Searching for Analytics

Ever walk into a room and can’t remember what you were supposed to be doing there? A minute ago you had all of life’s answers, and now you’re just standing there, staring idly at random objects trying to cue your brain to recall any hint of purpose?

Of course you have.

In fact, it happens quite a lot in big data initiatives: the business sets out looking for something, and fails to remember quite what they were looking for as they struggle to navigate the massive volumes of content.

For me, it always happens when I’m walking upstairs in my house. There must be something hypnotizing about the repetitive white square inlays on the beige background of the steps. They send me into a blizzard of thought and toss me out at the top completely lost.

So, what’s wrong with us?  Might we have acute sudden-onset amnesia? Is there a glitch in the matrix? Is this forever?

Of course not. You’re simply a pre-occupied forgetful idiot like I am; we all are. We’ll think of it ten minutes later over a nice glass of fresh-squeezed orange juice. But in the moment, you’re Tom Hanks in Castaway with a satellite phone but no telephone numbers to dial. You have a wealth of possibilities at your disposal, but no discernible way to hone in on your specific intention.

I imagine this is commonplace for anyone tasked with finding specific slices of value in large volumes of information. And without the right tools, it’s a task I don’t envy. Because in the world of unstructured data mining, it is often not simply that one cannot find what they’re looking for. If it were, a robust search engine would likely suffice. It is more often that they do not even know what they’re looking for.

That is the challenge we strive to tackle with ZL Enterprise Analytics. It is an effort to provide our customers with a trail of breadcrumbs to follow, even when they are not sure what they are looking for. It’s a way to empower what little cues they do have to find something they didn’t know they needed, and to paint the fullest picture with the fewest number of iterations. It's an analytics driven approach

Now if I could just remember where I left my sandwich.

analytics Big Data data accessibility search

I’m a University of Michigan grad, where I studied chemistry and statistics. Unsurprisingly, my work is now in the tech field as a Client Implementations Lead at ZL. Outside of work, I surround myself with good music and good friends. A well-seasoned traveler, my interests span the affairs of many cultures, with the sole exception of Ohio. I would like to note, however, that Ohio does boast top notch highway service plazas, which make it one of the best states to drive straight through. Today, much of my time is spent driving through the golden hills of the bay area. I miss pond hockey, rainfall, and occasionally the eastern time zone. But In-and-Out sooths the pain.