Barbara Wetmore is a long-time editor at IBM developerWorks, having managed the Architecture, Open source, and Web development zones in the past. She's currently trying to move from the befuddled to enlightened state when it comes to big data, her latest undertaking. You can help her on her journey by contacting her at email@example.com.
July 10, 2014
This month’s articles show the promise of big data technology in action. Explore the tools that help you digest the data, filter out the noise and make your next business decision based on the trends it reveals. Grab your safety goggles—it’s time to put theory to the test.
June 2, 2014
developerWorks Editor Barb Wetmore brings you a summary of the latest how-to technical content for developers. This month includes an announcement of a new big data and analytics zone on developerWorks, integration of DB2 for z/OS with InfoSphere BigInsights, creation of a date time dimension with IBM Cognos software and real-time analytics using IBM Predictive Maintenance and Quality.
May 5, 2014
DeveloperWorks big data and analytics editor, Barb Wetmore, brings you a summary of the latest how-to technical content for developers. This month includes enabling Watson to use sensor data, using the BLU Acceleration service in the Codename: BlueMix cloud platform, detecting and tracking the physical activity of mobile phone users and more.
March 6, 2014
Do you know how many olives it takes to make that tablespoon of olive oil you just doused on your lunch salad? It takes a big pile of olives. More than 50.
January 1, 2014
If your new year resolutions include getting more familiar with big data and honing your skills, here’s a quick, easy-to-scan glimpse of some highlights you might have missed during your holiday celebrating. Think of these resources as items on the grab-and-go aisle in the café.
December 17, 2013
Quick. Name one difference between data and big data. It’s bigger, of course, and it comes in faster, in more shapes and sizes. Sometimes it’s hard to sort the trustworthy from the noise. For a big data developer, the trick is to find tools and technologies that can be applied to traditional methods of processing and analyzing data.