How to build customer loyalty using e-commerce

February 11, 2015 | by Sarah Warsaw, Social Media Specialist, Big Data, SWG UKI, IBM
E-commerce is a trillion dollar business, however the industry is being affected by high return rates, which are detrimental to their profits. How can analytics help to reduce these return rates for retailers across the web?

Spooky action at a personal distance

February 5, 2015 | by James Kobielus, Big Data Evangelist, IBM
Big data analytics is getting positively spooky in its ability to infer our intentions in real-time and in the context of our environments. In the Internet of Things (IoT) era, voice inputs, gestural interfaces, and data-driven inferences will be able to drive remote actions in your personal domain...

Using predictive analytics to win

January 30, 2015 | by Tim Moran, Director of Interactive Sales, WNEP-TV /
It’s that time of the year again: when fans begin lining up at the supermarkets to plan football weekend festivities. Let's take a look at how can predictive analytics be used in analyzing everything from performance to parking at the big event.

Managing data at speed requires flexibility and agility

January 30, 2015 | by Bob Palmer, Global Banking Industry Marketing, Big Data, IBM
In part five of this series we explored Acquire, the first of three key stages within the analytics lifecycle, which provides the ability to acquire and integrate data quickly—foundational to creating an analytics speed advantage. In part six we will look at recommendations and practical actions...

Good times with fast data

January 29, 2015 | by Kimberly Madia, Worldwide Product Marketing Manager, InfoSphere Streams, IBM
What’s your idea of a good time? How about lighting fast performance, scalability and cool applications? Learn why it’s true that the fastest data also has fun and innovative applications.

Data scientists need to nip model overfit in the bud

January 29, 2015 | by James Kobielus, Big Data Evangelist, IBM
Overfitting is an unfortunate consequence of top notch data scientists attempting to refine their statistical models. It stems from the tendency to skew data science models by starting with a biased set of project assumptions that drive selection of the wrong variables, the wrong data, the wrong...

Protect yourself on Data Privacy Day

January 28, 2015 | by Richard Lee, Managing Partner, IMECS, LLC
Data Privacy Day is now much more than a day of focus on protecting your online data and personally identifiable information; it is now a stark reminder to everyone as to just how much our personal privacy is in jeopardy and how each of us must defend and protect this right.

Data masking factories for the big data era

January 28, 2015 | by Praveenkumar Hosangadi
There is a growing trend among larger companies to develop mature and repeatable processes. One such growing trend is the use of data masking factories where repetitive processes are executed as a centralized service for large numbers of applications.

Landing your big data on cloud without compromising security

January 27, 2015 | by Amy Xu, IBM Senior Solution Architect, IBM
As enterprise data centers continue to process more and more information, many organizations are considering cloud-based storage resources but have concerns about the security risks of such a move.

Extending the power of R to everyone

January 26, 2015 | by Mikhail Lakirovich, Product Marketing Manager, IBM
Learn how Predictive Extensions for IBM SPSS Modeler enables users to leverage the power of R with a simple download and connection to their SPSS Modeler stream.