Monday Feb 25, 2013

Connecting Velocity to Value: Introducing Oracle Fast Data

To understand fast data, one must first look at one of the most compelling new the breakthroughs in data management: big data. Big data solutions address the challenge today’s businesses are facing when it comes to managing the increasing volume, velocity, variety of all data - not just data within as well as about the organization. Much of the buzz and to-do around big data has been around Hadoop, NoSQL technologies, but little has been talked about velocity. Velocity is about the speed this data is generating. In many cases the economic value of this data diminishes fast as well. As a result, companies need to process large volumes of data in real-time and make decisions in a more rapid fashion to create value from highly-perishable, high-volumes of data in business operations.

This is where fast data comes in. Fast data solutions help manage the velocity (and scale) of any type of data and any type of event to enable precise action for real-time results.

Fast data solutions come from multiple technologies, and some of the concepts, such as complex event processing and business activity monitoring, have been in use in areas such as the financial services industry for years. But often, the pieces were used in isolation—a complex event process engine as a standalone application to apply predefined business rules to filter data, for example. But when these concepts are tied to analytics, capabilities expand to allow improved real-time insights. By tying together these strands, companies can filter/correlate, move/transform, analyze, and finally act on information from big data sources quickly and efficiently, enabling both real-time analysis and further business intelligence work once the information is stored.

Oracle’s Fast Data solutions offer multiple technologies that work hand-in-hand to create value out of high-velocity, high-volume data. They are designed to optimize the efficiency, scale for processing high volume events and transactions.

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