Call me slow on the uptake if you like, but it’s finally dawned on me that outsourced data marts are a nontrivial segment of the analytics business. For example:
- I was just briefed by Vertica, and got the impression that data mart outsourcers may be Vertica’s #3 vertical market, after financial services and telecom. Certainly it seems like they are Vertica’s #3 market if you bundle together data mart outsourcers and more conventional OEMs.
- When Netezza started out, a bunch of its early customers were credit data-based analytics outsourcers like Acxiom.
- After nagging DATAllegro for a production reference, I finally got a good one — TEOCO. TEOCO specializes in figuring out whether inter-carrier telcom bills are correct. While there’s certainly a transactional invoice-processing aspect to this, the business seems to hinge mainly around doing calculations to figure out correct charges.
- I was talking with Pervasive about Pervasive Datarush, a beta product that lets you do super-fast analytics on data even if you never load it into a DBMS in the first place. I challenged them for use cases. One user turns out to be an insurance claims rule-checking outsourcer.
- One of Infobright’s references is a French CRM analytics outsourcer, 1024 Degres.
- 1010data has built up a client base of 50-60, including a number of financial and retail blue-chippers, with a soup-to-nuts BI/analysis/columnar database stack.
- I haven’t heard much about Verix in a while, but their niche was combining internal sales figures with external point-of-sale/prescription data to assess retail (especially pharma) microtrends.
To a first approximation, here’s what I think is going on.
Privacy laws force some outsourcing. It’s often OK to use credit data to decide what you’ll market at whom, even when it’s not OK to actually see the credit data itself. What’s more, in some cases data can’t leave a country, so if you don’t have critical business mass in that particular country, it’s natural to use an outsourcer who does.
Privacy even aside, owners of proprietary data are natural analytics outsourcers. Either you ship your data to your customers to do with as they please — and impose on them the expense of managing it — or you manage it for them.
Analytic “secret sauce” software providers also are natural outsourcers. Most proprietary analytic rules are pretty simple-minded. Outsourcing preserves mystique and pricing power.
The usual benefits of SaaS apply. Fast set-up, no fixed costs, etc. are all goodness, just as they are in the transactional world.
With that as background, the big change in the analytics outsourcing market is the same as the one sweeping the rest of the analytics world — interactive access to detail data is finally becoming affordable. If you just run weekly or monthly reports, and there may be no reason to distinguish between analytic and transactional processing. But if you want to allow ad-hoc query, unlimited drilldown, or live dashboards, then you’re talking a serious data mart technology stack.
And I do mean “data mart”. Outsourcing an enterprise data warehouse, with all of your proprietary transactional data, doesn’t make much sense unless you’re a complete SaaS shop already outsourcing that data in the first place.