The Next Frontier for Data Analytics

Michael Vizard

There's a lot of subtlety at work among providers of data analysis tools and data warehouse platforms that appears to signal more open-ended approaches to business intelligence software to come.

SAS Institute and Netezza, for example, recently announced an alliance in which SAS's scoring analytics software will run inside the Netezza data warehouse. That means analytics can be processed in memory right alongside the rest of the data warehouse, as opposed to information being exported to a separate application for processing.

As more and faster analysis is required with real-time data, the ability to process analytics in-memory on the data warehouse becomes quite an asset.

But there is also a longer-term trend at work here that is worth noting. According to SAS Institute CTO Keith Collins, SAS envisions a world in which its software will be able to analyze data coming from multiple data warehouse repositories at once. That means that while some processing will be done inside the local database, it's getting closer to being able to analyze data coming from multiple data warehouse platforms in almost real time.




That has a couple of implications. More sophisticated analytic models involving multiple companies could arise from this ability to quickly compare data across multiple data warehouses. It also means that SAS customers could start to envision data warehouse platforms as elements of a SAS analytics grid where they could choose which platform to use for what type of analytics based on the cost and attributes of the platform.

With the cost of storage going down and the ability to process large sets of data increasing, we're clearly on the edge of a new frontier in data analytics that ultimately will change the way we think about not only how data is processed, but also analyzed in the context of a real-time business process.

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