stream computing

The first ever Forrester Wave for streaming analytics

Length: 13:38
July 21, 2014

Going, going...gone! That phrase has been used by auctioneers to indicate the final bid opportunity for a hot auction item. Now “going, going, gone” is being used in the world of big data. Why? Organizations realize that they need to act faster by analyzing streaming data and taking action in the moment. Streaming analytics identifies opportunities in real time that would be missed using traditional analytic models that require storing, cleaning and querying data.

Is there a business opportunity hiding in your fast moving big data? The answer is yes and the time to act is now. In fact, to quote from new Forrester Wave: Big Data Streaming Analytics Platforms, “The velocity of business demands streaming analytics.” To help you understand fast moving data, Roger Rea joins us to discuss the streaming analytics market and the results of this first-ever Forrester report on streaming analytics platforms.

If you want to learn more about real-time computing, visit www.ibmbigdatahub.com, where you’ll find podcasts, videos, blogs and more.

Developers who want to learn more about InfoSphere Streams should join the StreamsDev community - for developers by developers! Also download IBM InfoSphere Streams Quick Start - ibm.co/streamsqs

Developing real-time applications through open source

Length: 17:44
July 13, 2014

IBM has a long and successful history with open source, from running Linux on IBM PCs to contributing initial codebase for Eclipse. We believe a mix of open source and closed source is the best way to drive adoption in the marketplace. Having the full support of a vendor like IBM can lower risk while open source can help achieve customer requirements. In this podcast, Mike Spicer, lead architect for InfoSphere Streams, talk about IBM’s latest contribute to open source—the new GitHub project from InfoSphere Streams.

Learn more about this project at github.com/ibmstreams. Also visit Streams Dev site for developers at developer.ibm.com/streamsdev

Juggler or high diver: How do you work in real time?

Length: 16:44
June 16, 2014

If you take a quick glance at any technology publication (and many business publications as well) you will likely see some reference to real-time. There’s real-time customer service, real-time marketing, real-time analytics and the list goes on. But what does real time mean? Is there a standard definition? Should there be?

Roger Rea, product manager for IBM InfoSphere Streams, joined host David Pittman to share the surprisingly long history of "real-time computing," and explain how to tell if you are a juggler or a high diver when it comes to real-time analytics.

If you want to learn more about real-time computing, visit www.ibmbigdatahub.com, where you’ll find podcasts, videos, blogs and more. Developers who want to learn more about InfoSphere Streams should join the StreamsDev community for developers by developers! https://developer.ibm.com/streamsdev/ and download IBM InfoSphere Streams Quick Start: ibm.co/streamsqs

Building the business case for real-time analytics at CenterPoint Energy

Length: 34:04
April 7, 2014

Industry analysts project that 30% of companies will “monetize their data” by 2016. But what does this mean? Many organizations are trying to figure out how to turn their data into a gold mine. The reality is each business is unique and data monetization projects should be customized to focus on a particular outcome for that organization. Joining us for this podcast about their real-world data monetization projects are Bill Bell from CenterPoint Energy and Jim Sharpe from Sharpe Engineering. Bill is the Technology Director of Analytics & Data Services at CenterPoint Energy, and Jim has 35 years of industry experience and is a leading expert in complex low-latency analytics on big data for situational awareness and resource management.

You can download a free version of InfoSphere Streams Quick Start Edition to play around with the product and see what it can do for you at ibm.co/streamsqs

For more information about the IBM big data platform and products, visit www.ibm.com/bigdata. For more podcasts, blogs, videos, infographics and other resources, visit www.IBMBigDataHub.com.

Going with the flow: The evolution of CEP to stream computing

Length: 17:10
March 26, 2014

Stream computing is a natural evolution of Complex Event Processing, also known as CEP, but it has broader uses on a wealth of emerging streaming data sources, such as weather and transportation data, and videos as well.

Roger Rea, product manager of InfoSphere Streams, explains what stream computing is, how it differs from event processing and CEP and gives examples of how companies are employing stream computing for real-time analyses and applications.

You can download a free version of InfoSphere Streams Quick Start Edition to play around with the product and see what it can do for you at ibm.co/streamsqs

For more information about the IBM big data platform and products, visit www.ibm.com/bigdataFor more podcasts, blogs, videos, infographics and other resources, visit www.IBMBigDataHub.com.

Comparing Complex Event Processing and Stream Computing - Why Should You Care?

Length: 17:06
August 1, 2012

What is “event processing”? What are the similarities and differences between complex event processing and stream computing? Why would you want to use these techniques? Roger Rea, IBM InfoSphere Streams product manager, answers these questions and others.