Big data - Introduction
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This is KZero entry number one about Lifelogging – and will definitely not be the last. Over recent weeks I’ve noticed a surge in tweets and media articles about this concept and it’s one that’s been on our radar for a while. Time to start peeling back the layers and examining what Lifelogging is and how it will impact our lives in the future. Lifelogging is essentially using technology to capture, record and store our lives, as we live them. These means the people we meet (what we see), the things we say and listen to (what we hear) and the places we visit (where we go). So far so good.
Laying out the foundations of Lifelogging : Kzero
Blogging, Microblogging, Lifelogging. Evolution? | KZERO - Blog
In the first KZero post on Lifelogging , I indicated that in a way Lifelogging was a natural evolution of how we publish ‘personal information’. The argument used is the first real mainstream form of persona data capture was (and is) blogging. People sitting down at their computer and writing a blog post (text and image based).
This post is part of our ReadWriteCloud channel, which is dedicated to covering virtualization and cloud computing. The channel is sponsored by Intel and VMware . Read the case study about how Intel Xeon processors and VMware helped virtualize 12 business critical database applications . Earlier this year we wrote about an infographic that visualized what 10 petabytes looks like.
Data Defined [Infographic] - ReadWriteCloud
Nope. . Up and down its ranks, Google executives will tell you without fail that Google is not a media company, that its organizes and manages content, but stays away from producing it. It’s an article of faith at the Internet giant. But it’s also beginning to show strain as Google moves into new territory. In February, Google announced a subscription service called One Pass to enable consumers to buy professionally produced news and information across the Web with a single click. And a great many new-media consuming devices featuring Google software called Honeycomb are about to come into the market, making that information all the more attractive and mobile.
How Google Is Evolving Into a Media Company - NYTimes.com
Editor’s note : Guest author Semil Shah is an entrepreneur interested in digital media, consumer Internet, and social networks. He is based in Palo Alto and you can follow him on twitter @semilshah Spend enough time in Silicon Valley, and of all the buzz words you’ll hear neatly tucked in with “graph,” “serendipity,” and “personalization” is one often uttered though, on the whole, not yet fully understood: “Big Data.” On the surface, everyone realizes the opportunity.
Big Data Needs To Think Bigger
Thoughts From the Man Who Would Sell The World, Nicely
"My background is in Artificial Intelligence and my last business was building predictive data. Most of our customers were oil companies, and you can hold that against me if you like. But my pitch back then was 'just give me enough data, I'll figure out something.' And often enough I did figure out something." That's how Houston-based 80Legs CEO Shion Deysarkar describes his background. Tonight his Web-crawling-as-a-service company will put up for sale tens of millions of data points extracted from public social networks and other websites.
Mamas, Don't Let Your Babies Grow Up to Be Data Wranglers
A web of infinite information : does that sound like a scary problem of "just too much"? Venerable blogger Om Malik and Twitter co-founder Evan Williams agreed in an interview today that it is. Williams, as a founder first of Blogger.com and now of Twitter, is probably more responsible for the explosion of social data online than any other single person. Luckily, not everyone feels the same way about this historical moment.In August of last year, a IT-centric research blog called Wikibon released a stunning infographic representing the total amount of data stored online in 2010. The astronomical figure cited -- 1.2 zettabytes, or 1 billion terabytes -- could have filled a stack of 16GB iPads (75 billion, to be precise) that would nearly reach the peak of Mount Everest. Other estimates have put the annual quantity of total information transacted (i.e. not necessarily stored) closer to 3 or 4 zettabytes. And those figures are growing by leaps and bounds each day. In the pre-digital era, storing information was costly and, not surprisingly, usually reserved for only what was perceived as the most critical data (e.g. astronomical observations, census calculations, commodity prices). The entire notion of publicly storing images, thoughts and records of the trivial moments in our lives (the raison d'être of Facebook, Twitter, Flickr, and the like) would have been incomprehensible just a few generations ago.
Surviving the Data Deluge: a Call to Action for the 21st Century
It sounds obvious that deciding what it is that you want to govern is essential - but information is a complex beast with many facets. I find it useful to think about the capabilities that I need to have. These are the basic parameters that determine my scope - and the nature of the challenges in delivering them. In my world of corporate business intelligence I believe that there are 26 capabilities related to information management. I like to group them into 8 categories:
Oz Analytics: Actionable Information Governance
Following up on my recent blog discussing the 26 capabilities that underpin Actionable Information Governance , I want to talk briefly about some organisational ideas that can help you deliver these capabilities more effectively. Once again, what I present is based on my experience and observation of what works with my practitioner colleagues. These ideas are based on my belief that leading the use of analytics in the organisation needs to be the business itself and that this leadership must be under the support of at least 2 C level executives. Finally, there should be a Centre of Excellence and two communities of practice:
Oz Analytics: Actionable Information Governance Part 2
Five ways to generate data
Adding something : The twin to taking something away is obvious, but there are plenty of novel applications. These include installing a new kind of thinking (e.g., CBT ), extending your social circle (introduce yourself to one new person a day), or changing your surroundings (how about daily trips to a museum to surround yourself with inspirational art?) Making the invisible visible : As subset of adding, I’m intrigued by structuring our environments to make something that’s intangible more noticeable. Applications of what’s known as an Information Radiator in Agile software development, these kinds of changes can take many forms.How To Make Data Actionable
In the olden days, the ability to collect, organize, and analyze massive amounts of data was largely the province of scientists working in academia, government, or private industries like pharma or biotech. Not so in the 21st century. Data collection and analysis is now a key competitive advantage for online companies from social networks to consumer shopping sites. It’s not just NASA that has a “Chief Scientist” anymore – LinkedIn, Yahoo, and Amazon have them, too. When it comes to running an online business (be it a blog, a network, or a store), data analysis has become an incredibly powerful tool and a bit of an obsession.Information Arbitrage - The Role of UI/UX in the Big Data Revolution
This week’s Strata Conference was a truly magical event for those immersed in the world of Big Data. Congratulations to Tim O’Reilly , Gina Blaber and the rest of the O’Reilly team for throwing a fantastic event. It was great to be a part of it and I’m looking forward to being deeply involved in the next edition, New York style.Data and Visualization: Predictions for 2011
A lot of my time these days goes into planning DataMarket ‘s efforts in the new year. An essential part of that is trying to grasp the major trends in areas that matter to us. DataMarket is building an active marketplace for statistics and structured data .How To Get Experience Working With Large Datasets
I think I have been lucky that several of the projects I been worked on have exposed me to having to manage large volumes of data. The largest dataset was probably at MailChannels , though Livedoor.com also had some sizeable data for their books store and department store. Most of the pain with Livedoor’s data was from it being in Japanese. Other than that, it was pretty static. This was similar to the data I worked with at the BBC. You would be surprised at how much data can be involved with a single episode of a TV show.Big Data - Ressources
Big Data - Taxynomy