- Ask HS: What's Wrong with Twitter, Why Isn't One Machine Enough? http://t.co/YC6XrmBtof ->
- CIA cloud battle redux? U.S. defense agency puts cloud work out to bid http://t.co/3jeqBvY2oT via @gigaom ->
- Stealthy In-Q-Tel stakes HyTrust to lock down intelligence clouds http://t.co/CHlnGpa10c via @gigaom ->
- N.S.A. Leak Puts Focus on System Administrators http://t.co/zEJ7kOxwG4 ->
- VMware sell-off continues as it offloads Zimbra http://t.co/KKENlwOHfe via @gigaom ->
- VMware co-founder Diane Greene has a stealthy new startup. Here are the details http://t.co/2ZQGXeP7HX via @gigaom ->
- Hyperloop? http://t.co/Z0FwfJRhuv ->
- Elon Musk will soon unveil design for the Hyperloop, which promises travel from SF to LA in 30 minutes http://t.co/WxcyU1I4br via @gigaom ->
- Build Your Own Web or Mobile App In Minutes With These Cloud Based Tools http://t.co/9F8dsPAcY3 via @forbes ->
- Top 11 Mobile Web Development Tools Used at Mobify | Mobify http://t.co/YgL4ttoo0K via @mobify ->
- Modern Twitter infrastructure. http://t.co/fUtIPVaUMT ->
- In medicine, data Darwinism becomes playing god http://t.co/Cz0FAsaBHS via @gigaom ->
- Pinterest rival The Fancy gets $53 million from Will Smith, American Express; valued at $600 million http://t.co/K2X1wxgYwV via @gigaom ->
- Forget servers; One day Facebook, Google and other web giants will make their own custom chips http://t.co/VBd2xdOBQk via @gigaom ->
- RT @neiltyson: Whenever you give a cross-street, a building floor, and a meeting time, you’re handing someone a 4D coordinate in space-time. ->
- I’m not sure MSFT can rally and compete as with 90′s Internet. They ignore their customers so badly. http://t.co/KjfLrAvGD6 ->
- How Ray Kurzweil Will Help Google Make the Ultimate AI Brain | Wired Business | http://t.co/gEB50KPNx6 http://t.co/XcyqCyfL7l ->
- As traditional PC sales and chipmakers slump, ARM rakes in the cash http://t.co/hfUnCBvac6 ->
- DARPA tools for designing vehicles. http://t.co/hyEiDIRPm8 ->
- Tankcraft: Building a DARPA tank online for fun and profit http://t.co/kq0OU7eWA2 ->
Another great paper from Google. if it worksfor them, its probably worth copying. Particularly appreciated the Brighthouse reference.
Big Metadata is my phrase for the application of Big Data tools and techniques to the larger ecosystem of data surrounding business software. While Big Data is focused on unwieldy data sets at large firms or new-technology companies, Big Metadata is about every company or organization taking advantage of the massive amounts of relevant metadata that is completely ignored.
Business software only capture the bits of each transaction that will calculate changes in such things as inventory, bank accounts, and production. This reductionist view of each transaction is disconnected with the reality of daily business: full of exceptions and rewrites and human conversations. Just as consumer software is making strides in conforming to our habits and needs, business software should capture the reality of business and not enforce an ideal.
How we got here is simple. The constraints on storage, processing, software development and error checking left us focused only on critical features. We now design business databases to be as narrow as possible. We write code to run the system for today and struggle to reconcile original decisions as processes, people and the whole business landscape continues to change.
When we talk of business software being more human, more predictive, and more like the consumer software we experience from Apple and others, I think we are looking for the same kind of Big Data solutions that come from Google, Apple, Amazon, and Facebook. These are solutions based on massive amounts of data, good choice in analysis factors, and a sprinkling of algorithm and statistics.
There are clear individual business uses for social networks, voice and gesture recognition, cloud infrastructure, schema-less databases, in-memory storage, distributed algorithms, graph processing, domain-specific languages, development frameworks and other technologies. I believe the combination of these technologies to solve the common challenges in business will fuel the next great wave. My hope is to sketch out the future of business software.
Ouch… A Google+ product manager on why he left… Money quote: I couldn’t even get my own teenage daughter to look at Google+ twice, “social isn’t a product,” she told me after I gave her a demo, “social is people and the people are on Facebook.”
“With enough data, you can discover patterns and facts using simple counting that you can’t discover in small data using sophisticated statistical and machine learning approaches.” Link
I used to assume that big data and data mining and statistics were inseparable. But the reality–companies making a killing transforming data into value–is far from complex.
Big data is not hard. Statistics are not required. Neither are complex algorithms. Google’s Marissa Mayer attributed the company’s intelligence to the volume of data available for cross-referencing and not to clever algorithms. Google translate leveraged massive volumes of cross-referenced text in multiple languages rather than a finely tuned understanding of grammar. Voice translation uses much the same technique based on huge volumes of recorded, transcribed text.
Right now our two best tools are visualization and data exploration (business discovery). Both are simple, easy to demonstrate and easy to grasp. The big data revolution’s message to the masses is that simple correlation will outstrip them both as long as enough data can be crunched. And much of this can be automated, pre-calculated, and even anticipated. Imagine the analysis system analyzing itself: these people tend to ask these questions at these times!
Data can be correlated post-hoc. Correlation does not equal causation, but simple correlation is ample evidence on which to take action. Correlation is immediately perceived visually. Correlation is relative and easy to compare. Correlation can look at 2, 3, 4 or more factors at once. Correlation is business friendly. It is easily understood. Correlation is gut-instinct compatible. Kids understand it: mom gets upset when I put peanut butter on the cat. If I do it right now, she’ll probably be mad.
The business opportunity is really that so much big data is simply thrown away. The opportunity to store all this data didn’t exist, so we have an old habit of simply letting it vaporize. Every server message, every website click, every customer contact and interaction, every manufacturing activity, temperature, timeclock action, phone call received, phone call placed, security video, email sent. Every bit of data can be analyzed, and from multiple perspectives: employee, employer, customer, vendor, shipper, receiver, and on and on.
We don’t know what we’ll find. As more and more stories of big data at little(er) companies emerge, the snowball will become an avalanche.