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Data virtualisation on rise as ETL alternative for data integration
This article is part of the IT in Europe issue of August 2012
Data virtualisation is emerging as a possible technique for businesses to use in tying together disparate databases to become more agile in both their business operations and their data integration processes. Traditionally, companies have relied on data integration technologies, such as extract, transform and load (ETL) tools, to pull data from transactional systems and populate data warehouses for business intelligence (BI) and analytics uses. But for applications that require real- or near-real-time decision making, getting critical business insight out of an ETL-fed data warehouse can seem as effective as sending Lewis Hamilton out to qualify for a Grand Prix in an Alfa Romeo Series 1 Spider. The iconic 1960s roadster is a lovely machine, but one that’s likely to fall far short of Formula One’s uncompromising need for speed. More on data virtualisation Get this quick definition of data virtualisation ETL vs ELT? Understand the differences between them Learn how HealthNow New York plumped for Informatica over IBM and Composite...
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