Opera Solutions announced this morning that it will incorporate SAP’s in-memory database HANA into its Analytics-as-a-Service offerings.

The combination of HANA and Opera’s advanced data mining capabilities – which centers around what the company calls signal hubs – will allow enterprises that lack the internal talent to deploy and manage Big Data on-premise to deliver near real-time predictive analytic capabilities to frontline workers as a service, according to Shawn Blevins, Executive Vice President and General Manager of Sales.

(The deal was announced this morning at SAPPHIRE in Orlando. We’ve got full coverage of the show via #theCUBE at SiliconANGLE.tv all day Tuesday and Wednesday.)

Of course, SAP has its own line of predictive analytics software (part of the BusinessObjects portfolio), but enterprises still need analytics pros to build and implement the predictive models, said Blevins. Opera obviates this need, he said. SAP is betting much of its future on HANA, and the deal gives the German software maker and now database vendor another channel to reach customers.

If you haven’t heard of Opera Solutions before now, it’s time to start paying attention. The company did $100 million in revenue in 2011 and boasts an internal team of over 220 Data Scientists expert in machine learning and advanced analytics. The private company also raised $84 million in Q3 2011 led by Silver Lake Sumeru.

Opera’s business works like this: Customers send their data to Opera’s data center, where the vendor scrubs, stores and blends it with third-party data sources. From there, Opera’s Data Scientists go to work, combing through the data to identify insights that are then delivered back to the customer in the form of on-demand vertically-focused applications.

Opera uses an array of technologies to process and analyze all that data depending on the particular use case. HANA is now certified as one of those technologies. That means Opera can now perform ETL, data normalization, and data analysis all “in the HANA box,” said Blevins.

Opera’s model aims to abstract all the complexity from Big Data Analytics. It’s an interesting approach, one that I think CIOs should consider especially in scenarios where internal analytic talent is lacking. My main word of caution would be that once you outsource a core capability such as analytics, its difficult to bring it back in-house. Institutional knowledge around developing predictive models builds up in the outsource vendor – Opera in this case – and not within the customer’s collective intelligence.