Yoda: Big Data Potential — and Ignorance

IO Impotency
Got Crowd? BE the Force!
Got Crowd? BE the Force!

Baby steps…

What Big Data Can Mean for Sustainability

The first Industrial Revolution showed the world how much machines could accomplish. What GE calls the “Next Industrial Revolution” is now showing how much machines can accomplish when they communicate with each other. And just as steam — and later electricity — powered the first industrial revolution, Big Data is powering the second. Machine-to-machine communication (M2M) gave birth to the age of Big Data and advances in big data are expanding our sense of what the Internet of Things can accomplish in the coming years.

It’s too soon to know whether or not the promise of Big Data is being overstated. Google Trends shows that the number of news references for “Big Data” has increased ten-fold since 2011. Comparing that with the Gartner Hype Cycle suggests that the concept may be nearing its “Peak of Inflated Expectations” and will soon be sliding into a “Trough of Disillusionment” [see accompanying graph]. Still, if the Hype Cycle is an accurate forecast of the future, it seems reasonable to expect great things from Big Data once it reaches the “Plateau of Productivity.”

The Four V’s of Big Data

According to Wayne Balta, vice president of corporate environmental affairs and product safety at IBM, Big Data is defined by the four V’s: volume, velocity, variety and veracity.

Read full article.

Phi Beta Iota: The article focuses on a 1% improvement in efficiency in five of today’s major industries: aviation, health care, power, rail, and fossil fuels. This means that the article is focusing on incremental improvements in legacy industries instead of design improvements of the whole. In my circles, that is considered counter-productive. Volume of garbage, zero velocity, insipid variety, and near zero veracity. Until you can do holistic analytics, true cost economics at the component level, and open source everything engineering, you are deepening the problem rather than devising affordable, interoperable, scalable solutions.See Especially:2014 Robert Steele: Appraisal of Analytic Foundations – Email Provided, Feedback Solicited – UPDATEDGraphic: Embedded Intelligence — Adding Open Source Everything (Engineering Intelligence), True Cost Economics (Supply Intelligence) and Holistic Analytics (Demand Intelligence)

See Also:

Big Data @ Phi Beta Iota