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"The Big Data Landscape" with Radhika Subramanian, CEO of Emcien

The Big Data Landscape: Storage, Analysis & Reporting

These are great times for data. Big data and complex data are being queried, manipulated, and visualized at a scale that was unimaginable only a decade or so ago. We are flooded with Big Data success stories, and the number of successes continues to grow. Advances in data are helping us understand how diseases are spread around the world, while companies like Pandora can accurately predict political leanings based on musical tastes.

Each of these advancements are impressive, but they obscure a growing problem. The scale of data collected and stored continues to grow. Not only does our ability to collect data increase, but sensors and data collection are seeing their way into more devices every day. RFID tags, network logs, vehicle reporting, and satellite data contain information crucial to improving our work and our lives, so we collect as much of it as we can. In contrast to this growing stockpile of data is our collective ability to make sense of it all. To date, existing technologies have focused on creating a store of data and then querying it in specialized query languages. Visualization tools made great advances on this process by removing the language requirement and allowing users to work through a more human interface, but the basic process remains the same. These analytics technologies, traditional or visualization, allow analysts to understand their data by asking one question at a time. Each new technology that is built within this paradigm can only make the process for querying data faster.

The rate at which our data stores continue to grow is far outpacing our ability to create and run queries. And no serious Big Data thought leader has any expectation for this explosion of data to slow and so the gap between what we can collect and what we understand continues to grow. Until new methods that analyze and extract patterns from large and complex data sets automatically are implemented, this gap will become bigger and bigger.

Meeting Details:

The meeting will begin at 6:30pm allowing members time to network, arrive and enjoy pizza. At 7pm, BDUG will give an introductory welcome, and will be shortly followed by the presentation. After the presentation everyone has the option to head downstairs to Aja (restaurant and bar in the building) for networking and drinks after the meeting.

Important Note:

Parking at the Alliance Center is $10 max. If you wish to go to Aja after the meeting they will validate part of your parking. If parking is a problem, some members park at Phipps Plaza for free and walk over. BDUG does NOT validate parking.

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  • Sudhir A.

    Thanks Radhika for the wonderful session. It was really mind blowing and now gives a very good idea about not only about Big Data but also what Data Scientist do "sorry!!!! "Are supposed to do"

    June 13, 2014

  • Tom G.

    Enjoyed getting Radhika's perspective on Big Data and the role of the data scientist

    June 13, 2014

  • Hosie W.

    Really enjoyed Radhika's big stack model of addressing big data analysis.

    June 13, 2014

  • Tom G.

    Excited about learning more about customer needs and requirements. Check this out:

    June 9, 2014

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