David F. Carr in an article about DJ Patil and his work on Big Data at LinkedIn:

That is what he means by data jujitsu, where jujitsu is the art of using an opponent’s leverage and momentum against him. In data jujitsu, you try to use the scope of the problem to create the solution—without investing disproportionate resources at the early experimental stage. That’s as opposed to data karate, which would be a direct frontal assault to hack your way through the problem.

Original title and link: Data Jujitsu and Data Karate (NoSQL database©myNoSQL)

via: http://www.informationweek.com/thebrainyard/news/strategy/231900611/web-20-expo-linkedins-big-data-lessons-learned

Chris Anderson in a 2008 article:

Sixty years ago, digital computers made information readable. Twenty years ago, the Internet made it reachable. Ten years ago, the first search engine crawlers made it a single database. Now Google and like-minded companies are sifting through the most measured age in history, treating this massive corpus as a laboratory of the human condition. They are the children of the Petabyte Age.

The Petabyte Age is different because more is different. Kilobytes were stored on floppy disks. Megabytes were stored on hard disks. Terabytes were stored in disk arrays. Petabytes are stored in the cloud. As we moved along that progression, we went from the folder analogy to the file cabinet analogy to the library analogy to — well, at petabytes we ran out of organizational analogies.

Original title and link: The Data Deluge Makes the Scientific Method Obsolete (NoSQL database©myNoSQL)

via: http://www.wired.com/science/discoveries/magazine/16-07/pb_theory

What to look for when hiring a data geek—a different name of the now established data scientist role

• A strong background in computer science is essential. Dealing with information is not easy. The data geek needs to be able to collect the data, which in many cases involves knowing about databases, some networking, and Web programming technologies (XML, HTML, etc.), for a start.
• Statistics and mathematics are part of the game. Your data geek needs to know statistics inside out and backwards, and the software for manipulating them to develop an analysis.
• Data visualization is key. You need data visualization tools that are in equal parts useful and appealing. Your data geek should have an eye for graphs, maps, and charts, with a feel for the right dashboards, scorecards, data mashups, or even Excel workbooks—to generate the right mix of information for the right people.
• A bit of creativity goes a long way. The right data geek will use all the above skills to create new and improve existing ways to increase the return on investment (ROI) of your organization’s BI solutions.

Many different opinions on what data scientists should know and do.

Original title and link: You Need to Hire a Data Geek (NoSQL database©myNoSQL)

via: http://blog.technologyevaluation.com/blog/2011/06/06/got-bi-now-you-need-to-hire-a-data-geek-heres-what-to-look-for/

Infoworld published a non scientific research on the hottest new jobs in IT and Data scientists and Cloud architects made it in the top 6.

About data scientists:

According to Norman Nie, CEO of Revolution Analytics, data science jobs will require workers with a spectrum of skills, from entry-level data cleaners to the high-level statisticians, yielding a range of opportunities for newcomers to the field. As the business world gets increasingly social, the demand for people to plumb the depths of all that social networking clickstream data will only increase. The cliché going around is that “data is the new oil.” A career in refining that raw material sounds like a good bet.

Cloud architects:

In addition to establishing and managing a private cloud infrastructure, Ron Gula, CEO of Tenable Network Security, says cloud architects will increasingly need to be experts in choosing public cloud services. “When you get into the nuances of SLAs, you become less of an IT person and more of a lawyer,” says Gula. The ultimate goal is the hybrid cloud, where cloud architects and business management decide which cloud services make the most sense to run internally and which should be farmed out on a pay-per-use basis.

Original title and link: Data Scientist and Cloud Architect: The 6 Hottest New Jobs in IT (NoSQL database©myNoSQL)

via: http://www.pcworld.com/businesscenter/article/230285/the_6_hottest_new_jobs_in_it.html

Hilary Mason^[1] and Chris Wiggins^[2]:

We’ve variously heard it said that data science requires some command-line fu for data procurement and preprocessing, or that one needs to know some machine learning or stats, or that one should know how to `look at data’. All of these are partially true, so we thought it would be useful to propose one possible taxonomy — we call it the Snice* taxonomy — of what a data scientist does, in roughly chronological order: Obtain, Scrub, Explore, Model, and iNterpret (or, if you like, OSEMN, which rhymes with possum).

The clearest list of what a modern data scientist is supposed to know and do.

Original title and link: A Taxonomy of Data Science (NoSQL databases © myNoSQL)

via: http://www.dataists.com/2010/09/a-taxonomy-of-data-science/

From Loraine Lawson interview with Jeff Erhardt^[1].

What is R?

R is an open source statistical programming language. The easiest way to think about it is the largest commercial competitor in the states is a company called SAS, and while it’s not a perfect analogy, one way to think about R is as an open source version of SAS. It’s not perfectly correct, but for people who have not heard of R, that’s one way to explain it.

Where can R help?

• analyzing and gaining meaning from collected data
• developing models and extracting the insight from data
• implementing these analytics within an enterprise and disseminating the knowledge across the enterprise

Now are you ready to bet what will be the data processing platform of tomorrow?

Original title and link: R: What Is and How Can It Help? (NoSQL databases © myNoSQL)

via: http://www.itbusinessedge.com/cm/community/features/interviews/blog/the-power-of-r-more-companies-using-language-for-business-analytics/?cs=46325

Rob Karel:

data in and of itself has no value!
The only value data/information has to offer – and the reason I do still consider it an “asset” at all – is in the context of the business processes, decisions, customer experiences, and competitive differentiators it can enable.

Just a different way to correctly say that BigData is snake oil.

Original title and link: Stop Trying to Put a Monetary Value on Data - It’s the Wrong Path (NoSQL databases © myNoSQL)

via: http://www.information-management.com/blogs/data_management_business_intelligence_BPM_ROI-10020057-1.html