Velocity matters

For the last decade plus, the day job has been preaching that performance is an advantage, a feature you need, a technological barrier for those with both inefficient infrastructures and built in resistance to address these issues. You find the latter usually at organizations with purchasing groups that dominate the users and the business owners.

The advent of big data, (ok, this is what the second or third time around now) with data sets that have been pushing performance capabilities of infrastructure has been putting the exclamation point on this for the past few years. Big data is all about turning massive data sets into actionable intelligence, and enabling people to make use of the data that they’ve gathered.

Our argument has been and remains, the faster you can make your analytics, both the larger data sets you can analyze, and you can analyze them with more frequency (more models per unit time), and more accuracy (more sophisticated and coupled models representing a more accurate and testable set of hypotheses) you can obtain.

Our voice has been a lonely one in the wilderness for years until the Data Mining/Business Intelligence/Big data revolution was (re)born. Now, all of a sudden, we see article after article saying what we’ve been saying all along.

Here’s one at techcrunch (yes, I know, but still its an ok high level read). Written by a KPCB person, so they’ve got a built in bias as to what is important. And who is important.

But points 8 and 9 matter.

8. Data is the new competitive advantage: The promise of Big Data is its power to bring new insights to light. Improved analytics have triggered new, non-obvious ideas about how businesses operate. For instance, discovered that a sales rep who calls a lead back within 5 minutes of a request for information boosts the likelihood of closing a sale by 10X. By harnessing big data sets, companies will discover patterns like this for the first time.

Well, it used to be called Data Mining. Then Business Intelligence. Now Big Data. The idea is to analyze your data, build testable hypotheses, and iterate until you have enough of a sense of how things might play out to build a set of tactics to further a bigger picture strategy. This is nothing new in one sense, but whats new is you have the ability to look at data at scale. And that starts opening up whole new vistas of inquiry.

9. Speed kills ? your competitors: Faster application performance will distinguish the winners in enterprise. Studies by Walmart and Compuware show that one additional second of latency in application delivery can decrease revenue by 10 percent. An emerging set of companies is focused on speed: Instart Logic accelerates application delivery, AppDynamics monitors and helps address application response time, and PernixData and Fusion-io leverage flash-based storage to make data delivery many times faster.

Put a different way, you need performance to be able to respond to rapidly changing conditions. Obviously KPCB is biased about which of these matter, but the point is that there are products that can help make things go faster.

And at the end of the day, the most important aspect of being able to work with and gain insight from data, is your ability to interact with the data, ask questions of the data, construct testable hypotheses, and run many tests.

Which is why Scalable Informatics matters, as the FastPath software defined appliances combine the highest performance hardware with the best and fastest software stacks for analytics.

Just an observation on this, that its nice that the market as a whole has come around to our viewpoint.

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