In so many respects, the last ten years can be fairly called the Data Decade. In large part, that’s because the data business came into the last decade on a strong footing. While the ad-based media world was decimated by the likes of Google and Facebook, data companies held firm to their subscription-based revenue models and thrived as a result. And while legacy print publishers struggled to make online work for them, data publishers moved online without issues or complications, in large part because their products were inherently more useful when accessed online. As importantly, data entered the last decade with a lot of buzz, because the value and power of data products had become broadly understood.
At the highest level,, data got both bigger and better in the last decade. The much-used and much-
abused term “Big Data” came into popular usage. While Big Data was misunderstood by many, the impact for data publishers is that for the first time we became able to both aggregate and productively access and use truly massive amounts of data, creating endless new opportunities for both new and enhanced data products.
\While life without the cloud is unimaginable today, at the beginning of the last decade it was just getting started and its importance was vastly underappreciated. But the cloud profoundly altered for the better both the cost and convenience of maintaining and manipulating large amounts of data.
I’d argue too that APIs came into their own in the last decade to become a necessary component of almost every online data business. The result of this is that data became more portable and easier to aggregate and mix and match and integrate in ways that generated lots of new revenue for data owners while also building powerful lock-in with data licensees who increasingly became reliant on these data feeds. That’s one of the reasons that the data business didn’t feel the impact of the Great Recession as severely as many others.
Through a combination of Big Data, the cloud and APIs, the last decade saw incredible growth in collection and use of behavioral signals to infer such critical things as purchase interest and intent, opening both new markets and new revenue opportunities. This of course allowed many data publishers to tap into the many household name marketing automation platforms. Hopefully, companies will someday develop marketing campaigns as sophisticated as the data powering them, as the holy grail of fewer but more effective email messages still seems badly out of reach.
Another fascinating development of the last decade is the growing understanding of the power and value of data. The cutesy term “data exhaust” came into common usage in the last few years, referring to data created as a by-product of some other activity. And just as start-ups once rushed to add social media elements to their products, however inappropriately, venture capitalists now rarely see a business plan without a reference to a start-up’s data opportunity. There will be backlash here as both entrepreneurs and venture capitalists learn the expensive lesson that “not all data is good data,” but in the meantime, the goldrush continues unabated.
Somewhat related to this trend, we’ve seen much interest and activity around the concept of “data governance,” which is an acknowledgement that while poor quality data is close to useless, top quality data is enormously powerful in large part because it can be trusted implicitly. Indeed, if you listen in at any gathering of data scientists, the grousing you will hear is that they see themselves in fact as “data janitors,” reflecting the fact that they spend far more of their time cleaning and structuring data than actually analyzing it.
I can’t close out this decade without also mentioning the trend towards open data, which in large part refers to the increasing availability of public sector databases that often can be used to enhance commercial data products.
In all, it was a very good decade for the data business, a happy outcome that resulted primarily from the increased technical ability to aggregate and process huge amounts of data, growing willingness to share data on a computer-to-computer basis, and much greater attention to improving the overall quality of data.
And the decade now in front of us? Next week, I'll take a look ahead.