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What is real-time data management and why does it matter?

Ask most people what data management means to them, and they’ll probably mention data integration, data quality, or database administration. But as decisions and business processes become increasingly information-reliant, there’s more to it: trustworthiness, availability, security, ease of access, and integration with other data are now hygiene factors.


Businesses embarking on initiatives to deliver new insights from Big Data, real-time queries, and predictive analytics – with a focus on what’s happening in the moment or in the future – can’t afford to lose momentum to creaking platforms, data silos, and disjointed systems. They need a robust and reliable way to deliver answers and interactions to the edge of the enterprise.

Of course, no established enterprise has the luxury of a blank sheet of paper. The way forward begins with the acknowledgement that an accumulation of hundreds or thousands of applications and databases has led to data fragmentation. Explosive data growth is pushing the limits of storage, security, administration, and quick access. And despite processor speeds, cores, and threads quadrupling over the years, organizations are still struggling with scalability and performance issues through a combination of unpredictable workloads, rampant data growth, poorly designed applications, and access and integration issues.


As real-time data management becomes indispensable to new ways of doing business, organizations are urgently looking for a real-time platform that is tuned and optimized to cope. In fact, according to an April 2013 Forrester Consulting survey of several hundred IT professionals, commissioned by SAP, 72% of
enterprises that don’t have real-time data management in place plan to do so within two years.

To find out more about the trends that are driving interest in real-time data management, check out our second blog in the series or watch our short

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