If you’re a regular reader of GigaOM you know that we’re big believers in the power of data — both big and, well, bigger — to change the way we think about our world. Until relatively recently, it hasn’t been possible to gather enough data at scale to truly understand the patterns around us. But as our smartphones turn us into walking sensors and we live ever-increasing amounts of our lives online, we’re generating massive amounts of data that can improve the health of a business (or a person), help us make rational decisions about resource prioritization and finally convince NFL coaches that they should go for it more often on fourth down.
The key is developing the tools and techniques to properly collect, harvest, and analyze that data. On Wednesday and Thursday this week, we’ve gathered some of the top minds in this emerging field in New York at Structure:Data to help you understand how data and data analysis can improve your business and your life. They include Paul Maritz, chief strategist at EMC (s emc) and a leader of The Pivotal Initiative; data experts from companies like Facebook, (s fb) Microsoft (s msft), IBM (s ibm) and a host of startups; and even the CTO for the Central Intelligence Agency, Ira “Gus” Hunt.
More information about the conference can be found here. If you can’t join us in New York, follow along with the livestream here, or join the conversation on Twitter with #dataconf. We’ll also post a roundup of all our coverage from what should be a very interesting two days of data.
Wednesday:
- Forget FICO: how data is changing the rules of credit and underwriting
- Kleiner Perkins’ Michael Abbott: It takes two (teams) to build a successful app
- Without human input augmentation, algorithms alone are making us dumber
- SDN can turn the network into a big data “curator,” claims Juniper
- It’s not Skynet yet: In machine learning there’s still a role for humans
- Data science is not enough. We need data intelligence too
- If you think big data is big now, just wait for the internet of things
- EMC’s Paul Maritz: it takes leadership to move companies toward a data-driven future
- How Aetna uses patient data to prevent diabetes and heart attacks
- Even the CIA is struggling to deal with the volume of real-time social data
- How coding contests can be better at solving problems than Harvard
- For big data achievements, IT and analysts need to work together
- Big data is still hard, but it gets better
- From Amazon’s top data geek: data has got to be big — and reproducible
- Beyond the Like button: Putting social networks to work for us
- Do we need internet exchanges for public cloud data portability?
- People will give up their personal info if you give them a good reason
- Six ideas from entrepreneurs for solving your big-data problems
Thursday:
- Why Nuance sees the semantic web as a key to smarter natural language interfaces
- Big data analytics is great but it’s no a silver bullet
- It’s not enough to just have information — intelligence requires context
- Hadoop: “It’s damn hard to use”
- Want a bigger/greener/more agile data center? Use the data
- Getting beyond the cult of big data
- How search can solve big data problems
- Hadoop applications abound, but Hadoop still needs improvement
- If the future of BI is Hadoop, SQL and the cloud are the glue
- Why Guavus analyzes lots of telecommunications data before storing it all
- Pursuing big data utopia: What realtime interactive analytics could mean to you
- Nasdaq on the virtues of the public cloud
- No, not every database was created equal. Here’s how they stand out
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