Grant me a "crabby old guy" rant on big data. I continually hear people in our industry using the term big data as a product-category name — and confusing everyone about the business value of big data solutions. Moreover, too many people now seem to think that Hadoop is big data, when Hadoop is just one of the several big-data solutions available — and Hadoop isn't good for many big data scenarios.

Big data is a label for the trend toward processing dynamic (and therefore voluminous) data using in-memory architectures. This trend is being played out in 8 major scenarios that I can find. In each case, enterprises are struggling to understand how the various big data solutions will help generate revenue and profits, manage expenses, and service customers and citizens.

I posted a slide deck from a recent discussion of the big data trend on Slideshare. Here is the link: In that slide deck, you'll see this diagram listing the 8 big data scenarios we've seen in our work with clients here at Forrester Research.

Each of these scenarios poses specific architectural design, application development, and operational challenges. And each typically demands a particular technology solution. That's right; there's not one big-data product category but many categories. Big data must include complex event processing platforms, elastic caching platforms, and the various not-only SQL (NoSQL) databases. We have yet to see a one-size-fits-all suite or solution for all of these scenarios.

My hope is that we start zeroing in on the scenarios and the value to enterprises of the various big data solutions that address each scenario. By doing so, we'll unlock the value of big data a lot faster. And this old guy will have one less thing to crab about.