"To boldly go where no man has gone before."
With that straightforward phrase, Captain Kirk inspired not just the crew of the Starship Enterprise, but all of us to follow him on an incredible journey. He exuded confidence that came from not being afraid to explore. In that spirit, I offer 4 new
When you start thinking through Hadoop and all of this big data technology, you start to realize that it might take more than a few minutes to set up and run.
As technologists ran through the first wave of Hadoop, only the advanced early adopters spent the time to master the vast array of
Interest in big data remains high. In fact, according to the 2012 study “Analytics: The real-world use of big data” that surveyed more than 1100 executives and practitioners from 95 countries, 75 percent of organizations have big data activities underway.
But that same study also uncovered two
Lawrence Weber explains how to get started with IBM InfoSphere BigInsights Quick Start Edition. Quickly learn how to manage Hadoop and work with Big Data using the BigInsights Web Console.
With the growing popularity of cloud computing, enterprises are seriously looking at moving workloads to the cloud. There are issues around multi-tenancy, data security, software license, data integration, etc., that have to be considered before enterprises can make this shift. Even then, not all
In our Friday Data Flick series this week, we look at how companies are achieving an “enhanced 360-degree view of the customer,” which is another of the top five uses for big data (also called “use cases”). In less than 15 minutes, you can watch these two videos and walk away with a thorough
This week’s Friday Data Flick gives you insight into “operations analysis,” which is one of the top five uses (also called “use cases”) for big data. Operations analysis is about analyzing a variety of machine data to get improved business results. The key is combining machine and business data,
Dr. Michael Kowolenko, Principal Research Scholar, shares how North Carolina State University helps businesses make better decisions and gain insight using IBM big data solutions.
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Given the explosion in the volume, variety and velocity of data growth, it is clear that big data has a low value per byte compared to the traditional enterprise data. An oft repeated analogy to this is a gold mine where you dig tons of dirt to discover an ounce of gold. But, enterprises can still
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
One of the recurring themes at yesterday’s “Big Data at the Speed of Business” launch was comsumability, which is just a fancy word for ease of use. Let’s face it, Hadoop can be hard; big data can be complicated, and there’s certainly a learning curve involved in being able to leverage most big
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.
In this series of videos Andrea Ames explores the capabilities of IBM's Accelerator for Machine Data Analytics, a collection of Big Data applications used to analyze log files and machine data. In the final part of this series, Andrea explores significance analysis.
In this series of videos Andrea Ames explores the capabilities of IBM's Accelerator for Machine Data Analytics, a collection of Big Data applications used to analyze log files and machine data. In part 4 of this 5 part series, Andrea works through an example of frequent sequence analysis.