When you hear the term "fast data," your first thought is probably the velocity of the data. That's not unusual in the realm of big data -- where velocity is one of the V's everyone talked about. However, fast data encompasses more than a data characteristic; it is about how quickly you can get and use insight.

Working with Noel Yuhanna on an upcoming report on how to develop your data management roadmap, we found speed was a continuous theme to achieve. Clients consistently call out speed as what holds them back. How they interpret what speed means is the crux of the issue.

Technology management thinks about how quickly data is provisioned. The solution is a faster engine -- in-memory grids like SAP HANA become the tool of choice. This is the wrong way to think about it. Simply serving up data with faster integration and a high performance platform is what we have always done -- better box, better integration software, better data warehouse. Why use the same solution that in a year or two runs against the same wall?

The other side of the equation is that sending data out faster ignores what business stakeholders and analytics teams want. Speed to the business encompasses self-service data acquisition, faster deployment of data services, and faster changes. The reason: They need to act on the data and insights.

The right strategy is to create a vision that orients toward business outcomes. Today's reality is that we live in a world where it is no longer about first to market. Instead, we have to be about first to value. First to value with our customers, and first to value with our business capabilities. The speed at which insights are gained and ultimately how they are put to use is your data management strategy.

This is fast data.

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