– By Andy Thurai (@AndyThurai). This article was originally published on Xively blog site.
In the last decade, as a society, we had worked very hard toward “liberating our data” — unshackling it from the plethora of constraints unnecessarily imposed by I.T. In contrast to this, In the 90s and early 00s, data had been kept in the Stygian depths of the data warehouse, where only an elite few had access to, or had knowledge about it or the characteristics defining it.
Once we had the epiphany that we could glean amazing insights from data, even with our “junk” data, our efforts quickly refocused around working hard to expose data in every possible way. We exposed data at the bare bones level using the data APIs, or at a value added data platforms level, or even as industry based solutions platforms.
Thus far, we have spent a lot of time analyzing, finding patterns, or in other words, innovating, with a set of data that had been already collected. I see, however, many companies taking things to the next proverbial level.
In order to innovate, we must evolve to collect what matters to us the most as opposed to resign to just using what has been given to us. In other words, in order to invent, you need to start with an innovative data collection model. What this means is for us to move with speed and collect the specific data that will add value not only for us, but for our customers in a meaningful way.
Read more of this blog on Xively blog site.