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This Is How You'll be Crunching Big Data Next Year

"Big Data" has been one of the most overused and hyped tech terms of the past year, but the reality is that massive scale data analysis technology is quickly evolving to become more accessible and useful. The process of hacking together clusters of machines or VMs, and managing distributed analytics software is maturing into high-performance, on-demand data services that can be incorporated into existing apps. New data analytics APIs allow mobile and game developers to process large amounts of data more quickly and cheaply than ever, with no upfront hardware costs. Small startups are able to gain important insights into customers and products by analyzing data using hosted services. Previously, they may have thrown away that data, not having the cash and expertise necessary to take advantage of it. We'll take a look at large scale data analysis trends that are becoming the norm, share stories of actual start-up success, and take a look at the future of the "Big Data" application field.


  1. What are the major pain points associated with collecting and analysing large amounts of data?
  2. What are the major trends in Big Data analytics technology?
  3. Why should a small or medium sized start-up care about Big Data "platforms as a service"?
  4. What are some of the questions that start-ups have been answering using next generation, hosted, and real-time data analysis technology?
  5. How can I incorporate new Big Data technology into my own applications?



Michael Manoochehri, Developer Programs Engineer, Google, Inc.

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