Business technology thought leader John Ladley has spent 30 years around data and IT project management, where he witnessed and pioneered in the progressions of data warehousing, business intelligence and enterprise information management. This week the author and president at IMCue Solutions led a series of data innovation briefings addressing emerging technologies at the Enterprise Data World 2012 conference in Atlanta that often included the topics of big data and semantic technologies.
What are you noticing in applied data technologies today versus a couple of years ago?
One thing that’s becoming a real versus a nascent idea is in the use of semantic tools, and of course a lot of people are seeing that also with the big data tools. In both cases it’s becoming real that if the organization has the right mix of data with velocity, volume and variety and the source isn’t too terribly convoluted, they can find a very short time to market with potentially powerful results. Both semantics and big data have been called “next big things” of the kind that usually take three to five years to come to fruition or just disappear. In this case, both have come to fruition and are establishing themselves very rapidly.
We hear a great deal about big data, but the buzz around semantic concepts, RDF and OWL and SPARKL seemed to appear for a few years and then went underground. You’re saying the applied use of semantics is clearer now?
We saw an interesting case just this morning from a company called Spry doing work with the Department of Defense. Also, there have been acquisitions of some of the pioneers and incorporation of the technology. RedHat bought MetaMatrix years ago, for example, and you’re beginning to see that technology emerge in areas where there is a value proposition to be applied.
You mentioned it’s kind of an abrupt appearance of technology.
It’s not unlike the mid-80s experience with relational databases for those of us with gray hair. I was hip deep in delivery in those days with what was then the relational database and everyone thought it was a great idea. But it was hard to understand, still pretty abstract and the performance wasn’t quite there. We weren’t really sure, but we kept dabbling and finding value until all of a sudden one day the world was nothing but relational databases.
You say there’s a window of opportunity for companies, but so far we have a lot more questions than constructive answers, like we’ve just invented some new kind of telescope for data that lets us see things for the first time.
That’s a really good analogy, you’re saying we can look out and see these swirly dots that aren’t just stars, they’re galaxies and we may have no idea what they are or mean or how to interpret what I am looking at. To a certain extent that’s still an evolution that has to occur with big data. When I talk about a window of opportunity, I qualify the comment to say that as the organization finds it has a concise bounded huge set of data, there is value there. There is another 95 percent of organizations that can’t use big data. I got into a lively discussion with a bunch of analysts about a year ago on that topic. They were saying everyone should be going for big data.
As in all aboard or miss the boat?
Right, exactly. I said absolutely not, I am putting my CEO face on, or my CIO face on. I have an organization here that culturally cannot get a transaction entered correctly without having to change it the next day, and now you’re telling me I am going to do big data? You can’t do big data on garbage. What I find interesting about the big technology, and I need to qualify this more, is it is ready to go if you’ve got the background and the data and the culture.
Is it true that the big data folks aren’t the same IT data people who had been walking the hallways, that it’s a different group?
Yes, but the point is that the products are working. In the old days of the relational world, they’d say the product works but we’re just getting no data. When you closed the door with Oracle they’d say it wasn’t working too well yet. But the Hadoop stuff and MapReduce, that stuff works. You can jam terabytes in there and it works.
Now the business is going to want a silver bullet, right?
Of course, and this was part of that discussion with the analysts. They won’t care just to grab a bunch of data and process it. What they can think about is whether they know what to do with it. They can think about whether they have the culture to react. If you don’t have the sincerity to use information as an asset or as fuel for the organization, they are still going to be wasting their time and money.
Isn’t it a little daunting to be invested midstream with BI or MDM and then be told there’s this new direction everybody is going in? It can’t make our program managers presently carrying all the project risk happy.
That gets back to knowing that the ones saying you have to go all in are the ones selling it and the ones representing the sellers and that includes some of the analyst groups that have gotten into this at the expense of everything else. It’s there for you if you have a culture that’s prepared for it and you have an idea what you want it to do.
That’s been the progression all along in information management for us in that these things are interrelated and tend to fall to the same people as value emerges.
It goes back to a slide I use to describe enterprise information management. It’s not multiple disciplines top to bottom in a conference. It’s one discipline that has a bunch of components that are separated only by latency, volume and velocity. Other than that there is nothing new under the sun.
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