Real-time Analytic Processing at Your Fingertips
During a recent conference, I had the privilege of speaking with clients from many different organizations about their big data challenges. Most were very excited and just starting down the path of harnessing its power. Tempering this excitement was a concern about the complexity of big data technologies and questions about how to apply them effectively in a highly customized environment – one size certainly doesn’t fit all. While big data holds big promise, it does require new skills and technologies. Adding stress is the reality that business leaders demand greater insight immediately …. or sooner!
As data grows in volume and as it speeds across the enterprise, it is almost impossible to capture, understand and analyze the data using traditional technologies. Even if you do have the ability to capture the wide variety of data types proliferating throughout your IT environments – text, image, video, audio, financial transactions, GPS tracking, smart devices (just to name a few) – the time and money required to store and analyze it becomes untenable.
Furthermore, you might miss the opportunity to capitalize on the data. In some in-the-moment applications, the data can even become meaningless or obsolete if not used immediately. For example, someone who tweets “I am sure hungry for a pizza!” could receive a coupon for your pizza establishment via their smart phone. Receiving the coupon 12 hours later will have less value because it is likely the craving has been satisfied. This is where real-time streaming analytics can save the day.
With stream computing, you can perform advanced real-time analytics on data in motion. This means you can rapidly ingest, correlate and continuously analyze a massive volume and variety of structured and unstructured streaming data as it arrives from thousands of real-time sources. The end goal is to make real-time predictions, discoveries and analysis as data enters the system, because even one minute might be too late in the era of big data analytics.
To help you get started fast with big data and real-time analytics, IBM announced InfoSphere Streams Quick Start Edition. This brand new, no-charge offering empowers you to experiment with stream computing in your unique, non-production environment. There is no data limit or time limit. Read more on the InfoSphere Stream Quick Start Edition website.
When you download InfoSphere Streams Quick Start Edition, you get the core components of InfoSphere Streams but restricted use for non-production and no formal support option is available. You also become part of a vibrant community. See developerWorks for more information and also to access the free tutorials.
So what’s in the box? You have two options for download: native install or VMware image. In either case, InfoSphere Streams Quick Start Edition provides:
- A set of comprehensive development tools designed to make it easy for you to create Streams Applications. For example, drag-and-drop graphical editors, data visualization and visual application monitoring.
- When you download the native installation, you are provided a scale-out architecture. You can scale from a single server to an unlimited number of nodes to process millions of events per second with microsecond latency. The VMware image is limited to use on the downloaded machine.
- Sophisticated analytic processing.
If you find yourself challenged to analyze large volumes of data in motion, and you want immediate, accurate analysis for fast and informed decision-making, then get started now by downloading InfoSphere Streams Quick Start and exploring the tutorials today.
Want to learn more about InfoSphere Streams?
- InfoSphere Stream Data Sheet
- Executive Brief: Comparing Costs, Benefits and Risks for Use of IBM InfoSphere Streams and Open Source Storm
- Complete list of InfoSphere Streams Resources in the Streams Library
- You might also want to try InfoSphere BigInsights Quick Start - "Hadoop for the Enterprise"