SAS Institute is planning to work with the largest database and data warehouse vendors to get its analytics software embedded in their products. That should help companies do faster and higher volume data analysis, such as scoring customers and prospects for targeted marketing.

SAS's plan is all road map and no product today, but SAS CTO and senior VP Keith Collins said the company's working with the largest database companies so they and SAS can make the changes necessary to embed analytical technology. It plans to announce Monday a joint development center with Teradata, which counts Wal-Mart among its data warehouse customers.

Collins sees a three-stage road map for embedding analytical tools directly into the database:

Data preparation and filtering tools will come first, so only the right data needed for analysis is pulled from the database. SAS expects more detailed plans about this first step by the middle of next year.

Next will come software to make quicker and more automated the process of tying the results of analysis to the original data, such as putting a customer score with the individual.

Last will come the actual analytics engine being embedded in databases.

Why does SAS see opportunity to do this now? One is technical, in that databases that used to be focused on transaction processing now are much more capable of what Collins calls "mixed workloads," including doing sequential data processing needed in analytics.

The other is business driven. Companies want to use analytics -- whether its business intelligence querying, decision-support tools, or performance-tracking dashboards -- in much more timely ways to run their business. Collins offers the example of banks doing real-time analysis to spot abnormal transactions that might point to money laundering.

The biggest advantage to in-database analytics would be speed. Today it can take months, Collins said, for a company to translate the output of a major analytics project, such as segmenting all the company's customers, and applying the results back to the data source.

For the IT department, Collins also sees a governance advantage to in-database analytics. As analytics become a more important part to how a company drives sales, it will become a "material" process in the lingo of Sarbanes-Oxley, requiring IT to more closely document data flows. "The governance of the analytics process becomes much more important for IT," he said. And the less data moving around, the less complicated that process.