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Appliance Deployment and Data Warehouse Architecture

February 22, 2012


Are you using appliances as part of your data warehouse? No? Ever thought about it for your appliance deployment strategy?

Eric Williams, who retired recently from Catalina Marketing Corp. as executive vice president and CIO, told industry observer Alan Earls in an interview that using apps as part of the actual data warehouse architecture was part of the company’s successful appliance deployment strategy back in the 1990s. Of course, back then they were building their own apps; once commercially-produced products became available, they switched to those.

It makes sense. As industry insider Craig Borysowich explained recently, “a data warehouse is simply an application system that supports an organization’s management decision-making process,” with an application component consisting of a set of functions, or “applications.”

The advantage of this form of appliance deployment, as Williams outlined it to Earls, is that bundling together data warehouse software and hardware in a preconfigured package gives you something that’s easier to deploy, costs less and can “quickly scale out to support business and data growth,” as Earls put it.

And Catalina’s approach fits with Borysowich’s recommendation to buy as much functionality as you can, resorting to building your own only when you can’t buy what you need.

Some companies choose to install appliance deployments to supplement existing data warehouse platforms, as Lancet Software’s Randy Mattran, vice president of professional services told Earls. Generally this happens with apps that are what Mattran called “special-purposed machines,” with a reliable operational data store behind them to “consolidate and integrate enterprise data from multiple source systems.”

The main reason for appliance deployment to become part of the data warehouse architecture is for business intelligence and analytics. You’ve got all those millions of bits of customer information in there, and you need to analyze and get value out of it all. Consultant Julie Lockner told Earls that about half of all companies rank getting more data analytics as a top five IT priority over the next year and a half.

Edited by Jamie Epstein

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