Blogs

Analyzing the business value of analytics

Analyzing the business value of analytics

April 3, 2015 | by Bob Palmer, Global Banking Industry Marketing, Big Data, IBM
In part seven of this multi-part series, we looked at the second key stage within the analytics lifecycle (Analyze), which focuses on analyzing the data and identifying the insights most likely to create a positive business impact. In part eight we will examine recommendations and practical actions...
Fluidity: The key to continuous confidence in cloud analytics

Fluidity: The key to continuous confidence in cloud analytics

April 2, 2015 | by James Kobielus, Big Data Evangelist, IBM
Fluidity is the degree to which your cloud data analytics resource can be rapidly and cost-effectively repurposed and reconfigured to respond to and proactively drive change in a dynamic world. The fluidity of the logical data warehouse depends on core interfaces, infrastructure and tooling that...

Changing what we know (and do) about the weather

March 31, 2015 | by Andy Rice, Vice President, Product and Analytics, The Weather Company
I have been in the weather and meteorological solutions industry for 15 years, but in the last five years I’ve witnessed an amazing transformation.
How social data is helping businesses make smarter decisions

How social data is helping businesses make smarter decisions

March 31, 2015 | by Sarah Warsaw, Social Media Specialist, Big Data, SWG UKI, IBM
IBM recently announced the incorporation of Twitter data into Watson Analytics. Find out how external data sources can help decision-making for businesses in a range of industries.
Meet the Internet of Things

Meet the Internet of Things

How the Jetsons help us understand IoT solutions

March 31, 2015 | by Pete Karns, Director, Internet of Things Cloud, IBM
In today's world there is a lot of hype surrounding the Internet of Things. Perhaps that’s because IoT has, and is demonstrating, the potential to disrupt nearly every system and business process we rely on. A full 37 years before IoT was coined, a visionary cartoon provided examples that we can...
Fight "Blacklist" criminals using real-time actionable intelligence

Fight "Blacklist" criminals using real-time actionable intelligence

March 26, 2015 | by Liesl Geier, Market Segment Manager, IBM
Describing intelligence software has gotten a whole lot easier as Hollywood continues to produce gripping spy shows like The Blacklist, Homeland and CSI. But while the layman description may have gotten easier, the real threatscape continues to evolve as criminal and terrorist networks continue to...
Delving deeply into the narrative hierarchies of computer vision analytics

Delving deeply into the narrative hierarchies of computer vision analytics

March 26, 2015 | by James Kobielus, Big Data Evangelist, IBM
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...
The evolving shape of distributed databases in the Internet of Things

The evolving shape of distributed databases in the Internet of Things

March 19, 2015 | by James Kobielus, Big Data Evangelist, IBM
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...
Only one of the 5 Vs of big data really matters

Why only one of the 5 Vs of big data really matters

March 19, 2015 | by Bernard Marr, Best-Selling Author, Keynote Speaker and Leading Business and Data Expert
People have been using the four Vs (Volume, Velocity, Variety and Veracity) to describe big data, but all of the big data in the world is no good unless we can turn it into Value, the fifth V of big data.

Big data: Not just for big business

March 18, 2015 | by Nick Rojas, Independent Consultant, Self-Employed
Though big data has long been thought to be the domain of solely large-scale enterprises, more and more this perception is proving to be false.