SAND Supports Unicode Conversion During SAP NetWeaver BI Upgrades
SAND/DNA nearline solution reduces the costs of migrating to SAP NetWeaver BI 7.0
Montreal, Canada, September 18, 2007 – SAND Technology Inc. (OTCBB: SNDTF.OB), an international provider of intelligent enterprise information management software, announced today that it has introduced a Smart Unicode Conversion framework for SAP NetWeaver® BI.
Companies worldwide have accepted Unicode as the standard encoding scheme for character data. With the introduction of SAP Netweaver BI 7.0, SAP has adopted Unicode as the recommended encoding scheme for new SAP BI installations.
As a result, many organizations migrating from SAP BW 3.x to SAP NetWeaver BI 7.0 are seeking to convert their databases to Unicode. Nevertheless, conversion requires considerable resources. Tests have shown that, depending on the type of data involved, up to 1.1 to 1.3 times the amount of disk space is required to accommodate data converted to Unicode, along with 30% more CPU power and 50% more memory.
These resource requirements can be reduced by adopting SAP’s Nearline approach for SAP NetWeaver BI 7.0 and moving older and less frequently used data from the main SAP BW 3.x database into SAND’s software-based SAND/DNA nearline repository.
Using the Smart Unicode Conversion framework, companies can reduce the amount of data that needs to be converted while also lowering TCO and improving their ability to meet Service Level Agreements (SLAs) using the SAP NetWeaver BI 7.0 NLS Interface immediately after SAP NetWeaver BI 7.0 goes into production.
“Using Smart Unicode Conversion based on SAND/DNA, companies are able to save time and resources while migrating from SAP BW 3.x to SAP NetWeaver BI 7.0,” said Roland Markowski, Managing Director, Central Europe, for SAND Technology. “Not only can they can speed up the Unicode conversion process, but perhaps more importantly they can equip their SAP NetWeaver BI 7.0 system with an agile relational database from the outset, without losing access to historical and less frequently used data,” he added.