Order and organization have become buzzwords thanks to today’s trend towards minimalism. There’s “the life-changing magic of cleaning up,” entire websites dedicated to bringing a minimalist mindset to every area of life, with tips, tricks and articles galore full of instructions on how to de-clutter your house, your office, even your car. It may seem to be a bit much, but even the most disorganized among us can admit that creating order out of chaos makes an immeasurable difference to effectiveness, productivity, and general wellbeing.
The same is true when it comes to the data lakes that are growing in every large organization. In today’s digital age, the concept of big data is synonymous with this sense of chaos. Of course, the hectic nature of big data may have something to do with its sheer magnitude.
According to Forbes, “data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.”
That’s a staggering amount of information. How will we ever be able to manage it all, let alone manage our own companies’ ever-growing and increasingly unruly data lakes? In short: with a metadata management solution that aligns the information about the data you have.
Metadata management works to bring together diverse collections of information, organizing it all into a single system so that it can be understood within a wider context and used to its fullest capacity. A data lake full of information that nobody in your enterprise can access or understand is, quite simply, not effective or efficient.
Forget the element of data for a moment, and consider a real, organic, topographical lake. Presumably, a natural pool of water would, over time, become home to a diverse and populous ecosystem of plant and animal life. And while it is true that within any organic ecosystem there are predators and prey, there are also plenty of species that coexist peacefully, swimming freely and openly beneath the surface of the water.
Now, let’s go fishing. If you’re new to freshwater lake fishing, you might have no idea what you’ll hook once you cast your line. You might not even be aware of the possibilities. Or, perhaps you’re a more experienced angler and you know that there are certain fish common to these types of waters, like bass, pike, trout, or perch. But even as a seasoned fisherman, there’s no guarantee that you’ll catch the specific type of fish you’re looking for once your line is in the water. All you can do is wait, and see what comes up.
Waiting patiently without any guarantee that you’ll get what you need is not a workable or effective strategy when it comes to data governance. It’s not much of a strategy at all. A company’s ability to remain competitive and be responsive to new business opportunities is intrinsically linked to the quality, reliability, security, accessibility, and usability of its data. And there’s no better first step towards reliable, accessible, actionable, quality data than a bit of housekeeping.
Data organization is just one way to understand metadata management. Creating an orderly structure and aligning the data you have is a crucial part of building contextual understanding around your data. And the metadata that makes your disparate, raw data meaningful also serves to keep it organized at all times and at every level, no matter how much new data you add.
Data governance and metadata management are both crucial capabilities that organizations must master in order to turn their raw data into actionable, effective, and efficient information assets. And these powerful and effective business capabilities begin with just a little emphasis on organization and order.
Let’s return to our freshwater fishing lake. We’ve seen already that in a naturally-occurring, disorganized lake where fish have free rein, there’s no way to guarantee that we’ll catch the fish we’re looking for. But if we organize this metaphorical lake so that the trout are in one place, the pike are in another, the perch, the bass, and so on, both beginners and savvy anglers alike would be able to navigate to the exact part of the lake where their desired fish resides, and reel in dinner easily and efficiently.
Data lakes are no different. What if you could go fishing in your data lake for the exact type, range, or set of data you need, and know without hesitation or doubt that you’d come up with the right information on your line? With your data lakes organized and managed in this way, you can go fishing for trout and come up with trout, every time. There are no surprises because you know what data you have, where it’s located, how to find it, and what it means. Data governance and metadata management enable precisely this result, which is why you need to implement an effective metadata management solution.