In a previous post, we discussed the importance of the rising tide of real-time, sensor-generated data—aka Data in Motion—that will gather momentum as the Internet of Everything emerges. Unlocking the potential of Data in Motion cannot be achieved by analyzing stored data or by examining historical data. Rather, it requires tools and interactions that capture value here and now, in real time.
The intelligent network plays a key role here. It can add contextual information such as location, identity and presence while the data is moving. Value can be extracted and acted upon through policy changes, security enforcement and packet processing, as events occur to create advantage here and now, or even to predict the future. By harnessing the value of Data in Motion through the intelligent network, organizations can make better decisions, deliver enhanced experiences to their customers, partners and employees, and build a competitive advantage over the long term.
For example, to maintain and improve patient care in a 
cost-effective way, healthcare providers can use Machine-to-Machine (M2M) technology to remotely monitor the progress of patients in their homes. Remote monitoring is more efficient and cost effective than having patients repeatedly visit healthcare facilities. As real-time healthcare applications continue to develop, Data in Motion will help patients take more proactive control of their own health, using instant biofeedback to help them modify personal behaviors.
To be clear, Data at Rest is not without value. Indeed, combining it with Data in Motion can produce optimal business outcomes. Data at Rest provides the context for creating the actionable insights from Data in Motion, helping organizations analyze and understand the past while they take contextual action on events in real time.For instance, by tracking a consumer’s real-time location and historical online interaction, a retailer could develop valuable contextual information while enabling store touchpoints with mobile access. With an up-to-the minute view of customers, the retailer could send customized promotions in real time.
And then there’s the opportunity for service providers. For most of them, Data in Motion represents a largely untapped opportunity, despite the wealth of data flowing through their networks. Think of the potential. Their networks and users are constantly generating huge amounts of real-time and near real-time data, packed with details like location, content and subscriber information—much of which can be analyzed and correlated in real-time to create usage and traffic patterns, network congestion analytics, media behavior, dwell times analytics and more. A service provider, for example, could extract detailed data such as a user’s device type, data quota, recent Internet activity and current connection speed. Armed with this real-time intelligence, the provider could offer highly targeted mobile advertising or sponsored data—and charge a premium for it.
Harnessing the potential of Data in Motion creates business opportunities but also new IT challenges. In a next post, we will look at some of these challenges and how to best address them.
Great insights and I love the notion of data at rest and in motion. It helps me better understand/articulate the value additive properties of analytics properly used in a network to go from reactive reporting to developing pre-emptive business outcome impacting results.