

Radhika Subramanian's Blog

Predictive Analytics and Sensor Data

Posted on July 2, 2014 at 2:48pm 1 Comment

Large scale equipment for power generation, manufacturing, mining, and similarly sized functions are structurally important to the global economy. They turn raw materials into the energy and other products that help keep the economy running.

Consider the gas-turbine electric plant. These installations can involve multiple instances of large scale gas turbines like those manufactured by General Electric and Siemens, and they can supply power for thousands of homes and many jobs.…


Hadoop in the Big Data Stack

Posted on June 11, 2014 at 8:30am 0 Comments

What is Hadoop? It’s another wacky name for an open-source software project, but Hadoop was also a significant advancement in the way that companies, governments, and organizations can collect, store, and process data. Companies like Cloudera, Hortonworks, and others have emerged to deliver professional level, Hadoop-based data solutions for the enterprise, while many organizations have built successful Hadoop implementations on their own.

Where the traditional model for data storage…


Learning to Predict Death with Big Data

Posted on June 3, 2014 at 2:26pm 0 Comments

Emcien founder and Chief Scientist Dr. Roy Marsten contributed this piece to Wired. Read the original Big Data article here.

Death. Many of the discussions around data revolve around death. These discussions are typically pretty mundane. Why do phone calls die? Why do banks go out of…


Big Data Lessons from the NFL Draft

Posted on May 12, 2014 at 1:00pm 0 Comments

The great myth of Big Data is that it’s defining characteristic is size. In spite of the warnings about Variety and Velocity, in addition to every other V-word out there, the world has been obsessively focused on the collection of bigger and bigger data. But the key to extracting valuable information from data isn’t actually the size of the database, but your ability to make the most out of the data that you have.

In the NFL, scouts don’t simply identify talent by…


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