Big Data: Vertical Behavioral Analytics

And you are now thinking: "what does that mean?"

The below is actual an updated something I wrote a while back, but I'm dusting off that post for several reasons.

1) It seems to be a very interesting perspective in light of the IDC keynote that you can view here. It extensively talks about moving to the third generation IT platform and highlights specifically vertical big data solutions.

2) The strong emphasis in current media on "parallel analytic platforms" and the big deal everyone is making about having that analytics platform, but then leaving it at that...

I (we) think that you cannot just stop at "we are processing in parallel and have something like mapreduce", you should be able to work in verticals or specialized scenarios and offer value. And that is what the Oracle story is, verticals layered on top of a parallel analytic platform.

So what did I mean when I wrote Vertical Behavioral Analytics? Here is the augmented reality with additions, making this Vertical Behavioral Analytics V2...

First of all, analytics. I would think you had guessed by now that this is really what I'm after, and of course you are right. But not just analytics, which has a very large scope and means many things to many people. I'm not just after Business Intelligence (analytics 1.0?) or data mining (analytics 2.0?) but I'm after something more interesting that you can only do after having access to large volumes of data - both external and internally collected.

That all important data is about undiscovered behavior and unknown relationships. What do my customers think? More importantly why do they behave like that and can I read their mind? If you can figure that out, you can tailor web sites, stores, products, promotions, events etc. to that behavior and create an enormous increase in business value from big data.

Today's behavior - that is somewhat easily tracked - is based on web site clicks, search patterns and all of those things that a web site or web server tracks. That is where the Big Data 1.0 lives and where these patters are now emerging. Other examples however are emerging, and one of the examples used at the conference was about predicting churn for a telco based on the social network its members are a part of. That social network is not about LinkedIn or Facebook, but about who interacts with whom. I call, sms or IM you a lot, you switch provider, and now I might/will switch too to keep on that unlimited SMS plan for friends. That behavior is in Call Detail Records, which is basic telco data. Nothing novel other than it is expanding into SMS and IM, or generally mobile devices.

The above becomes interesting if you start to build up these "bunch of connected people (BCP)" networks from CDRs and add external data to it. For example demographics and income related information could be used to target device upgrades and/or plan changes based on economics for the BCP. Or add in the idea of device reviews (or comments on social media outlets) to push devices into the BCPs...

And that just naturally brings me to the next word, vertical. Vertical in this context means per industry, e.g. communications or retail or government or any other vertical or specialized environment (like language specific for apps on mobile devices).

The reason for being more specific than just behavioral analytics is that each industry has its own data sources, has its own quirky logic and has its own demands and priorities. Of course, the methods and some of the software will be common and some will have both retail and service industry analytics in place (your corner coffee store for example).

But the gist of it all is that analytics that can interpret and predict customer behavior for a specific focused group of people (that BCP mentioned earlier) in a specific industry is what makes Big Data interesting.

After our blogs are migrated, and we can post again, I will spend some time on this blog talking about Oracle's ideas around big data with some more detail. How could one use Oracle's to parallel analytic platform, its vertical expertise and the cloud infrastructure to build these vertical behavioral analysis solutions. Stay tuned for an interesting 25 years... or a few interesting blog posts in the near future.

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The data warehouse insider is written by the Oracle product management team and sheds lights on all thing data warehousing and big data.

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