Rynek systemów Business Intelligence (BI) jest jednym z najbardziej dynamicznych segmentów rynku oprogramowania. Dotychczasowe rozwiązania analityczne, oparte na kostkach OLAP, okazują się jednak niejedynym i nienajszybszym rozwiązaniem. Celem niniejszego artykułu jest prezentacja nowej technologii, tzw. BI in-memory. Technologia ta umożliwia zarządzanie informacją w taki sposób, jak to dzieje się w ludzkim mózgu.
EN
The market of Business Intelligence Systems is one of the most dynamic sections of the software industry. The previous analytical solutions based on OLAP turn out not to be the only available and quickest ones. The aim of this article is to look through the traditional methods of analyzing and presenting new technology called BI in-memory. This technology makes it possible to manage the information in such a way as it takes place in human brain.
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Today's fast-paced, competitive marketplace means increasing pressure to raise profits, do more with less and operates more efficiently. Achieving these goals requires faster and improved decision-making ability across organizations. Unfortunately in many situations, departments continue to operate in information silos. Existing enterprise systems often are not linked and software packages are not integrated. Decision makers have difficulty getting the accurate information they need and IT professionals spend more time responding to ad-hoc report requests than focusing on strategic initiatives. Business intelligence integrates data from across your enterprise, and provides self-service reporting and analysis at everyone's "fingertips". Decision makers spend less time looking for answers and more time driving strategic decisions. BI decision-support initiatives are also very expensive endeavors. Disparate business data must be extracted and merged from online transaction processing (OLTP) systems, from batch systems, and from externally syndicated data sources. BI decision-support initiatives also call for new technology to be considered, additional tasks to be performed, roles and responsibilities to be shifted, and analysis and decision-support applications to be delivered quickly while maintaining acceptable quality. A staggering 60 percent of BI projects end in abandonment or failure because of inadequate planning, missed tasks, missed deadlines, poor project management, undelivered business requirements, or poor quality deliverables. An effective methodology of introducing the BI decision-support initiatives can lower this high investment risk. BI projects can be organized according to the six stages and 16 development steps within these stages as outlined in this article.
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E-business requires specific software, especially in the case of large, scattered companies operating under unfavorable market conditions. Such solutions as Business Intelligence systems enable to discover correlations and interdependences between economic data, i.e. to perform multi-dimensional data analyses. Large amounts of data acquired and collected every day provide the basis for making optimum strategic decisions.
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Wspomaganie biznesu, szczególnie w przypadku dużych, rozproszonych firm działających na trudnym rynku, wymaga specyficznego rodzaju oprogramowania. Dzięki takim rozwiązaniom jak systemy Business Intelligence możliwe jest odkrycie związków między danymi gospodarczymi, czyli wielowymiarowa analiza danych. Gromadzone codziennie tysiące danych stają się podstawą optymalnych decyzji strategicznych.
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