It is now almost impossible to talk about digital transformation and not talk about ‘big data.’ As data has become one of the chief drivers of competitive advantage, entire business models now center around harvesting and harnessing every form of data imaginable. But as data volumes explode and more of it comes in unstructured forms, organizations find themselves spending more time cleansing, transforming and joining data sets than they do realizing value from that data.
AuriQ, a firm that has been working in data analytics since 1996, has introduced a new big data platform called Essentia that they believe will help enterprise organizations perform data analysis on large data sets more quickly, efficiently and affordably. They accomplish this using the combination of data virtualization and in-memory processing — a combination that they claim provides their clients with a significant advantage when dealing with very large, unstructured data sets.
Their approach to data virtualization of unstructured data enables them to ingest data once and then virtually categorize and transform the data without ever moving it or changing the raw data itself. Once virtualized, their architecture and use of highly scalable in-memory processing enables users to cleanse, explore and analyze data interactively and in real-time — even with extremely large or complex data sets. The speed resulting from the combination of data virtualization and in-memory processing is particularly beneficial in complex use cases that require large, complex data sets from a multiple structured or unstructured sources.
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