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You are here: Home / CRM Systems / SAP Showcases Testing & New Apps
SAP Showcases HANA Tests and New In-Memory Apps
SAP Showcases HANA Tests and New In-Memory Apps
By Jennifer LeClaire / CRM Daily Like this on Facebook Tweet this Link thison Linkedin Link this on Google Plus
Although may be the first name you think of when it comes to CRM innovation, well-established SAP refuses to be counted out of this lucrative game. In fact, German-based SAP has been firing innovative missives at lately, and it's getting the attention of the enterprise marketplace.

Last week, SAP outlined an extensive road map for the coming year, including a variety of enterprise software applications based on its new In-Memory Computing technology.

In addition, SAP's quiver now includes an arrow with IBM's name on it. Big Blue and SAP just announced the first official performance results of the SAP In-Memory Appliance software, known as HANA (short for high-performance analytic appliance).

The test results, which were independently audited by Winter Corp., found that HANA can handle 10,000 queries an hour against 1.3 terabytes of data, returning results in seconds.

HANA's Heavy Lifting

This type of heavy lifting can be key to companies that need to analyze large amounts of data for sales analysis, product development, enterprise resource planning, and related business intelligence.

The test scenarios were based on query workloads that are typical of enterprise resource planning (ERP) requirements, such as those typically encountered by SAP enterprise customers.

Analytical queries in the test were designed to mirror the research needs of real businesses, such as analyzing trends in their sales history, top customers, best-selling products, customer returns, and other parameters. The tests were designed to analyze minute levels of detail, across virtually any time frame.

In one example, SAP HANA proved it could handle large and simultaneous demands for business analysis by taking on 10 analytical query streams and four operational reporting systems. HANA was able to produce combined results for 10,000 queries an hour. WinterCorp confirmed that HANA can also analyze large volumes of data in seconds -- even with intricately complex queries.

SAP's Road Map of In-Memory Apps

The HANA test results were released last week, as part of the company's larger announcement of a road map for future applications that will be powered by SAP's new In-Memory Computing technology.

SAP claims this new family of applications will transform how people do business, enabling them to plan faster and view business problems more holistically. With faster, real-time analytics capabilities, SAP said corporate decision-makers will be able to base their next moves on up-to-the-minute transactional data that is constantly updated.

Over the year ahead, SAP plans to release a number of new and upgraded applications, outlined below, using its new In-Memory Computing technology.

Sales and Operations Planning:

SAP said the first application planned will help sales and marketing departments collaborate more closely with finance and operations to help boost the bottom line.

Built on SAP in-memory computing technology, this application will help employees and managers evaluate the financial impact of their strategy on supply-and-demand scenarios. Staff responsible for supply chain management will be able to create simulations and "what-if" scenarios based on detailed transactional data.

Intelligent Payment Broker:

Also ahead is a new financial application that will use SAP in-memory computing technology to calculate and offer financing options on open invoices.

By analyzing current and historical data, this application will be able to intelligently propose which discounting terms should be offered on which invoices. SAP said its in-memory technology will help eliminate the guesswork behind discounting, and can even help predict the impact that different finance terms will have on their customers' liquidity.

Smart Meter Analytics:

Another new application included on the road map will enable utility companies to analyze smart meter readings to forecast demand, analyze profitability of customer segments, and develop new products.

SAP said in-memory computing will make it possible to process massive amounts of data coming from these devices in real time, so that utility companies can react quickly to changes in energy production or consumption.

SAP Trade Promotion Management:

Other SAP software is in the works to help businesses ensure that their trade promotion process and forecasts are based on solid historical data, again using in-memory computing to improve the planning process.

SAP estimates that consumer-goods companies often spend about 20 percent of their annual revenue on promotions -- making accurate analysis of each promotion incredibly important.

SAP Cash and Liquidity Management:

The final application included on the road map for the coming year is part of the SAP Business Suite software. It allows business managers to predict inbound and outbound cash flows, with functionality for collections, risk management, and short-term borrowing.

SAP said its new in-memory computing technology will boost users' ability to examine data easily at different levels, for example, by region, by country, or globally -- enabling more reliable business decision-making.

Simplifying IT

Overall, SAP expects its new in-memory computing technology will help enterprises simplify their IT infrastructures. The simplification would come by eliminating the need for data caches, aggregations, and batch processing. Eventually, SAP said, in-memory computing will help customers reduce their database usage and reliance on disks, leading to the need for fewer layers, and ultimately, enabling a simpler architecture.

As part of the transition, SAP is upgrading its business-intelligence and enterprise-management software that is part of its SAP BusinessObjects portfolio. The new versions, announced last month, are built to work on top of SAP In-Memory Appliance software (SAP HANA) giving a performance boost for large-scale data analysis.

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