By Dain C. Hansen on May 24, 2013
If it’s hot cars, fast action, and bad acting you want, definitely you are in the wrong movie theater. But if it’s real-time insights and high value from high velocity data you are looking for, checkout our own little action movie below. Fast data is the latest term that has hit the streets and is ripping a hole in the traditional pavement of how we think of our information architecture. It’s about embracing the element of real-time and high velocity when it comes to all forms of data. It's about finding new ways to act on that elusive data across machines, applications, and from our customers. This data is constantly in flux and changing every minute.
In the last few weeks, we’ve seen 6 new ideas come across that really unveil some new thinking around Fast Data.
1) Real-time are the most critical data insights for making decisions (especially employees). In a recent study by the Economist Intelligence Unit, In Search of Insight and Foresight, Getting More out of Big Data. In one survey response, 48% of employees cited that real-time data (i.e. Customer interactions) was the most critical for making decisions. This was above all forms of data insights including qualitative, historical, trends, and predictive analytics. For CEOs, CIOs, CFOs however, this real-time information was much lower in importance. What this tells us is that the way data is treated in the organization needs to be carefully planned and considered.
2) Machines need to be smarter if they are going to keep up with us – In the recent article by Oracle Profit Magazine, Data at the Speed of Life Ed Zou, vice president of Oracle Fusion Middleware product management, writes, “the right technology needs to be put into place not only to harvest machine-to-machine (M2M) fast data but also to filter it in some way so that only the most important information is available to be acted on in real time. Otherwise, tens of thousands of devices capturing data every second and all the fast data being sent unfiltered could cause not only a deluge at the data center, but an overwhelming amount of traffic on the network”.
3) Fast Data requires an event decision architecture - Pete Utzschneider, Vice President Product Management at Oracle, suggests in this article the best way to combine fast data technologies with M2M makes it possible to create an "event decision architecture" that can be used in making changes in operations and customer service. It is possible to collect the data from a massive number of devices as it becomes available, run it through Oracle Event Processing on a server and make decisions about large and small issues that affect profitability.
4) Fast processes dictate a Fast Data approach to applications – In the article by Tony Baer, Ovum Principal Analyst, Oracle puts applications in the Fast Data lane. Baer talks about the advantages of using in-memory technologies and put them to work for business applications. These in-memory applications put all of their logic in, and write transactions straight to Flash storage where the disk is only used for ‘cold data’. Oracle’s In-memory applications include selected offerings from the PeopleSoft, JD Edwards, Oracle E-Business Suite, Siebel, and Hyperion portfolio. These new applications can run 20x faster using this technology.5) In-memory is not just a passing fad - Take a look at Stephanie Mann’s (@StephMannTT) recent article, Look out, Big Data: In-memory data grids start to go mainstream , she writes, “the rise of in-memory data grids (IMDGs) -- or in-memory distributed caches -- is part of a larger trend in big data technology. Gartner reports that markets aligned to data integration and data quality tools are on an upward swing, set to push IT spending to $38 trillion by 2014”. And adding to Mann's point: Oracle Coherence is a great example of this technology at work, and is part of the overall Oracle Fast Data Solution which works especially well with Oracle Event Processing.
6) Big Data acceleration needed - In his recent article Big Data Good, Fast Big Data Better Adrian Bridgewater talks how ‘speed’ is what he calls the ‘unloved second cousin of Big Data’. He goes on to say that “Analytics without real-time analytics is like a car at full throttle without a steering wheel, i.e., we need to be able to react to data in the real world and navigate through it without crashing.” Thank you Adrian for this wonderful car analogy and it goes perfect with Fast Data and the Furious 6 Ideas. I couldn't agree more with the headline that big data and fast data are better together.