Here Comes the Data Wave
Playing the "stealth mode" game is a little difficult. We've been up and at it since mid last year, quietly collecting a loyal following of users for both our live and private beta offerings. Now the market seems to be all about "data". The timing is perfect. And so, here comes the tide. Firstly, we're actually somewhat honoured that there are a few other ML (machine learning) sites out there who've followed -- almost verbatim in some cases -- our design and feature set. It's heartening and reassuring. Secondly, we're excited to see the number of cool contributions to the ML community from some extremely talented people, our folks included. It helps evangelize the entire mindset and approach to data, which leads us into the next point: big data. For the brick and mortar businesses, this phrase won't hold too much weight or value -- neglected are those businesses who aren't purely IT-based or focused (that was very Yoda sounding, wasn't it?). The aim is to take the water to the horses: bring the value to the user as opposed to throwing up a tool and expecting people to come to it. Yes, all activities generate a lot of data. But, it needs to be:
- recorded somehow;
- accessible by the productivity and logistics apps and workflows that make the business or activity operate: not so easy if you take a moment's pause to think about it;
- analysed: this means setting goals and knowing what questions to ask. Again, from the end user's point of view, this isn't obvious.
You get the point. Surely this raises related questions about the target markets for big data and machine learning, and demographics and capabilities of those demographics, verticals (and all those annoying business terms that make scientists squirm). But we think that if people are entering this market and intend to make a dent in terms of providing actual value that allows, enables and empowers (beyond just, say, creating a report on how many widgets I manufactured), those questions need to be considered quite deeply and very, very seriously. As PIFIQ, we're frankly beyond the age of reporting platforms -- they have their place, but are only one piece of a much larger puzzle. If you're an enterprise, you won't need luck because you can afford to fight battles with 'corporate buy-in' of reporting platforms and their ilk. Unfortunately, most SMBs in the new economy cannot afford to operate as such. They need to operate faster, with a more global reach and figure out what works and what doesn't and why. This means recording sheaves of data and sifting through it -- or using a black box and getting advice out of it. Period. There may be a big wave of data, and the hype will only pan out with the aid of pervasive data recording mechanisms for a wide range of markets (yes, yes privacy is a concern...but that's for another post!). Otherwise, big data and large scale analysis providers will only be fighting over a narrow portion of IT-based data generating clients who have a minimum level of knowledge, which in our opinion does not really address the larger and more general audience. Finally, we've often been asked: "why haven't we heard of you in IT circles?". But I think we've answered that: we're not IN the IT circles. While we're a team of scientists with a stack of grad degrees, machine learning clusters, and love cute elephant mascots, we're loathe to wear and parade those terms when we approach those who can benefit from these technologies. But...we have an API for you fellow engineers, while we happily operate in "meat space". We hope to see you out there. And again, a big thanks to our growing user base and product evangelists. More to come in a few weeks. Keep an eye out for new tools and methods of ripping up your data -- no, you still won't need any math or programming knowledge. Cheers!