The concept of real time data management isn’t new; it’s been around for decades. But only a few businesses have succeeded in building a real-time platform from the ground up that will support the agility and scalability they crave.

The problem is that it’s not a straightforward matter to integrate data from disparate sources in real time and support an on-demand transactional platform that can handle unpredictable workloads. Budget is often a show-stopper. According to an April 2013 Forrester Consulting survey of several hundred IT professionals, commissioned by SAP, two in five organizations found that their real-time data platform efforts were hampered by a lack of IT budget. But tellingly, most were expecting their expenditure on real-time data management to increase.

A similar proportion of organizations lack the expertise or knowledge to support the programming, administration, and integration requirements of traditional in-memory solutions. A further roadblock is the complexity of existing data sources, as the integration of unstructured data requires a deeper understanding of its association with structured data than many businesses have today.

However, recent technology advances, lower hardware costs, and innovation have helped overcome these issues. A combination of distributed in-memory storage, data virtualization, Big Data solutions, predictive analytics, enterprise data modeling, data governance, and data streamlining and replication tools can deliver an economical real-time data management platform that will satisfy any enterprise requirements.

If that sounds like an extensive shopping list, you’ll welcome the news that these components are available as part of a single, software-based architecture for data management and applications that can be deployed modularly. SAP® Real-Time Data Platform does precisely this.

In the next blog in this series, we’ll explore the IT and business benefits of real-time data management. Meanwhile, to see how it all fits together, visit or watch our short video.