Stream computing combines data streams with an increasingly broad range of applications designed to help businesses solve problems of all kinds. Learn more about how you can capture data streams and infuse them into your applications.
Data shows that organizations spanning many industries can transform business and enhance growth by using cloud-based delivery models for applications and streaming analytics. But not every business scenario is well suited for services through the cloud. Take a look at five signs that an
Stream computing makes dependably analyzing continuous data streams from sensors, social media or mobile device data efficient and effective. Even with multiple uses for big data in every industry, the end goal for organizations is to take advantage of stream computing to capture previously
The data warehouse has never been more relevant than it is now. The DW’s role in the big data universe appears likely to grow. What the DW does, above all else (and this is far from its only role in many organizations) is serve as hub for governing your system-of-record data to be delivered into
Deep learning algorithms are growing progressively smarter at recognizing patterns in video, audio, speech, image, sensor and other non-textual data objects. Correlation of deep learning model results with other sources of contextual information can show how the information supplied by media and
Databases are evolving into a new stream-centric architecture that is well-suited to real-time distributed analytic computing in the Internet of Things. This new paradigm will leverage distributed event logs, temporal database concepts and materialized views as core architectural concepts. As it
Since the kickoff of the InterConnect solution expo on Monday, the traffic around the IBM InfoSphere BigInsights and InfoSphere Streams booth has been nonstop as several hundred folks stopped by to get the scoop on Hadoop and stream computing.