Data 2.0 Summit: Live Coverage
Thank you everyone for joining us at Data 2.0! Hope you enjoyed it as much as we did!
LIVE UPDATES (in Pacific Daylight Time):
Panel: Democratizing Data: A Business, Technology and Society Problem
Geoff Domoracki (Data 2.0), Diego Oppenheimer (Microsoft), Alan Keahey (IBM), Brendan Wallace (Identified), Gil Elbaz (Factual), Bruno Aziza (SiSense)
"Can we imagine a world where apps take care of all the work and all the consumer has to deal with is a search box?" - Domoracki
"In our education system, there's a lot more emphasis on calculus than statistics but statistics is much more prevalent and useful in today's economy." - Oppenheimer
"Doesn't more powerful data mean more policing? Whose responsibility is it to police data: the end user or the provider?" - Domoracki
"It's not simply data analytics, but instead, you are always having a conversation with data. You have a community that is discovering and manipulating datasets who you have to talk to." - Keahey
"Accessibility is just the beginning of accessibility." - Oppenheimer
"With more data comes less integrity." - Wallace
"Or because more data is available, do we have to be more truthful in what we say or post?" - Aziza
Lightning Talk: Big Data and Focusing on People - Steve Sims (Badgeville)
Big data analytics is often too macro. People generally do things for four reasons:
1) To feel smart
2) To be successful
3) To feel socially valued
4) To have structure
Figure out what data corresponds with which intrinsic human desire and change your platform accordingly.
Lightning Talk: In Machine Learning, Simpler is Not Always Better - Beau Cronin (Salesforce)
Machine learning = refinery. It's not a finding a needle in a haystack challenge; it's turning low-quality data into something that's higher value. Machine learning attempts to take bits and pieces of the world and make it into something more real.
Fantasy World vs. Real World vs. Realer World:
Lightning Talk: Who are Causes' users? An exploratory analysis - Sara Vera (Causes)
Using K-Means clustering, Causes figures out who is active in what causes, to give them faces and personalities. They use this data to engage users with tailored approaches. Customization!
Panel: Web Standards: Myths and Realities
Geoff Domoracki (Data 2.0), Tantek Celik (Mozilla), Greg Lindahl (Blekko), Joshua Koran (Turn), Jordan Medelson (CommonCrawl)
Where have web standards outpaced the market's willingness to adopt universal methods, and where is there true demand for the coordination of new web standards?
There are good and bad examples of every standard that exists. There is no one vision of how the web works, but rather, its about what your company seeks to gain from web services. Look at competitor sites, see what they all have in common, and start building from there.
The Future of Data-Driven Business - Ken Wincko (Dun & Bradstreet)
Companies are always looking for new ways to get ahead. Business Analytics is the most heavily funded department for several years running now. It is crucial that businesses develop a complete and informed view of prospects, customers, competitors, suppliers and partners - the whole ecosystem - through relevant data an analytics. You have to be flexible and insightful.
Lightning Talk: Using APIs to Get Focus on Big Data - Richard Pulliam (Layer 7 Technologies)
90% of value is greated by internal use of an API. Common problem with APIs: How do you create aggregate views for all the things people do with your API?
Lightning Talk: Intro to Fitbit and Consumer Health Data - Christine Brumback (Fitbit)
Fitbit makes health a competition and helps monitor your daily activity. Using this data, they create apps that help users stay motivated and get healthy.
Lightning Talk: Picturing the Web of Discussion - Sam Parker (Disqus)
Very cool visualization of discussions across the web!
11:35am: Finally, a lunch break!
How Social Data Will Shape the Enterprise - Cameron Evans (Socialcast by VMware)
Socialcast is brand new (two weeks old) and aims to make communication, sharing documents, and collaboration easier. Utilizing social data will help us make social capital decisions. Use data to not only make the right decisions, but to avoid making the wrong ones.
Lightning Talk:The Future of Data - Bruno Aziza (SiSense)
1 TB in 1980 cost $14 million. We're still doing a poor job of using hardware today. Also, we only adopt 24% of the solutions that we build, and there aren't enough data scientists to produce the solutions that meet the hire expectations of businesses today. The goal is to make big data easier to store and analyze in order drive up the creation and adoption rates of data solutions.
Lightning Talk: Can Data Science Reall Do That? - Anthony Goldbloom (Kaggle)
Data is everywhere
Lightning Talk: Milking Data-as-a-Service for All It's Worth - Gil Elbaz (Factual)
Dairy industry is worth $350+ billion and growing. So what can we learn from this huge industry? There's incredible metadata on milk. You always know how fresh the data is, but that's not the case with a lot of data. Using APIs to connect to dozens of data services (e.g. social media, analytics services) helps create metadata for your information.
Panel: From Climate Data to Technology to Solutions
Ucilia Wang (GigaOm), Adam Rein (MissionPoint), Daniel Goldfarb (Greenstart), James Strittholt (Conservation Biology Institute)
What makes a good data-based decision? It's a mix of reliable data, insightful analytics and finally, good graphics and visualizations to present to the decision makers.
There's a booming market for novel analytics technology that applies to companies doing older, more traditional things. For example, data analytics has done a lot for wheat farmers as to when and where to plant seeds, and how much to water different fields.
Spotlight: Layer 7 Technologies - leading provider of security and management products for API-driven integrations spanning the extended hybrid enterprise
"90% of existing data has been created and stored in the last 2 years."
Spotlight: Disqus - a global comment system that improves discussion on websites and connects conversations across the web. The comment system is on 2.5 million sites all over the world, 1 billion unique visits with 20 million comments every month in 40+ languages.
9:38am: "The need for quality data is more prevalent than ever, and we are moving from relying on the government to democratizing the creation and collection of such data. We provide a platform for those who are out there doing things." - J. Strittholt
9:15am: Keynote by James Strittholt, PhD, Conservation Biology Institute
Data Basin:a science-based mapping and analysis platform that supports learning, research, and sustainable environmental stewardship.
Fasinating use of Data Basin to analyze drought: 2008 vs. 2012. Is the 2012 drought a catalyst for 2013 flooding?
9:00am: We are live at the Summit! The theme: Democratizing Data.
Good morning from the Golden State of California! I am at the Data 2.0 Summit in San Francisco, where entrepreneurs, executives, investors, and thought leaders are gathered to discuss the intersection of Big Data, Social Data, and Cloud Data. There's a solid lineup of speakers, panelists and workshops that I hope to bring to you so keep refreshing your pages for updates throughout the day. We're trying something new and bringing you live coverage of a great event! The summit runs from 12pm to 8:30pm EDT. Tweet @SmartDataCo or comment on this post if you are interested in hearing more about any particular speaker, workshop or panel, or if you have questions.
Cindy Weng is the Digital Community Strategist at SmartData Collective and is also pursuing her Ph.D. in Media, Technology and Society at Northwestern University. Her interests and areas of expertise lay in the technology sector, particularly big data, predictive analytics, social media and network analysis.
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