In the extremely competitive automotive industry, leaders are looking for ways to differentiate their products by offering an improved driver experience.
One way to achieve this objective is to leverage the wealth of information coming from an increasingly instrumented world. Industry analysts
"Data in motion" is one of the key aspects of big data. Being able to harness and use data in real time as it flows through sensors and systems has many applications, from improving call-center operations to preventing manufacturing malfunctions. Watch as Roger Rea, product manager of Infosphere
As I wrote in Part 1 of this blog series, big data and analytics can help companies develop the “digital oilfield”— integrated operations that unite operational technology (OT) with information technology (IT) to improve decision making and enhance operational and business performance. Adding
Big data is a new natural resource. Like other natural resources, big data needs to be successfully mined, refined and delivered in order to create value.
Organizations first need to mine big data through Exploration. Exploration is finding, connecting and understanding the value of all available
We’ve got a new zone on developerWorks, dedicated to big data and to architects and developers looking to build analytics applications to derive insight from that data. It turns out developerWorks was already covering big data to some extent, just not in a classic developerWorks “zone” format. And
Big data has its discontents. The backlash is a necessary reality-check in an otherwise vibrant arena. Often in this industry, when a technology is vogue, the hype can interfere with rational decision making, both among users and among solution providers.
Big data tends to focus on extreme scale.
Quality-of-service (QoS) is one of the most paradoxical metrics in the telecommunications industry. “Quality” of the customer experience is normally measured through surveys and logged feedback, but plenty of data can lead to good quantitative measures.
The University of California, Los Angeles (UCLA), announced their work to develop a bedside early-warning system for brain pressure in traumatic brain injury patients. At the core of this system is InfoSphere Streams, which can ingest and analyze, in real-time, huge volumes of fast-moving data –
The UCLA Department of Neurosurgery analyzes brain wave data to predict the rise of deadly brain pressure as part of a National Institute of Neurological Disorders and Stroke study. Knowing in advance that brain pressure could potentially rise in TBI patients gives doctors more time to prevent
Smartphones and other mobile gadgets have become integral to every aspect of modern life. So it’s no surprise that enterprises everywhere are starting to tap into them as a rich source of data for deep analysis in Hadoop, NoSQL and other big-data platforms. By the same token, mobile devices are
Most of us don’t think of big data as a personal resource for mobility, but, clearly, that thinking will need to change. Smarter mobility depends on the ability to serve all of our mobile devices from an intelligent big-data infrastructure
Cyberspace is today’s new battleground, and cyber security continues to be a top imperative for both enterprises and governments. This is where big data comes in. IBM® Security QRadar® uses big data capabilities to help keep pace with advanced threats and prevent attacks before they happen. It
“The hardest part of any journey is taking that first step.” - Unknown
No, Tony Robbins is not guest blogging today. And it’s a shame, too, because if he were, he would come up with plenty of inspiring quotes designed to help you overcome the perils of a big data journey. He’d motivate you to build
Infographic: Certain things cannot be overlooked when dealing with data. Best practices must be instituted for the care of big data just as they have long been in small data. Before enjoying big data's amazing analytical feats, you must first get it under control - with tools that are up to the