By Michelle Kimihira on Jan 28, 2013
Original post in The Fusion Middleware Newsletter.
Today, IT and business users are trying to better use information to innovate and transform their businesses. The buzz revolves around how to successfully harness the four V’s of big data: volume, variety, value, and velocity.
A fair amount of attention has been focused on building strategies to successfully corral the huge volume of data generated through sources such as social media, sensor data, Weblogs, and partner and customer data. Companies are adopting databases such as Hadoop and NoSQL to help assimilate and manage the variety of unstructured and semistructured data types found in big data. For most, the primary goal is to identify good information embedded in nontraditional data to create economic value for the organization. But the velocity at which the data is accumulated is also intriguing, and possibly the least explored aspect of big data so far.
An upcoming Webcast “Fast Data—Turning High-Velocity Data into Value,” focuses on the emerging topic of fast data and the products, solutions, and services Oracle offers to help your organization implement a fast data strategy.
Fast Data: Managing Big Data Velocity
Big data is inherently dynamic, both in terms of how fast it comes at you and how fast you should consume and analyze that data to make better decisions and create value. This is where a concept known as “fast data” comes in, says Amit Zavery, vice president of Oracle Fusion Middleware product management. “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,” he says.
Companies need to tackle velocity in a number of different ways, including
- Manage the information flow. When data comes from a fire hose rather than a faucet, it makes sense to remove extraneous data and more quickly get at the actionable information.
- Use event processing. Companies can use predefined rules and filters to get to real-time insights quickly.
- Implement real-time integration and transformation. Companies can capture data and events immediately and move information where it is needed—and in the right format—to best support decision-making.
- Adopt analytics and business intelligence. Companies’ strategies should support both automated decision-making and more complex, human-based interactions, such as business process management.
“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,” says Zavery. “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, transform, analyze, and move information from big data sources quickly and efficiently, enabling both real-time analysis and further business intelligence work once the information is stored. Moreover, the appeal of fast data has grown well beyond bellwether industries such as financial services. As mobile solutions and increased volumes of data become commonplace across many industry sectors, the value of applying a fast data strategy as an end-to-end solution has become more apparent.
Find out what fast data solutions Oracle offers in an upcoming Webcast “Fast Data—Turning High-Velocity Data into Value.”
Read a blog post about fast data.
Watch the Oracle OpenWorld 2012 Middleware general session video to hear more about fast data from Hasan Rizvi, Oracle executive vice president of middleware development.