IT and business don't always agree on big data

Not all decision makers within an organization are on the same page with respect to big data plans. The disparity is due to the different perspectives of the business and IT end of the organizations.

Read more: IT, business have different views on data - FierceBigData 

Analysis in light of the Pareto Principle

Many businesses who are not getting as much utility out of big data as they would like identify the source of the problem as their inadequate hardware, and inadequate finances. However, in a Smart Data Collective post, Paige Roberts argues that it's not the hardware, but the software that's to blame.

"Investing in better utilization of existing hardware is a far better, more sustainable, and cost-effective solution" for businesses who find their current setups inadequate. Roberts points to the inefficiency built into current "utilization rates of hardware [that] are around 15 percent worldwide." Even the most efficient data centers max out at only 20 percent, meaning that 80 percent is untapped.

Do those numbers ring a bell?

Read more: What's the real problem with the hardware? - FierceBigData

What do Long Island and Arlington, Texas have in common?

The answer is science. This topic was of particular interest to me because I've visited Brookhaven, one of the institutions involved in the partnership, multiple times. It's on Long Island, which, surprising, as that may be, actually has quite a history in connection with science as engineering, including the space program. 

Their goal is to extend the PanDA system for more general applications. Brookhaven and UT Arlington originally developed the workload management system to process the massive quantities of data involved in a component of the research of the Large Hadron Collider, or LHC.

Read more: Project aims to improve big data processing for science and engineering - FierceBigData http://www.fiercebigdata.com/story/project-aims-improve-big-data-processing-science-and-engineering/2012-09-11#ixzz26BQk146W 

The ROI of social media marketing

SumAll’s “vision” is based on “making data beautiful, affordable and accessible.” Its target is small and medium sized companies that have not had the same access to the analytics tools that larger companies have used to “leverage their data to make better decisions and more money” Like Toms and Warby Parker, SumAll declares itself devoted to  “do good by doing right.” To that end, it grants a share of itself to SumAll.org. 10% of its ownership to a non-profit called. 

The company itself is not intended to be nonprofit, planning on charging for premium services in future, though for now at least,  tool is available for free.

Read more: SumAll pins an ROI on social media metrics - FierceBigData http://www.fiercebigdata.com/story/sumall-pins-roi-social-media-metrics/2012-09-06#ixzz25iYqd6Rh 

When Big Data becomes Big Brother

You are being watched. Does that make you feel safe or make you feel exposed? The answer to that question determines whether people applaud or decry New York City Mayor Michael Bloomberg's latest initiative. Not everyone is ready to surrender their privacy to Big Data even for a system supposedly designed for their own good. 

Read more: When big data becomes big brother: New York City's system for crime prevention - FierceBigData http://www.fiercebigdata.com/story/when-big-data-becomes-big-brother-new-york-citys-system-crime-prevention/2012-08-30#ixzz25iNx32rh
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What's in a name?

Should data scientists be called "data artists?" That is what someone contend, as I discuss in 

What is a 'data scientist'?

Ultimately, working with Big Data effectively calls for using both the creative and methodical parts of the brain. In that way, it is, indeed, a science as Einstein  described it: “The mere formulation of a problem is far more essential than its solution, which may be merely a matter of mathematical or experimental skills. To raise new questions, new possibilities, to regard old problems from a new angle requires creative imagination and marks real advances in science.”

Can algorithms render humans obsolete?

Apparently not altogether. Read my post on the limits of algorithms for people who still clamor for the human touch:  The ascendancy of the algorithm and human resistance - FierceBigData http://www.fiercebigdata.com/story/ascendancy-algorithm-and-human-resistance/2012-09-06#ixzz25iKRGHh8