In 2012, the term â€śBig Dataâ€ť was thrown around with as much abandon as â€śSocial Mediaâ€ť was for the previous couple of years.
A one-size-fits-many-things moniker, â€śBig Dataâ€ť (like its cousin â€śSocial Mediaâ€ť) has been the subject of many a blog post, conference session and CMOâ€™s sleepless night, as industries realize its essence is important, but are not quite sure what to do with it (a bit like they did (still do?) with â€śsocial mediaâ€ť).
Do a search for the phrase over the last month and you can see a bit of a backlash against startups using the term â€śBigâ€ť in front of their wares and all that information we know and love.
Itâ€™s always been â€śBigâ€ť in relative terms to whatever weâ€™ve been mining; itâ€™s just that now (thanks to the web) itâ€™s getting bigger.
Photo on Flickr D Sharon Pruitt
An article in the New York Times offers:
â€śBig Data proponents point to the Internet for examples of triumphant data businesses, notably Google. But many of the Big Data techniques of math modeling, predictive algorithms and artificial intelligence software were first widely applied on Wall Street.â€ť
Others are suggesting what we mean when we say it, is a â€śsmart use of dataâ€ť, and that marketers are just using it as a â€śperniciousâ€ť way to rebrand an old adage and start a new fad.
The NYT piece mentions a McKinsey report that concluded that soon the US will need 140-190 thousand workers with â€śdeep analyticalâ€ť expertise and 1.5 million â€śdata-literate managersâ€ť.
It goes on to quote (and hereâ€™s the gem) Rachel Schutt, a senior statistician at Google Research, who defines a good data scientist as someone whoâ€™s not just savvy with math(s) and computer science, but:
â€śâ€¦someone who has a deep, wide-ranging curiosity, is innovative and is guided by experience as well as data.â€ť
She must be talking about SEOs surely?!
As seasoned professionals in the search industry, we know thereâ€™s more to a successful web strategy than a bunch of numbers (just listen to Jim Sterne talk about the importance of asking your customers how they â€śfeelâ€ť) but itâ€™s those numbers, coupled with curiosity about human behaviour, that keeps us pushing the envelope and wanting to do better.
At Majestic, we have a lot of numbers to talk about. A database with 4 trillion URLs is nothing to sniff at, but (as my wife keeps reminding me) itâ€™s what you do with it that really counts.
So beyond SEO, weâ€™re starting to think of other ways businesses can use all this gorgeous data. Weâ€™re talking to the finance industry about how they can pre-screen credit applications from ecommerce sites. Weâ€™re taking to social platforms about how they can use the data to improve their algorithms, and to advertising networks about how they use Majestic with pricing or fraud detection or targeting.
The more we think about it and get â€ścuriousâ€ť, the more â€śinnovativeâ€ť we think we could be.
So my question to you is: What DO you or what WOULD you use Majestic data for other than link-building and SEO?
Weâ€™re grateful for all the kudos we get for being agile enough in bringing new features, bells and whistles to the platform, but we want to do more and be better.
So weâ€™re curious to know what would you do with a distributed crawler and 4,060,890,688,027 unique URLs?
Let us know in the comments below.
Oh and please keep it useful and â€śWhite Hatâ€ť!
To slightly misquote Rachel Schutt in that NYT article, â€śWe only worship THAT machine.â€ť