April 25, 2013

Analytic application themes

I talk with a lot of companies, and repeatedly hear some of the same application themes. This post is my attempt to collect some of those ideas in one place.

1. So far, the buzzword of the year is “real-time analytics”, generally with “operational” or “big data” included as well. I hear variants of that positioning from NewSQL vendors (e.g. MemSQL), NoSQL vendors (e.g. AeroSpike), BI stack vendors (e.g. Platfora), application-stack vendors (e.g. WibiData), log analysis vendors (led by Splunk), data management vendors (e.g. Cloudera), and of course the CEP industry.

Yeah, yeah, I know — not all the named companies are in exactly the right market category. But that’s hard to avoid.

Why this gold rush? On the demand side, there’s a real or imagined need for speed. On the supply side, I’d say:

2. More generally, most of the applications I hear about are analytic, or have a strong analytic aspect. The three biggest areas — and these overlap — are:

Also arising fairly frequently are:

I’m hearing less about quality, defect tracking, and equipment maintenance than I used to, but those application areas have anyway been ebbing and flowing for decades.

3. Much of customer interaction revolves around recommendation and personalization. In connection with that I’ll remind you:

4. Networks and sensors emit the epitome of machine-generated data. Data sources include web logs, network logs (in the IT sense), telecommunication networks, other utilities (e.g. electric), vehicle fleets, and more. Application themes include:

As one example of the last point, Oliver Ratzesberger told me years ago that eBay had up-to-the-minute BI cubes integrating customer response and log data, for the purpose of quickly detecting technology problems. Acunu recently told me that similar applications are one of their sales focuses.

5. In another example, games and mobile applications can be a lot like websites in terms of the analytics that support them (all the more so if we’re talking about games with in-app purchases). Two special features come up repeatedly, however — leaderboards for games, and geospatial data sent by mobile devices.

6. Algorithmic trading is flashy because of the sums of money involved, and because of what is often hyper-low latency; I’ve even heard 50 microseconds, and that’s a slightly out of date figure for a sequence of several atomic operations. But otherwise it’s not one of the more interesting areas to me, for at least two reasons:

Another reason I don’t study it much is that high-frequency trading could be devastated at any time by some simple regulatory changes.

7. I finally figured out one of the big drivers for better risk analysis. Banks need to keep capital lying around to cover a fraction of the risk they take on. If they can estimate the risk more precisely, and come up with a lower number, then they need to keep less capital. That’s a lot like finding large bags of money.

8. Anti-fraud applications arise in many industries, with many different kinds of data and latency requirement. For example:

9. And finally, the recent Boston Marathon bombing has brought law-enforcement/anti-terrorism applications to the fore. The Boston Globe criticized difficulties in information sharing, but the money quote is:

The FBI followed up by checking government databases and looking for things such as “derogatory telephone communications, possible use of online sites associated with the promotion of radical activity, associations with other persons of interest, travel history and plans, and education history,” according to FBI Supervisory Agent Jason J. Pack. “The FBI also interviewed Tamerlan Tsarnaev and family members. The FBI did not find any terrorism activity.”

Neither the telephone intercept nor the web-surfing tracking is a capability the government routinely admits, unless there was something like a wiretap order that I so far haven’t seen reported.

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