Capgemini’s Optimization of Data for the Enterprise

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In this age of big data, new technologies and methods have evolved and matured to the point where organizations are able to economically store and exploit the increasing volume, variety, and velocity of data at a fraction of the cost of traditional data warehouse technologies. In addition to traditional data sources such as CRM and […]

In this age of big data, new technologies and methods have evolved and matured to the point where organizations are able to economically store and exploit the increasing volume, variety, and velocity of data at a fraction of the cost of traditional data warehouse technologies. In addition to traditional data sources such as CRM and ERP, business leaders are now increasingly demanding integration with external sources such as social media, the internet of things and data provided by third parties in order to derive meaningful and actionable insights. Big Data technologies are allowing organizations to harness these unstructured and semi-structured data types, much of which was previously inaccessible due to its sheer volume and the structured bias of traditional EDW1 systems. Whether you are in a highly regulated industry where the archiving of increasing volumes of historical data is mandated by law or in an industry where near-real time access to all relevant data provides a sustainable competitive advantage, this ability to obtain greater value from your data assets can be the difference between success and failure.

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