I’ve recently joined the MarkLogic team, and couldn’t be more thrilled. For those of you who might have followed me from EMC to VMware to Oracle, you might wonder — why?
MarkLogic has solved an incredibly important and inherently difficult problem for its customers — how do you make connections across diverse data to deliver more value from information?
Think paying insurance claims, or making loans. Perhaps designing and testing aircraft. Maybe finding fraudulent behavior fast. Or finding bad actors on the global stage.
Anywhere you’d find rich, diverse data loaded with potential. The more you look, the more you find this particular problem. Analytics, yes, but that’s only part of the picture.
Human beings can be good at making these diverse data connections and finding important patterns. Personally, I’d like to I think I’m good at it, but I’m not cheap. I also make mistakes. How do we get software to do the same thing?
Metadata is nothing more than information that describes information. You can say that metadata provides important context around a chunk of information like an event.
When you’re looking for patterns, context matters. Think back to the last tragic event in the local news. You immediately want to know context — who, what, when — and why. Or perhaps you’re considering a big decision, so you start researching and informing yourself.
Either way, you want as much rich, usable context as possible. That’s why metadata is important — it informs decisions.
Now let’s pivot to the IT world.
Metadata is what makes the data plane (or data fabric) more valuable. You use metadata to make connections — and inform decisions.
So it stands to reason that — before long — you’d find certain organizations very enthusiastic about building and using rich metadata layers to inform important decisions. Pharma. Insurance. Aircraft design. And much more.
That’s what MarkLogic does. They help their customers build and exploit rich, active metadata layers that inform important decisions. There’s an enviable list of happy production customers doing truly impressive things with the technology.
My last tour of duty was at Oracle where I had the privilege of doing a deep dive of not only great Oracle technology, but many of the competitive alternatives.
One way of comparing technology is to isolate feature X and see if product Y also does it. But you’d miss the forest for the trees.
MarkLogic is what you get when you change the focus to building a rich, active metadata layer and don’t want to care so much where your data is coming from, or how it might be used at some point.
For our customers, it’s a journey.
They use metadata to search new connections and discover new insights. They build scalable applications to put those insights to work. And then they improve their decision models over time with predictive machine learning.
Obviously, this is a fairly rich discussion with so many interesting implications. Where are different organizations on their journey? What makes one organization need or want this kind of answer vs alternatives? What’s an organizational pattern for success?
Perhaps more interesting: what precisely causes the discussion to shift towards a rich, productive metadata layer being viewed as an enabling resource across the organization? Lots of organizations still putting spaghetti data flow charts up on whiteboards…
I’m looking forward to it.
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