Tag: GigaOm

  • The questions in Big Data

    In my last post that touched upon Big Data, I had mentioned how the seeming intent of Big Data is to synthesise actionable insights from processed and unprocessed information at touch points related or unrelated to the enterprise, and then use it to target consumers better. While this is probably true for the short-medium term, I read a wonderful perspective at GigaOm by Beau Cronin on its true potential – the path to building the equivalent of global-scale nervous systems. As I tweeted after I read it, it reminded me of something I’d written a couple of years back before I’d heard of #BigData – if we could actually use data to go beyond that to answer life’s profound questions. Before we go into the subject, here’s a nice video by OgilvyOne titled “Big Data for smarter customer experiences” (via) though it’s skewed more towards the experience rather than the data.

    Beau Cronin has mentioned several possibilities this would give rise to, and the post made me think if something like the hive mind concept would mesh into it as well – a sort of hybrid neural network. He has also pointed out the hurdles we would face while we get there – gathering, processing and conversion into actionable insights, and how phenomena such as priming,expectations, and framing matter so much in how we perceive our physical and social environments. In essence, a fascinating read.

    I was particularly intrigued by framing, and began thinking about it in the context of the unstructured data – tweets, posts, mails, videos – that is a major component of Big Data. The fundamental question being – is it unstructured because we’re framing it ‘wrong’? Based on the enterprise’ intent and not the users’? Ironically, I couldn’t frame the questions right until I met the ever-brilliant S, who has always maintained that the answer is easy to find once the question has been framed right. He has developed (Tulpa -to build or construct in Tibetan – is the concept he enlightened me on while we were discussing semantics) something that at a rough level mashes the MECE principle with Frame Semantics and the entity-relationship model. There’s IPR involved, so no more beans shall be spilled, but as always, I learned much from the conversation.

    In essence, structure can definitely be derived from what we currently call unstructured data, provided we frame the queries right. I can intuitively begin to understand that in the era of data abundance, the only way we can make sense of all of it is by focusing on an intent that is derived from a common purpose, so that the sources of data (users) will be more open to help solve the challenges of data collection. The processing and inferences that follow would yield the best results when the right questions are asked. I have a feeling that the questions asked by a business in an earlier era might not cut it.

    until next time, role models

  • Brands and the Personal API

    Lifestreaming and I go way back, at least 5 years. 2008 was when I wrote about it first, though the experiments had started earlier. Most of the services I’ve mentioned in the post are now defunct, but my interest in the subject never waned. From the perspectives of memories mentioned in that post to speciation to brands using their lifestreams to build communities around it, I have had several thoughts on the subject. That’s why I found this post at GigaOm, which was about Foursquare co-founder Naveen Selvadurai sharing data logs from his life (weight, sleep, activities) and hoping developers would hack his ‘personal API‘, very very interesting. There have been stories about people and the tons of lifestreaming data they have amassed, but I had never heard of an API, and therefore consider it pioneering work.

    Pioneering, less because of the novelty, and more because I think it has the potential to become mainstream, and even, the default paradigm of creation and consumption. Since the engagement @ scale framework refuses to let go of me, I immediately thought of the personal API in that context. With technological advances, I think it’ll become easier to create one’s own APIs and you can see several companies mentioned in the GigaOm post that are working on it. So I’d hope that its evolution is as fast as (or faster than) that of self publishing (on the web) which about a decade back was a relatively complex thing to do. So, in essence, we’re talking about huge amounts of data that are being generated and captured by individual users, and this is only going to be accelerated thanks to phenomena like wearable technology.

    The current way of looking at Big Data is to synthesise actionable insights from processed and unprocessed information from touch points related or unrelated to the enterprise. As I’d mentioned in my presentation (on engagement @ scale) this is then used to target users better or drive more efficiencies.  They don’t really operate at the higher levels of community/meaning/purpose. Now think of the personal API and the data it holds. What if we looked at this individual streams of ‘Big Data’ not from the enterprise’ perspective but from the user perspective? What if brands created platforms that  would allow people to upload data that they choose to so that the brands could solve their needs better? Like I wrote in my ‘maker’ post, with massive technology leaps happening in areas like 3 D printing, there are tremendous opportunities for co-creation. Brands could even aggregate data from these individual streams to find need gaps and package that for a larger market. In fact, I’d say that this is probably what Nike+ is doing already.

    But the real story is that these personal APIs could give great insights into the individual’s purpose in life, his priorities – in short, his life’s narrative. It gives brands the window to latch on to the narrative that they can identify with, and create value and meaning in the individual’s life. I think that’s what brands originally strove to do!

    Update: Thanks MJ, for pointing me to the Nike+ Accelerator!

    until next time, AP”I”

    PS: Over at Soylent, they’re creating the nutritional equivalent of water, an ubiquitous ‘meal’ that is customised for body types. Funding? Kickstarter of course! 🙂